analytics Archives - Littal Shemer Haim

Actionable insights for the right people at the right time

Littal Shemer Haim — Wed, 18 Sep 2019 05:58:10 +0000

(Reading Time: 5 minutes)

How would you define a professional expert in the field of data-driven HR? Certainly, there are many definitions of the People Analytics domain, that may include skills, practices, and responsibilities. However, today for a change, I’d like to suggest a different angle: a professional expert is someone you would always want to learn from and be inspired by. I have the honor to host my colleague from Amsterdam, which definitely fits this definition: Hendrik Feddersen, an expert in HR business processes and analytics, who offers “actionable insights to the right people at the right time”, in a European public sector organization. I didn’t spare Feddersen some hard questions in this interview, and I’m grateful for his thought-provoking answers and his contribution to the diverse opinions in our community.

The path to expertise

LSH: Tell us about yourself, Hendrik, and your background as a People Analytics professional?

HF: Thanks for the interview. I am a senior HR professional, speaker, and the author of HR Analytics Live. I graduated from the Bocconi University in Milan with a degree in Business Administration in 1988 and enjoyed specializing in HR Management, for many years. Having a well-appreciated business acumen, I continuously receive new projects in my current role, to optimize HR processes and HR Information Systems. I’m the Head of Human Resources Information Systems in The European Medicines Agency, which is responsible for the protection and promotion of the public and health, through the evaluation and supervision of medicines.

LSH: There are many paths one can go to reach a People Analytics role. What are the advantages of a path which stems from HRIS offers, and what are the challenges?

HF: At my workplace, I have privileged access to an enormous amount of confidential HR data. My skills in extracting data from SAP and the various SuccessFactors Talent Management modules enable that. Fortunately, I have a strength in nudging action-based on my observations and data extraction. Innovation in HR digitalization comes only on the condition that one understands the detailed HR processes and how those are related to HR data. My challenge, however, is to be able to serve all my internal customers promptly and surpassing their expectations. Yet, excellent customer service depends a lot on up-to-date IT tools.

LSH: Besides your academic background, you are most experienced in on-line learning. To advance one’s skills, would you recommend People Analytics domain-specific programs or general data science programs, and why?

HF: Online learning comes from my insatiable desire for self-development. I learned many of the things that I do now at work, in the last five years. It is an interesting question. To advance one’s skills, I would recommend general data science programs. In the open world, I mean, outside the HR domain, there is so much more that is going on, and people are much more open to sharing their bright ideas. People also receive the credit they deserve. My recommendation is to learn in the open world, and then use the new skills in the HR domain.

The professional community

LSH: Do you think that People Analytics as a profession has an open-source culture? Does openness make a difference in this domain?

HF: I believe that the People Analytics profession doesn’t have an open-source culture. That is a problem, of course, because this way, the People Analytics domain does not develop as fast as data science in general. One of the reasons for this is the HR data, which is, by its nature, sensitive, confidential, and change quickly according to the circumstances. Nevertheless, the People Analytics domain does progress, thanks to proprietary software, and thanks to meeting like-minded professionals at conferences.

LSH: Recently, you published a comprehensive open book about People Analytics practices in R. Tell us about your experience in R. How R is better? Are there barriers to start using it?

HF: Unfortunately learning R demands a steep learning curve. I published all my R code examples applicable to HR. There is no point in keeping them for myself. Any comments for improvement are welcome. I currently use R, mostly for quick and compact operations equivalent to Excel macros. R is much easier to read, and it manipulates data ultrafast. The beauty of R is that it can handle vast amounts of data quickly. There are numerous open-source packages to do all sorts of things. For R, there is a community, while there isn’t one for SAP HCM and SuccessFactors or not one that I am aware of. An open-source programming language is much more fun, and acquired skills are transferable to other companies.

A senior’s perspectives

LSH: You have a perspective of two decades in a very special organization: The European Medicine Agency. How did data-driven HR change during these years in it?

HF: That’s right; in fact, I have been doing the same HR activities for the last twenty years more or less. However, the sophistication I have been experiencing is impressive, and it never stops. The arrival of SAP HCM and SuccessFactors Talent Management modules were a breakthrough in producing vast amounts of new HR data. Of course, with more data come more responsibilities and more hick-ups.

LSH: How did The European Medicine Agency, which is a data-driven organization by its nature, contribute to the development of People Analytics? What opportunity it offered, in terms of culture, talent, tools, and investments?

HF: At the European Medicine Agency (EMA), colleagues are brilliant and highly educated. At EMA data protection is a strength. We started implementing data protection already in 2001. The new GDPR for European Union institutions and agencies has given us further impulse. It provides me with a lot of work: drafting of records forms, compliance and risk assessment forms, privacy statements, and description of processes. The very robust selection procedures are another strength at EMA. We are very objective and transparent in our methods. IT tools are undoubtedly necessary to generate HR data and analyze it afterward. It is also true the other way round: to steer an organization with advanced HR Tech tools, you must use the HR data available. Events take place at a breakneck pace. For example, going paperless meant that several colleagues had to get quickly familiar with HR numbers, digital signatures, and reporting tools.

LSH: We usually use, as People Analytics professionals, the mantra of “impacting the business.” What meaning such a mantra has in the public sector?

HF: The European Medicines Agency (EMA) is, indeed, a part of the public sector. However, since it provides services to patients and the pharmaceutical industry, it is unique. For example, EMA is committed to enabling timely patient access to new medicines. EMA promotes innovation and development of new drugs by European small and medium-sized enterprises. The mantra for us could be creating a supportive and fair work environment for the different generations and nationalities, notwithstanding the pressure to do always better and faster. For me, success is when others in the organization follow my line of thoughts and take actions based on the HR data I am providing.

LSH: What would be your advice to HR professionals who want to be more data-driven? From your experience, what is the right way to start?

HF: I wrote about it recently. HR managers are accustomed to making intuitive decisions based on personal experience or judgment. However, it takes time and patience to identify the correct HR data to base managerial decisions. In my view, it is crucial to gain trust from employees. Data quality is a significant challenge too. Not all HR problems are suitable for People Analytics. The overall aim should be to provide actionable insights to the right people at the right time. To do this, HR needs to have a good understanding of what their audience’s priorities are and be able to show how their analysis directly relates to those goals.

LSH: Thank you, Hendrik! It was a pleasure to host you. I hope you’ll continue sharing your experience and resources. I’ll surely continue to follow your work.

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People Analytics – Build the Value Chain

Littal Shemer Haim — Thu, 30 May 2019 13:01:38 +0000

(Reading Time: 3 minutes)

HR people must acquire better analytics skills. There is no question about that. When HR role vacancies are analyzed, this orientation is listed among the most important competencies. The data-driven part of HR practitioners’ work has emerged rapidly in the last years. All HR sectors must now leverage their data assets to make better decisions, and support all kinds of stakeholders, from employees to executives. They must also understand ML (machine learning) and AI (artificial intelligence) to have ownership of procurement and ethics in the implementation of HR-Tech. But how can HR practitioners close the gap? How can they up-skill and become more analytical?

A secret factor in learning programs

While most academic programs in the HR field still lag, and only a few exceptional programs focus on People Analytics, many other learning solutions can be found online. Wise and agile entrepreneurs, with a strong background in HR, analytics, and tech, already offer learning platforms and an excessive amount of content. But I believe that all of them still lack the secret factor that guarantees up-skilling HR.

Yes, a secret factor. But I’m going to tell you. After few years of training and mentoring HR people in the domain of People Analytics – with different levels of success, I must admit – I think I understand now how to prepare the HR team to embrace a data-driven mindset and People Analytics practices. By tracing the way HR groups in a variety of organizations have built their value chain in People Analytics, I discovered a new ingredient of success.

If you follow my work for quite some time now, you already know that I promote psychological safety in a learning environment to bypass the resistance for change. Or, in the word of a mentee testimonial, in a case study of people Analytics is SMBs – “We could afford to experiment with data, and making mistakes, knowing that we had the support of a professional framework”. However, crucial as it is, that psychological safety is not enough. The keywords here are “experiment with data”, our own data.

Experiment with data – our own data

I honestly believe that HR people can overcome their analytics barriers when they exercise. Online courses do offer a lot of exercise. However, only when HR people practice with real data, their own organizational data, they can bypass the obstacles. Only when they define business questions that are related to people in their organization and practically use methodologies that help them to make key employee decisions, they can succeed in developing the desired skills, and start interpreting and present analytics for people-related decisions.

Practice your own data. As simple as that. It doesn’t mean that HR people should become data scientists. In their training programs, they only need to follow the value chain of People Analytics, i.e., make first steps toward a quick win, with respect to business questions, acquire in-house resources and abilities to executing the first analytic project within the organization, and use the first analytic project to impact the organization.

From my experience, exercising based on real questions, challenges, and data is an important motive. Moreover, such training does not only enable up-skilling but may also be the actual foundation of a data-driven HR.

When done in groups, in which each member contributes according to actual role or aspirations, and when collaboration is established with People Analysts or other relevant roles within the organization, HR up-skilling in the analytics domain is guaranteed.

Featured in the book

"This book is not a typical textbook about People Analytics practices. It offers readers an opportunity to learn and change while enjoying themselves, taking time to contemplate, absorb ideas, and, hopefully, overcome barriers."

"You will find in this book sixteen lessons, organized in four milestones that, from my experience, build the People Analytics value chain."

Littal Shemer Haim

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Your journey to People Analytics makes you cry?

Littal Shemer Haim — Mon, 31 Dec 2018 11:39:55 +0000

(Reading Time: 4 minutes)

Did you ever cut an onion while cooking? If you did, I bet it made your eyes tear. The well-known burning sensation in the eyes is simply a reaction to the sulfur that spread in the air when you destroy the onion’s cells. But what if you peel the layers of the onion one by one? There will be less damage to the onion’s cells, and therefore, fewer tears in your eyes.

The hierarchical definition of People Analytics

People Analytics is just like an onion. This domain of expertise has many practical layers. Its hierarchical definition includes at least five perspectives: C-level and business perspective, HR processes, data in HCM and other HR-tech platforms, data science methods, and the daily activities of the People analyst. If you try to cut through the entire hierarchical structure of this multidisciplinary profession, it will be so hard to grasp, that it will make you cry. Well, at least metaphorically. However, if you explore the layers of this definition one by one, you’ll get a thorough understanding that eventually will enable you to impact your organization – Tearless guaranteed!

The variety of roles that are involved in any People Analytics project within the organization contributes to the complexity of this practice. Notice that in effect, each layer in the structure of People Analytics definition is influencing and being influenced by the nature of the layer on its top and bottom. For example, the data stored in HR-tech platform influences but is also influenced by the HR processes that generate it. This complexity implies challenges in People Analytics activities.

The language of business

A crucial part of your challenge in People Analytics is the effort to establish communication between different professionals. In the hierarchy illustrated in the People Analytics definition, you have a C-level perspective above HR processes and data science beneath. Therefore, you must ensure communication between two kinds of professionals: executives and data experts. I consider this communication as an important layer to peel, in the onion metaphor.

The People Analytics journey enables HR managers to become more strategic because they speak the language of the business. Obviously, they must do so, since People Analytics is all about impacting the business by the right questions and insights derived from people’s data. However, they can support decision making, only if the people who are in charge of data science projects can communicate effectively with business leaders.

The role of the People Analytics leader is considered sometimes as a translator, the enabler of this communication. The People Analytics leader must make sure that the data scientists understand the business needs in workforce-related analysis, come up with the right business questions to analyze and return with the best storytelling with data. The People Analytics leader must also make sure that the owners of HR operations, who may be in charge of BI in the domain of workforce, understand the needs of data consumers among the executives.

Demystify People Analytics

On the other hand, you have executives. They need support too, on their journey to the data-driven organization. Perhaps they need you, the People Analytics Leader, to demystify this domain for them. Business leaders may be familiar with quantitative methods in other domains, e.g., Marketing, Finance, and Operations. But how deep is their understanding of statistical models and algorithms in the field of the workforce? Do they really know how to interpret the insights derived from the shiny tools and methods of People Analytics to the right decisions about people, careers, and employee experience? They surely can benefit from learning some new terms, to avoid the inconvenience experience involved in misunderstanding concepts, methods, and technologies.

Democratizing data is a process, not an outcome

Enabling the communication between the data professionals and the data customers is actually a part of the process of democratizing data in your organization – a significant part of preparing a vital portion of your workforce for the future. Though democratizing data is relevant to all parts of the business, the domain of workforce apparently lags. Implementing tools for telling stories with data within the HR department is important, but it is certainly not enough. The gap in communication must be close too. Closing the gap will enable the process of getting the business question right, ensuring data integrity and transparency, iterating to find the best algorithms, and getting people to use the insights in their decision making.

Therefore, the HR leaders, who are also responsible for learning, must lead simultaneously, toward data literacy among the management and toward understanding the business among the data pros. People Analytics is not about software or cloud services. It is a mindset that should become common throughout the entire organization. Closing the communication gap between executives and data pros is an important part of educating the workforce, and it may save a lot of burdens, just like peeling the onion’s layers, one by one.

Related Course

The People Analytics Journey

An overview of future role of HR leaders in improving business performance by informed decisions about people based on data. People Analytics transforming HR; The Role of People Analytics Leader; Case Studies and Simulations; Emerging trends of HR tech.

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Learning culture, rituals, and establishing People Analytics

Littal Shemer Haim — Fri, 30 Nov 2018 18:54:46 +0000

(Reading Time: 4 minutes)

Business acumen and quantitative skills are vital parts of HR leaders’ role, on the journey to the data-driven organization. I believe you won’t argue with that. However, while approaching the end of 2018, we still see that although the adoption rate of People Analytics is high, barrier overcoming is still slow. As an HR leader, you may ask yourself why your organization is stuck on a certain point in the maturity model of this field.

People Analytics practices are related to HR practitioners’ mindset. Sometimes a mindset change is a key to a successful path in analytics. That’s a significant part of my role as a consultant when helping HR people to find and follow their path in analytics. I decided to be where questions are evolved, not where answers are requested, which means that I mentor HR people in analytics, as opposed to doing analytics for them, or instead of them. But to do so, I must understand their level in analytics first.

Who are the People Analytics mentees?

Guenole & Feinzig, co-authors of “The Power of People”, which is among the People Analytics books I recommend, nicely illustrate different levels of comfort with analytics in HR. Specifically, they present three groups with respect to their current analytical capability: Analytically Savvy, who are formally trained in analytics techniques; Analytically Willing, who are open-minded about analytics and are ready to learn; and Analytically Resistant, who are skeptical and dismissive of the value of a data-based approach.

The key to developing analytical capability among HR people is to provide engaging learning opportunities that are aligned with their level of expertise. Since most HR people I mentor may be defined as Analytically Willing, a good starting point for them, according to Guenole & Feinzig, is to provide foundational education, e.g., a basic online course about workforce analytics, and then put learning into practice by applying techniques to day-to-day work.

However, as much as I appreciate the willingness and the ability of HR people who are Analytically Willing, I don’t see Guenole & Feinzig’s suggestion practically works. The contents presented in online courses are valuable but are mostly general. When applying analytics technics to work, an organization’s specific challenges appear, and the power of will alone is not enough to handle them and to close the gap between theory and organizational reality. Furthermore, the barriers I witness are not related only to analytics practices, but also to the implementation of technology that is sometimes necessary for those practices.

Why People Analytics mentees find it so hard to change?

Change is inevitable, and that is also true in the Human Resources domain. In a recent keynote speaking, Josh Bersin mentioned that the amount of investments in the HR-tech market is huge as the size of the market itself. While all the giant players, e.g., IBM, Microsoft, Google, Facebook, want to be in this market now, most of the investments go to plenty of brand-new companies, according to Bersin. There are so many brand-new technologies that any reasonable HR leader will find it hard to start categorizing them. No wonder why so many HR managers that I meet feel paralyzed facing the rapid change in this field. What would help HR leaders to change, become more data-driven, and relay on state-of-the-art solutions? It’s time to start re-thinking about hacking the human side of digital transformation within Human resources departments.

Scientific evidence connect the challenge of change to the way the human brain is wired and explains why most change initiatives and digital transformations fail. A core driver of the brain function is maintaining safety and stability. Therefore, even a beneficial change can be perceived as a threat. When you lead a change in your organization, you directly conflict with your brains’ core needs. The best efforts of any consultant and even the greatest technological solution are sometimes not enough to overcome evolutionary tendencies.

Overcome change barriers with learning culture and rituals

So, we need an alternative. My suggestion for making change easier and helping against the reflexive resistance is creating new rituals within learning sessions, that would generate a sense of security. Through my experience in mentoring HR leaders and teams, I discovered how effective such rituals could be. When meeting agenda and pace of learning are predictable, and when new social norms such as asking questions and thinking out loud are created, people practice openness and curiosity. Familiarity with the setting gives them a sense of certainty and stability. This contributes to a culture of learning.

In a reality where the reasonable employee has 24 minutes a week to learn, new practitioners of People Analytics need something else. They need to be encouraged and guided, in mentoring sessions, to connect the right microlearning opportunities to their actual analytics tasks. Though I don’t encourage mentees to be dependent only on my resources, but rather teach them how to find and use the right resources to support their advance.

In my People Analytics mentoring sessions the group agreed upon asking anything and considering any thought or idea as feasible. Together we encourage taking risks, making mistakes, but we also celebrate our wins. While acknowledging everyone’s ability and encouraging the unique contribution of anyone in the team, I inspire people to find their own answers, instead of telling them what to do. That’s how they learn how-to-learn, on the flow of work.

Learning culture and rituals are essential for establishing People Analytics functions. I see the results already.

Related Course

The People Analytics Journey

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Can you reinvent career development by using analytics?

Littal Shemer Haim — Fri, 20 Jul 2018 07:12:18 +0000

(Reading Time: 3 minutes)

Among the many business questions that People Analytics leaders face today, the issue of career growth stands out. While organizations struggle with the instability of the workforce, research already points to the fact that internal mobility may be the cure to raising rates of employee attrition. But how exactly can a Human Resources practitioner address such a huge challenge? What would be their first steps?

I was privileged to talk recently with a prominent professional, both in the field of People Analytics and Learning and Organization Development, Orit Cohen (Schwarz), who is leading the People Analytics function at HP, and learned from her perspective and experience, how organizations could move forward with this important topic.

LSH: Do you think that all bosses are created equal, regarding career opportunities for employees?

OC: Well, as there are many leadership styles, it’s also clear that with regards to talent management and development, managers also vary in their ability to motivate, coach, and advocate for their employees. Those who excel, usually take an active part in the recruitment process, conduct unusual interviews, and look for the smartest, most creative, and flexible people who can grow with us, even when they don’t have a requisition open. They also grow and develop their talent by offering them lots of responsibilities, along with guidance and regular feedback, and empower them to do their best.

LSH: This surely contributes to talents’ success. But what happens when those talents become successful?

OC: Eventually, these talents become successful in their own right, and at some point, they would be ready to move on. As a large, global company, we aspire to retain these talents by offering them meaningful career opportunities before they would decide to leave. We understand the global trends and the fight for talent, therefore, it is important for us to focus on this topic and enable managers to support talent growth and internal mobility through talent sharing, so ideally managers would import and export talents internally and allow for career growth, without losing our best talent.

LSH: From the management perspective, it’s not so easy to let go of your best talent.

OC: That’s true. As published by CEB, 60% of HR leaders say managers are unwilling to share talent. This means that even the best managers may find it difficult to resist the urge to hoard their best people. After they have invested their energy in bringing the best talent into their teams and helping them to grow, they find it hard to send them off to the next opportunity, even if it’s just another team in the organization. It appears that managers hoard their talent because they have other performance priorities which may conflict with sharing talent, because they lack visibility to other talents in the organization, and because they focus on the person and not on their capabilities.

LSH: But hoarding your people means your team gets a bad reputation as a career dead end, right?

OC: Though I understand it’s hard to let your talent move on to their next opportunity, it is the manager’s obligation, as a leader, to support their talents towards career growth. It is interesting that, by helping their talent to reach great opportunities out of their team, managers can create a positive reputation as talent catalysts, which makes more people want to join them. So, eventually exporting talent actually helps to import talent.

LSH: So how can this be done? Clearly, employee mobility is important to everybody – the employees, the teams, the managers, and the organization as a whole.

OC: Organizations should facilitate employee mobility through a system that provides stakeholders with information, access, and governance for effective talent sharing across the organization. Such a system can help managers not only to export talent to other teams but also to import the talent they need in their team. I believe such a system will also increase employee satisfaction. CEB researchers found that such a system increased managers’ willingness to share talent by 50%, and consequently improved career satisfaction by up to 13%. This means that to increase employee mobility and career growth, the organization should offer managers more information about talents in other parts of the organization, thus help them to identify skills they need in their teams and understand the skills available elsewhere.

LSH: How do you leverage those insights into the People Analytics activities in your organization?

OC: From a people analytics point of view, we provide leaders with proactive insight regarding the talent who may be ready for their next career move. Also, to foster talent sharing, we want to support leaders by informing them where they do well and where they still have opportunities to improve in the cycle of importing-developing-exporting their talent. Shortly we will also provide managers with more visibility to project-based opportunities for employees, encourage leaders, and hold them accountable for importing and exporting talent, and train managers to become mentors and support career growth. From the employee standpoint, we’ll provide more visibility to the capabilities needed in other parts of the organization so employees can develop and advance their careers.

LSH: Thank you Orit!
I look forward to hearing more about your journey in HP, and about the contribution of People Analytics to employee growth in HP, next week in the people Analytics forum in Tel Aviv!

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Will People Analysts always be human?

Littal Shemer Haim — Tue, 08 May 2018 16:16:58 +0000

(Reading Time: 9 minutes)

(The article was based on my Lecture at the HR & People Analytics Forum Budapest, April 2018. I was really ahead of my time back then. Read also my list of Public Speaking)

We heard the words that every speaker emphasized in this conference: measures, KPIs, metrics, models, predictions, insights. And of course, People Analytics. These are important words. They are all related to our practices today. We have to measure, keep track of our KPIs, use advanced analytics to get business insights. We all do or intend to do, People Analytics.

But will our practices last, facing the rapid change in technology? How will our jobs as People Analysts will change in the future? Will People Analytics remain a job for humans? And if it will, what will we – humans do, when machines can do analytics much better than us?

I decided to be where questions are evoked

I’d like to present to you my future professional self as a People Analyst. I’ll take you to a short journey into my future experience, in fiction, yet realistic, organizational situation. Through my experience, my challenges, concerns, and hopes, I’ll answer the question I raised.

I believe that this glance into the future is essential for us. It enables us to prepare for the unknown, or at least try. As Dan Gilbert mentioned in his book “Stumbling Happiness”, the human being is the only animal that thinks about the future and has the ability to imagine events. Thinking about the future is useful because it evokes action. What actions should we take today in order to practice People Analytics in the future?

Our brain is an “anticipation machine”, so let’s use this function. But before I throw myself into the future, let me tell you a little bit about myself, in case this is our first encounter. I’m a consultant in the field of People Analytics for many years now. I started this journey more than 15 years ago, long before the terms “Data Science” or “Workforce Analytics” have emerged. I actually introduced myself, for years, as an Applied Researcher and an expert in Organizational Research.

My background education is interdisciplinary. It includes studies in the Technion – Israeli Institution for technology, where I graduated in Economics and Management studies, and where I gained my MBA. My studies encompassed a variety of courses in Mathematics, Statistics, and Computer Programming. Looking back, it prepared me well for my current occupation.

But I was always attracted to the human factor. Naturally, I took complementary HR courses – as many as I could. Yet, it wasn’t enough, so eventually I graduated in Psychology, and Positive Psychology, at Tel Aviv University. Research methodology in Psychology is a great asset for questionnaires and other research tools’ design.

I see my whole career on a spectrum between People and Business, and the domain of People Analytics mediates between these two poles. Every transaction between people and organizations can be revealed through data. However, as much as data is thrilling, we know it is not enough.

The key to success in leveraging data to insights is asking the right business questions. It must come first, long before analyzing data sets, using sophisticated machine learning models, or creating an amazing visualization. As a consultant, I understand now that only by being a part of the strategic hub in the HR group, I can access business questions, and can really make a difference, supporting them with the right projects. I decided to be where questions are evoked, not where answers are requested. Therefore, I’m focused now, on exclusive long-term partnerships, and offer my expertise to selected companies, one at a time.

So, in a nutshell, this is my journey in the data-driven HR, but alongside my activities in organizations, I spend time sourcing and sensing HR tech, and it makes me wonder: How innovation will eventually broaden human skills and shape the future of work? Which brings me back to my questions: Will People Analytics remains a job for humans? How this profession will change?

My future professional self as a People Analyst

Significant questions, indeed. In the next minutes, I want to take us out of our comfort zone, by asking about our relevance in the future. How should we change our mindset to stay relevant?

Like many of my fellow People Analysts, I’m an eternal student. I study all the time. My daily reading, writing, and sharing are not exceptional in the open-source culture of the People Analytics domain. Three years ago, when I achieved certification in R programming, and in Predictive Workforce Analytics, I was pretty sure that I’m on the right professional track. I was wrong! I’m convinced today that in my future career I will not have to write a single line of code, and I will not produce even a single predictive model. Let me tell you why.

As I mentioned, I’m focused on business questions. Looking around, mostly on the web, I discovered that most business questions related to people in organizations can already be handled by machines! Technological solutions already enable analysts to combine different data sources that a company has on its people, to tackle business challenges.

The emerging HR-tech scene, which includes dozens of thousands of companies and start-ups, already understands the importance of data in knowing how to manage and engage people effectively. Some platforms consolidate real-time data and give decision-makers valuable insights into their employees, at the touch of a simple button. It looks like soon enough People Analytics can be done without us, without the involvement of actual analysts. Is this really the case?

Absolutely not! We will be needed more than ever. But in a new reality where we no longer needed for statistical modeling and hacking skills, we would have to find something else to offer.

First practical implication: Procurement

People Analysts have a lot to offer. We can keep using technology to amplify, not overtake, our influential role in organizations. We can do so, mainly due to our ability to change. The first important change in this profession belongs to the domain of Procurement.

If analytics is to be bought instead of being produced, someone in the organization will have to deeply understand the business questions and find the best technological solutions that suit each one of them. Someone will have to lead the organization in this puzzling industry, that encompass may be more than 20,000 innovative solutions, and which covers the entire employee lifecycle, from hire to retire. Who could do this better than a People Analyst who already understands how Machine Learning works and how model accuracy is tested? Someone who already knows how to map and access data, and how to communicate it with different stakeholders in the organization?

People Analysts must start to look outside of their data sets, and be open now to HR tech innovation, in order to be ready to lead the process of embracing it. We will point the way and direct the organization, but in order to do so, we have to fill the pulse.

Second practical implication: Ethics

The second important change is the responsibility for data ethics. Ethics in People analytics is to know what is good or bad and practice our role with moral obligation. There is a lot that we can do with the data. However, it might not be what we should do.

The compliance with the GDPR and other regulatory issues being discussed these days is only a starting point. It will surely force awareness of People Analysts to privacy issues. But I think it will also influence employees’ behavior, and People Analysts will have to respond:

When people start exercising their rights and request access to their data, People Analysts will be ready in advance to give them comprehensive information about their data usage. When employees start asking to correct or erase their data, employers will request more transparency and security from HR software providers. Organizations will ensure that they process only the personal data that is necessary for the specific purpose they wish to accomplish, and therefore, they’ll need long-term planning and more serious considerations.

This will probably move the field of People Analytics forward. The implication for employees and candidates is Transparency! But not only… Eventually, since the People Analyst role will include more components of procurement and expertise in HR tech, we will learn, for the sake of regulations and ethics, to ask vendors hard questions and be more critique about model accuracy and data privacy.

Therefore, we’ll contribute not only to a culture of a data-driven organization but also to a safe work environment regarding employee data. Employees and candidates, for their part, will judge employers, in addition to Employee Experience perceptions, by employer ethics in data management, and when they feel secure, they’ll be more receptive and enthusiastic to participate and cooperate with AI to influence their career path.

Demonstrating the future reality

So far, I covered the two main changes in People Analytics: Procurement and Ethics. But how exactly this will be done? I decided to find out how such an occupational change will actually occur, and naturally, I turned to the Israeli HR-Tech ecosystem.

The Israeli HR-Tech encompasses about 80 companies. In a small country with about 8.5 million people, this means a proportion of one HR-Tech company or a start-up per 106 thousand citizens. Quite impressive, don’t you think? Don’t worry, I’m not going to present every one of these companies here. But I do like to describe the research I’ve done on this ecosystem and show you how you can use it to prepare for the future.

I mapped the Israeli HR-tech ecosystem according to five major business challenges of an imaginary organization: Effective Recruitment & Mobility, Optimal Employee Experience, Enhanced Learning & Development, Building Great Teams, and Top Business Performance. For each domain, I tried to nominate the three best solutions, based on my own professional judgment. I started what I would call a procurement screening process, with each of the selected companies, using a questionnaire I designed for that purpose.

My criteria were not completely businesswise. I did not explore start-ups as an investor or as an actual buyer. Start-ups could be in a different stage of their developing roadmap, and that was OK since I only explored them as a sort of proof to my hypothesis. So, what did I ask them?

A procurement process that includes Ethical probing

First, I tried to understand their solution and differentiation, in terms of advantages for three different stakeholders: the business, HR management, and the People – both employees and candidates. Then, I took a closer look at data and business questions. I asked what can be done with data, beyond the product’s main purpose. Founders were asked to describe different aspects of analytics, planned or implemented, such as specific business questions, a user interface for analytics, APIs or other connectivity considerations, regulation, and success stories related to data usage. I believe that this probing process will be part of my future daily routine.

You are probably curious about how startups founders reacted to my initiative. Well, most of them were not surprised at all with this theme, since they already considered themselves as a substitute for People Analytics practices, even if their solutions were not yet sufficient. For others, it was the beginning of an interesting discussion, since my research brought them to start thinking in a new direction. I think that my little research was a contribution not only for the purpose of this discussion about the future of People Analytics but also to some parts in this ecosystem too.

So what actually happened in the procurement process? I received great cooperation. I looked for solutions in those five different business challenges and planned to find the best one for each question and present it in my lecture. To my surprise, during my research, I realize that a single technology can be the answer, directly or indirectly, to all the five questions I posed. This technology was bouncing again and again in every aspect of business questions, so eventually, I decided to concentrate on a single company. In terms of procurement, this means finding one, instead of several solutions, which may be easier and perhaps less expensive for the organization. Therefore, it can certainly be the first priority.

What company was it? What was the technology? How a single technology can address five different business issues? Well, StepAhead was the company, and it is based on Organization Network Analysis. This is an emerging trend in the field of People Analytics. However, this company has an innovative approach in this field too. In my lecture I explored their solution and value proposition, keeping in mind that my focus was the procurement process, and not a comprehensive review about Organization Network Analysis. However, I demonstrated exactly how the company addresses all my questions and what differentiation I actually discovered throughout my procurement process, and while probing the founders. This is a competency that I believe every People Analyst should have. To complete the procurement process, I also had to deal with the issue of Ethics. No matter what machine you implement into your processes, it won’t handle Ethics. Ethical probing is one of the soft skills, which People Analysts must practice. So I asked hard questions about privacy, employee benefits and barriers, and about the “Big Brother” concept.

Technology is exploding in our faces

If you had asked me two years ago how our profession has been evolving, I would have said that it did not change much for a decade or so. But in the past two years, technology changes have been so rapid. Digital Transformation is changing industries and organizations from within. In a sense, technology is exploding in our faces. We can barely imagine how the future of work will look like, let alone our own profession. So how could we possibly know today what should we do in order to keep up with our role and stay relevant?

As I found in my research, gaining two new competencies is the answer. Procurement processes on one hand, and responsibility to the ethical use of employee data, on the other hand, can lead to a data-driven solution to at least five business challenges. These two competencies are the necessary professional upgrade for People Analytics. They will keep our profession relevant in the future. We can’t stop, or even slow, the rate of change. But we can prepare for it, by changing our mindset.

The human brain is not only an anticipation machine, as I mentioned earlier, it is also a sophisticated learning machine. Neuroscience shows us that an integral part of being human is being wired to learn. Our answer to technology is to learn more about these two competencies – Procurement & Ethics.

Humanity is here to stay

But doing so, we will not only keep the People Analytics human. As positive psychology taught us, people are most happy and healthy when they express their full spectrum of abilities. They experience flow when their challenges correspond to their capabilities. They feel meaningful when they connect to something significant and bigger than themselves. All this goodness can be provided in the organization with future applications, enabling people not only to excel, but to express the full spectrum of their competencies, and thrive.

Is technology your comfort zone? No, for most of us. But let’s embrace this opportunity. If you choose to change your perspective, by these two new competencies – procurement and ethics, you will position yourself at the heart of the organization. We can take control of the machines, by ensuring to pick the right ones, for the right purposes and processes, and thus contribute to a better future of work.

To conclude, humanity is here to stay. As much as technology is evolving, our human role will not lag behind.

The post Will People Analysts always be human? appeared first on Littal Shemer Haim.

Key takeaways from People Analytics World, London 2018 – Part 2

Littal Shemer Haim — Thu, 19 Apr 2018 18:49:31 +0000

(Reading Time: 6 minutes)

The 2^nd day of People Analytics World was a continuation of great professional sessions, and delighting hospitality, as I experienced in the 1^st day of the conference. I continued the fascinating exploration of People Analytics leaders who develop their field and provide their organizations with valuable tools that enable actionable insights. In this blog, I share my key takeaways from the conference second-day sessions, case studies, and demos, in which I participated.

#1. Keynote:
People Analytics role in navigating into the future of work

Katie Minton and Neera Ridler-Mayor, both Directors in People & Workforce Analytics at Deloitte, discussed the role of People Analytics in navigating the future of work. They presented an update of research about the future of work and its impact on HR. The workforce of the future will be very different than it is today, as artificial intelligence and robotics advance at pace will enable more work to be done by smart machines. They explored the role that HR and People Analytics need to play to navigate this disrupted landscape, and in particular in the formation of the “Social Enterprise”, which emerges when both the level of collaboration and internal agility and the level of external focus rise. They described the wide future role of People Analytics, that will include areas such as: optimizing business models, dealing with inclusive workforce and environment, driving the future service of HR, engaging in open talent economy, providing data points to direct opportunities for positive disruption, i.e., productivity. They recommended design thinking for People Analytics solutions and using People Analytics approach for People Analytics solutions, i.e., explore colleagues’ needs and demands. Their four keys to become a hero are: think big, start small, act fast, and stay human.

#2. Disrupt:
Be a game changer by techniques and attitudes that are being used in Marketing

Luk Smeyers, Co-Founder and CEO of iNostix by Deloitte guided People Analytics leaders to think like their colleagues from Marketing and apply Customer Experience Analytics to the employees. Smeyers encouraged People Analytics practitioners to get outside of the ‘dark room of HR’, aka their silos, and to use five techniques: hyper-segmentation, A/B testing, investment elasticity, uplift modeling, and statistical forecasting. He described a four-level model of HR transformation, and suggested HR to move first towards (and keep doing) “datafication” and business integration. The next steps would include integration with employees’ digital world and skills of the future. Smeyers considered GDPR a “present from Heaven”, which demands new culture: content-based, co-creation with employees, transparency and employee empowered. He also offered some valuable tips for “starting tomorrow”: use cross-functional team, do iterative work, and avoid silos by negotiating with your provider to access the data behind the dashboards.

#3. Demo:
Create a business impact with strategic workforce planning

Kai Berendes, an Executive Partner at Dynaplan, demonstrated how to create a business impact with strategic workforce planning. While analytics is usually focused on workforce supply, his strategic workforce planning uses holistic models that include both demand and supply, and bridge between business strategy and future workforce, by customizable demand models, a link between job families and skills, and between planning process and technology. Berendes demonstrated how to explore the impact of today’s decisions about people on the future, by simulation with the product. He explored supply dynamics step by step and then moved to demand, to find what roles are missing or no longer needed, using a graphical approach. He also demonstrated how to apply policies to the system, and receive a recommendation, e.g., what to do to close gaps, how to choose between internal or external workforce, and how to explore bottlenecks, competencies behind jobs, and more.

#4. Impact:
Understand employee experience to address turnover intentions, and prevent regrettable losses before they happen

Vanessa Lammers, Director of Global People Analytics & Insights in Nestlé Waters presented a proactive approach to enhance the employee experience and improve retention: the “Engagement Check-Ins”. Since exit surveys are not actionable, Lammers offered an alternative methodology to keep high-risk employees: from a predictive turnover model to a targeted engagement interview, to specific front-line manager intervention. She reviewed how her company leveraged both a predictive model and workforce planning approach to conducting Engagement Check-Ins and shared an online tool that aggregates employee feedback and captures action planning, thus enables a real-time pulse of the organization. Specifically, she described in details an original form that was used after check-ins conversation, for capturing open-ended answers quantitatively, and a dashboard that encouraged managers to fill them. Lammers emphasized the fact that since organizations are social systems, some of the most meaningful and actionable data is qualitative, and meaningful insights come from simply talking to people. Furthermore, managers can play a critical role in employee engagement and retention.

#5. Strategy:
Identify problematic people processes which are causing business problems

Max Blumberg, Ph.D., Visiting Professor at Leeds University Business School, explained how to identify the real challenges of the organization. By generalizing a case study related to a company’s sales, Blumberg showed how important is to know where to focus, to impact the business with People Analytics. When done right, we get organizational capabilities that end-up with KPIs, translated to money, he explained. However, too often, People Analytics addresses other issues, mainly people process relevant to HR like attrition, recruitment, and learning and development. Organizations generate value by investing in productive assets. However, in regards to people, while calculating the costs is easy, it is difficult to assess the value side of the equation. Analytics that address people process seldom provide senior general managers with the guidance they need for allocating budgets between competing assets to achieve their desired business outcomes. Blumberg stressed the importance for People Analytics to address business problems rather than just people problems and suggested a methodology for identifying problematic people processes which are causing business problems, by communicating with senior managers via a survey. This business-driven approach, according to Blumberg, is a good alternative to a data-driven approach.

#6. Disrupt:
Absence metrics enable to compare different operational employee groups

Caroline Williams, Manager of People Analytics in British Airways, demonstrated how the company drives wellbeing and positive behaviors in the workplace through absence analytics. This customer-serving organization depends on the wellbeing of their people to deliver high standards of customer service. One factor in supporting employee wellbeing is the management of absence. However, the causes of absence are often complex and challenging, as are the impacts on costs and productivity. The company uses analytics to better understand absence. The role of People Analytics in monitoring attendance was to create agreed definitions, define metrics, and improve analytics confident. The impact was a self-serve metrics, improved interventions, and integration of data into decision making, towards the goal of a well, happy and engaged workforce. However, it was a long-term project, with two years of validating data and getting everybody to roll the same reports.

#7. Strategy:
Create value by People Analytics practice with limited resources

Michael Tocci, Ph.D., Global Leader Talent Analytics & Insights in Procter & Gamble, offered guiding principles for creating value for the business with People Analytics, and demonstrated how an analytics project resulted in saving millions of dollars, by exploring expatriates costs globally, and considering recommendation, e.g., reducing expats in certain countries, looking for roles that can be located in lower cost locations, exploring necessity of senior managers, and exploring high potential and low performers among expats, and more. He presented how to create a People Analytics function with limited resources (time, budget, and people), and how to create value based on data-informed insights in HR. Specifically, he emphasized that fancy stats are not necessary and credibility is the key.

#8. Closing Panel:
How does HR stay relevant, in the world of automation?

The closing panel was led by David Green and included Steve Bianchi, VP People Operations in Improbable, Nicky Clement, VP HR, Organization Effectiveness, Performance & Analytics in Unilever, Jordan Pettman, Global Head of HR Data, Analytics & Planning in Nestlé, and Jim Matthewman, Consulting Director at Talentspringboard. It addressed organizational preparations for Digital Transformation. Technology is touching every aspect of the organization, and it is redefining the way people work, interact, report, manage and progress in their careers. With the audience contributions, the panelists addressed questions about culture readiness, benefits of digital transformation, data ownership, GDPR, and the relevance of HR in the world of automation. The panelist agreed about the lack of data talent and the misunderstanding of Analytics role. They stressed the importance of customer approach in the digital transformation and expressed their concern about the abuse of the digital world. In a blurred future of work, where gig economy is growing, skills demand is changing, and machine capabilities are leveraging, it is time to go back to creativity, innovation, and the emotional part of our brain, that machines don’t have. People and HR will have to offer a different value proposition, which will include readiness to learn, curiosity, and willing to transform to stay relevant. The new psychological contract will be value for data, but transparency and ethics regarding people data will be necessary.

The post Key takeaways from People Analytics World, London 2018 – Part 2 appeared first on Littal Shemer Haim.

Key takeaways from People Analytics World, London 2018 – Part 1

Littal Shemer Haim — Wed, 18 Apr 2018 20:04:51 +0000

(Reading Time: 8 minutes)

People Analytics World is a leading European annual conference on HR Analytics, Workforce Planning, and Employee Insight, in which I was privileged to attend in April 2018. I traveled to London with huge expectations, to learn more about the contribution of People Analysts, which are now becoming an essential part of HR groups across all industries. The growing importance of data-driven HR was well reflected in the conference’s attendees, both speakers, exhibitors, and delegates. My experience in the event exceeded my expectations. Thanks to the professional sessions, the delighting hospitality, and the great chairing of David Green, I had a wonderful opportunity to explore how HR leaders reinvent their domain, train themselves and their organizations to be prepared for the age of data, and get new tools that enable them to provide insights to maintain a competitive edge.

The conference program was challenging. It was split between three parallel tracks: Strategy, Impact, and Disrupt. I had a hard time choosing between lectures since I found all the speakers and topics relevant and most interesting. Fortunately, the conference organizers offered interactive tools that helped me to plan my agenda. In this blog, I share my key takeaways from the conference’s first day sessions, case studies, and demos, in which I attended. My next blog covers the conference on 2^nd day. In future posts, I may cover many sessions I missed, with some references that I read to recover my horrible FOMO (fear of missing out).

#1. Keynote:
Demonstrate how staffing creates an organizational capability that contributes to competitive advantage

Alec Levenson, a Senior Research Scientist at USC Marshall Center for Effective Organizations, suggested how to make People Analytics a part of organizational strategy. He started with some bad news: we are struggling with data quality while buying some shiny tools, but it won’t lead us to success, since no one in the organization looks at the bigger picture, and own the end to end analysis. Sometimes people in different departments work at cross purposes with each other, yet think that they are pursuing the company’s best interests. While we talk about ROI (Return of investment), this is a short-term financial return, in comparison with a competitive advantage, which is a long-term financial return. What is the return in the domain of people? We need to build capabilities that eventually will show an impact on productivity and profitability. Our metrics should be designed in three different levels: job, team, and business unit. However, we should start with the business level and not job performance, as we got used to. According to Levenson, the business performance causal model goes from the bottom up. A failure to align these three different levels will end with partial success in goals achieving. Productivity is not an individual issue. We should demonstrate how staffing creates an organizational capability that contributes to competitive advantage. Levenson invited us all to learn more, in his new book “Strategic Analytics: Advancing strategy execution and organizational effectiveness”.

#2. Keynote:
Learn some practical lessons from super-intelligent elite sports teams

Bernard Marr introduced his brand-new book “Data-Driven HR”, which offers practical guidance to HR professionals in leveraging the value of data available at their fingertips. Like elite sports, organizations have a huge amount of data, structured and unstructured, on the cloud and on devices, which will eventually change work. In sports, real-time analysis is done by AI tools that replace people who previously coded data, e.g., cameras or sensors that are used to record every move of athletes and teams. Analysis based on NLP enables to produce automated sports reports and replace journalists. Braking data silos on the cloud enables to optimize learning and offers a huge amount of intelligence related to sports players. Data analysis is not native to the sports domain, so new partners are needed, along with new considerations of data security. Marr claimed that most HR teams are data-rich but insight-poor. He outlined a path to more intelligent HR teams and discussed practical lessons that HR teams can draw from super-intelligent elite sports teams: Find future roles in using data. Design data strategy, i.e., contribute to key goals with data. Use the right data instead of big data. Build new capabilities related to data. Create trust and transparency so people will be ready to give access to data for the value they’ll get. Consider data security and ethics. Consider data diversity and use a variety of sources, e.g., devices, social networks, sensors, videos, etc. Move from report about the past to real-time and predictive analytics. Move to process automation while focusing on a strategic role. Find the right partners in new places, e.g., crowdsourcing and professional communities.

#3. Demo:
Transform real-time engagement analytics to personalized management insights

John Murray of Peakon discussed how to combine communication, processes, and technology to build momentum in the organization, creating an environment where employees are engaged, productive, and working towards the same goal. He stressed that Engagement is not just HR’s responsibility. However, there are benefits and challenges in moving to a real-time employee experience analytics model. In his demo, he showed how to build a tailored action plan based on analytics at all levels of management. In particular, managers can own their personal performance by dashboards that provide them with an overview of their team’s engagement data. As an admin, HR can control managers’ access to data and functions, and offer different dashboards for junior managers and senior leaders. The dashboards highlight findings and priority issues, thus help managers to respond effectively. Engagement scores are tracked over time, encouraging managers to continue their ownership over data and performance. Employee anonymity is a concern. Therefore, the platform limits manager access to real-time feedback until a sufficient number of employees have responded. The platform also offers managers the ability to communicate with employees directly, while preserving employee anonymity. The product includes many other features, e.g., benchmarking, employee conversations, Text Analytics, and many more to explore.

#4. Strategy:
Shape HR priorities using analysis and innovative experiments

Brydie Lear, Global Head HR People Analytics in ING, and her colleague Eva Oudeman, Lead Data Scientist People Analytics, covered how the Bank has been building a mature analytical team, moving away from one-off analyses and experiments, towards being asked by senior management to support strategic initiatives. Not only delivering high profile projects but even shaping strategic (HR) agenda using the output from innovation experiments. They described ambitions, the journey so far, the core services, key pillars for success, and how advanced analytics support strategic data-driven decision making. Their portfolio of analytics products includes – Hiring algorithm that reduces manual support and selection bias, by automatically matching CV’s to job profiles and predicting high performance; Continuous listening process for frequent feedback, to understand employees’ perception of strengths and key issues; Diversity projects, for an in-depth understanding of current and expected diversity situation, providing data-driven approach and dialogue on goal setting and realization; Reward solutions, for accurate financial and non-financial recognition, and forecasting, maximizing the return and effectiveness of incentives; Top talent performance, to identify top performers and potential talents, allowing for focused approach and maximum return; Voluntary attrition analysis, for predicting talent at risk to leave ING, enabling pro-active actions to reduce the risk and costs of replacing these key resources. Future add-ins of this portfolio will include team performance, for an in-depth understanding of key ING specific drivers for high and low performing teams, and hidden network understanding, to boost business performance.

#5. Impact:
Think about analytics in the space of competency development and validation

Subhadra Dutta, Head of People Science and Analytics in Twitter, reviewed how the company has been mapping individual competencies and performance stats, and their relation to organizational performance, using employee data and operational KPIs. Competencies are abilities or attributes, described in terms of behavior and key to effective performance. There is a data-based approach for developing and validating manager and individual competencies, and Dutta illustrated how operational outcomes are used to develop and validate these competencies. Dutta emphasized the importance of understanding what keeps employees, what makes them leave, and how the organization can help them to do their best. People join organizations for eliminated time. Therefore, it is essential not only to ensure to offer them great employee experience, but also to measure what really matters in their performance to other things in the business, and validate that. She demonstrated how traditional methodology in psychology research is relevant to current practices in People Analytics.

#6. Demo:
Align people processes that benefit from advanced analytics and adopt an agile mindset

Pauli Dahlbom, Founder of PeopleGeeks, presented a super interesting demo of advanced analytics deployment and success in Musti Group, a leading pet supply chain in the Nordic countries, which has 260 stores in Finland, Norway, and Sweden. The HR group of Musti applied Machine Learning-based sales forecast models, to optimize workforce planning and to automate their scheduling process. Their predictive model proved to work more accurately than the previous sales budgets that the business had built, and it has a huge impact: It optimized contract types and contract hours and enabled significant yearly savings. It reduced the participation time of hiring managers and improved the quality of new hires. The project also enabled to redesigned workforce scheduling and planning activities, to build predictive optimization model to align staffing hours to match expected traffic and to identify top-performing teams and individuals and target them to most important shopping periods.

#7. Keynote:
Challenge yourself with the opportunity of strategic position by a strong evidence base

Peter Cheese, CEO of CIPD talked about the opportunities and challenges for HR when embracing analytics. From productivity to cybersecurity, to innovation and agility, diversity and inclusion, the issues facing business are about people, and yet, the HR base of data, evidence, and insight are fragmented and inconsistent. HR lacks common frameworks and language, focus on this domain not necessarily in the right ways, and perhaps doesn’t have the right capabilities. To put this in simple words, “HR has too much PowerPoint presentation and not enough Excel files”. HR must understand the outcomes and insight needed, recognize the opportunity of collecting information about people, and built a momentum using AI to analyze and interpret it. However, HR has also profound challenges in raising ethics and trust from the people. Their stakeholders are not only the investors, but also the people, the environment, and society as a whole.

#8. Strategy:
Look at data and analytics across the organization from a perspective of collaboration

Michael Cox, Head of HR Business Excellence, Technology & Analytics, and Jordan Pettman, Global Head of HR Data, Analytics & Planning, both from Nestlé, presented the company’s journey to strategic data partnerships across the organization. In this globally distributed, complex, and ever-changing business, the HR team had not traditionally leveraged and managed their data to drive results out of analytical approaches to problem-solving. These two professionals positioned People Analytics as a business enabler, not an HR division, and offered examples for global People Analytics functions and practices. An important lesson is to use the same terms within the finance and HR departments. i.e., use the same numbers for the same reasons. Although these professionals managed to offer a global report catalog, they stress that there is no need for perfect data, and there is no single way to do it. Furthermore, since HR practitioners don’t know yet how to get the right People Analytics talents, it is essential to turn to colleagues from other departments and to connect with analysts who like to share their practices on collaboration platforms.

#9. Impact:
Break out common routines of Employee Engagement analysis and produce actionable insights that worth the executives’ attention

Laurie Bassi warned the audience that it is easy to plow deeper and deeper into employee engagement data, but lose sight of what it means for the actual performance of the business. Employee Engagement measurement has all too often over-promised and under-delivered. Bassi focused on practical ideas to get more value from the investment in Employee Engagement Analytics: Optimizing its “real estate”, doing simple but clever analytics beyond one-size-fits-all, focusing senior management on the key findings and making it easy for managers to act. Bassi offered five essential steps for valuable employee engagement surveys: ask the right questions, link survey data to outcomes data, “mass-customize” findings and recommendations, make it easy to understand, and point managers to solutions. A good starting point would be Sales, because these departments usually have good data, and executives really care about them. Survey questions can also be a proxy to business results. Bassi suggested some axioms for People analysts to repeat daily: The importance of the problem you are working on is approximately inversely related to the mathematical sophistication of the techniques needed to solve it. Outliers are your friends. Less is more. And finally, if you like to appear to be the smartest person in the room – get over it!

#10. Impact:
Set your sights on using your capability to turn HR into a profit center

Patrick Coolen, Head of Strategic Workforce Planning & Advanced Analytics in ABN AMRO shared his experience on set up, governance, methodologies, and outcomes of People Analytics. He covered future challenges: concepts of ‘instant’ analytics and continuous listening. He also offered ideas about opportunities to use People Analytics to generate revenue and direct ROI. An interesting perspective Coolen presented was the idea to start your People Analytics journey at the top of the developmental pyramid, assuming that if you could do that, you could do it all. Another interesting idea he presented was the team dashboard for the research portfolio, which enables us to link a variety of variables from different research to a few outcomes across the business.

The post Key takeaways from People Analytics World, London 2018 – Part 1 appeared first on Littal Shemer Haim.

Workforce data is a mess! What can you do about it?

Littal Shemer Haim — Wed, 10 Jan 2018 20:20:20 +0000

(Reading Time: 4 minutes)

Workforce data are the molecules of People Analytics. No predictive model, diagnostic analysis, or visualization can possibly be created without proper and relevant data. Anyone who appreciates the advantages of data-driven HR should stress quality in HR data. However, when I start a conversation about data with HR leaders, many of them spontaneously respond with a sigh. They know the naked truth: HR data is a mess! Nevertheless, there is so much that HR leaders can do to cope with this challenge, starting today. Let’s start with the following six suggestions, which hopefully will inspire us to face this painful issue.

1. Understand the advantage of workforce data access

Workforce data is everywhere in the organization: HRIS, ATS, CRM, LMS, etc. Business leaders need insights, which derived from that data, to improve business performance. A huge variety of technological solutions are available today, which enable HR people and other non-technical professionals to create insights from the data. The missing link is a desire to access the data, and to use it in actionable ways that reveal new opportunities for the company. The ability to access the data and use it properly will empower HR people to have ownership and responsibility of workforce data, and encourage them to maintain data quality in order to support informed decisions in the organization. Data democratization is a demand for many business domains. There is no reason it skips over HR. Therefore, HR leaders should consider the right tools and training to keep their team’s progress on this journey.

2. Understand the complexity of workforce data

Workforce data may be scattered on many platforms, both in the HR department and in different lines of business. It comes in many formats. Parts of it are structured, while other parts are unstructured, e.g., text fields from employee reviews. Sometimes, the data is not recorded digitally, due to certain difficulties or priorities. In other times, when the data did get recorded, old records are deleted or replaced, due to database structure constraints. Different users may have different needs, which a shared platform does not support, therefore some of them may keep supplement records, e.g., in Excel sheets. Furthermore, when new needs emerge, relevant data may be recorded elsewhere, in different systems. Hence, one of the most challenging issues is the different unique identifiers in different data sources, which sometimes makes it impossible to automatically combine data by matching field. Understanding the complexity of workforce data is the first step to deal with it. HR Leaders must start to get to know workforce data as much as they understand HR processes.

3. Prepare to improve workforce data

The struggle toward data integrity is worthwhile. It yields high-quality data that enable meaningful analytics. HR practitioners should configure their systems in a way that prevents or reduce errors. For example, they may want to eliminate mandatory requirements for fields that are not always available at the time of data entry, consolidate fields with duplicate information, and remove fields with no immediate purpose. When analytic questions are on HR people’s minds, higher the chances that they configure their system in a way that contributes to improved data quality. However, some of them still need guidance in system configuration and data entry processes.

4. Prepare to integrate data from different sources

Throwing all the data into a data lake and hoping for an amazing insight to emerge is a nice fantasy that is about to fade away. Instead, you must pick an important business problem to solve, identify and gather relevant data into the data lake, which will include HR structured data, HR unstructured data, and a variety of data from different lines of business. This involves huge challenges: First, you don’t want to disrupt anything in your business processes. Secondly, assuming you found the data, you must deal with duplications, versions, incomplete data, and issues of unique identifiers. And finally, you must do it fast enough, to face managers’ demands, in accordance with organizational and business challenges. You may find out that IT is not available to help with your initiatives, and worse, IT may lack the HR context to understand the data. Therefore, HR leaders should start reassessing their platforms and exploring the ability to integrate them with other solutions, e.g., their ATS and LMS. They must also be aware of other tools that may be needed: blending data tools (e.g., Alteryx), advanced statistics tools (e.g., R programming), and visualization tools (e.g., Tableau).

5. Prepare to build stakeholders’ trust

Data scientists and People Analysts usually have a hypothesis about the subject in question. In other words, before they dive into analysis, they acknowledge their expectations about the results. They must start their exploration with a question in mind, otherwise, they would not know where to start in the infinity of analytic directions. However, this is not always the case with other stakeholders – employees and managers. They may be surprised, shocked, confused, or embarrassed when exposed to the findings. Therefore, it is important to know in advance something about their expectations, attitudes, and beliefs. Whether the analysis supports or disproves stakeholders’ expectations, the analyst should dig deeper into the data, to provide supporting details. An analyst who anticipates potential questions and concerns can be better prepared with answers and contributes to stakeholders’ trust.

6. Remember the cause: Serving the organization’s goals

For HR to take a strategic role in management, it needs to broaden the scope of its analytics agenda to business questions. By blending people’s data with business data, HR can provide insights beyond HR metrics and may answer questions such as: How good is the workforce in executing the business strategy? It can start to analyze the connections between employee behavior and productivity, predict business outcomes by competencies, and measure the impact of various training programs.

I believe that any HR leader experiences these six angles in the ride to data-driven HR, but the mixture and volume depend on the phase in the journey. Any other suggestions? Please share it in a comment.

References:

Bernard Marr, “What Is Data Democratization? A Super Simple Explanation And The Key Pros And Cons“, forbes.com
Vangie Beal, “Structured data“, webopedia.com
Stacy Chapman, “Silos in Talent Data – Sigh“, linkedin.com
Alyssa Ruff, “How Smart HR System Design Leads to High-Quality Data“, analyticsinhr.com
“Data lake“, en.wikipedia.org
Roger Nolan, “Digital Transformation: Finding Your Data is Half the Battle“, business2community.com
Eric Knudsen, “3 Rules for Building Stakeholder Trust in Your HR Data“, visier.com
Rupert Morrison, “Five mindsets HR needs to get right to deliver business impact“, http://blog.orgvue.com

Related Course

The People Analytics Journey

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People Analytics in fast growing companies: Lead start-ups to data-driven HR

Littal Shemer Haim — Mon, 25 Dec 2017 12:34:10 +0000

(Reading Time: 3 minutes)(A version of this article was published in Raconteur, in partnership with bob)

Mark is the CEO of a fast-growing company. He had fund-raised millions of dollars and received a lot of recognition in the press. From the outside looking in, Mark is a success story waiting to happen. Yet, he is having trouble sleeping. His company is about to release a major product, but many of his best engineers are leaving the company. He lost 24% of his R&D department in just two quarters. How did this happen? And how was he so unaware of the way his employees were feeling?

Getting to the root of employee turnover

The costs of employee attrition are high, especially when losing a high performing employee. They take with them extensive knowledge of the company, relationships within and outside the organization, specific business practices, and much more. The important questions Mark must ask himself now are: What is happening in the company that is making people want to leave,? Who can he go to for help? Is this something he should discuss with human resources?

HR and People Analytics

Unfortunately, many HR leaders have not acquired yet the tools needed to analyze their people data in the right way. They can hold conversations with their employees and try to make sense of certain trends, but in the end, they would have trouble providing Mark with evidence-based answers. This is where People Analytics is becoming increasingly important to growing companies, and particularly to HR. People Analytics expert explores, infers and communicates significant data patterns to initiate and support strategic business decisions related to people in the organization.

Common questions that people analytics can answer include: How can we find more top performers? How can we better engage our highest performing workers? Which qualities do amazing teams have? Which people are most likely to stay in the company or leave it?

Two things are happening in the domain of HR and People Analytics: First, it is being used to predict future behavior based on present data. Secondly, it is being used for the sake of both HR and other departments in the company. Gaining answers to these types of questions can save a company from significant loss.

Why many CEOs need the People Analyst?

In an increasingly competitive space for top talent, a new profession has emerged: The People Analyst. This analyst is in charge of combining all the data a company has on its people to tackle business challenges. Much of the work of the People Analyst can be supported by machines. Many HR-tech companies understand the importance of data in knowing how to manage and engage people effectively. For example, bob, an all-in-one, cloud-based HR and benefits platform, is making headway in this field. This platform consolidates all the rich real-time data of a company into one system and gives decision-makers valuable insights into their employees from this data.

What about privacy and data protection?

As more people are becoming aware of the importance of protecting their data, privacy and data protection plays an important role in People Analytics. Regulations are being put in place to offer rights over employees’ data: Employees must be informed about data usage, data transferring and period of storage. Anyone who analyses employee data will need to follow these regulations.

People Analytics can help

Had Mark hired a People Analyst who can access the right platforms and tools, he would have been able to track how his top performers feel and behave and could have taken preventative measures to stop them from leaving. If you are a company in growth mode, you know how crucial is to retain your employees. People Analytics serve as an important way for you to stay on top of everything that is happening in your company.

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analytics Archives - Littal Shemer Haim

Actionable insights for the right people at the right time

The path to expertise

LSH: Tell us about yourself, Hendrik, and your background as a People Analytics professional?

LSH: There are many paths one can go to reach a People Analytics role. What are the advantages of a path which stems from HRIS offers, and what are the challenges?

LSH: Besides your academic background, you are most experienced in on-line learning. To advance one’s skills, would you recommend People Analytics domain-specific programs or general data science programs, and why?

The professional community

LSH: Do you think that People Analytics as a profession has an open-source culture? Does openness make a difference in this domain?

LSH: Recently, you published a comprehensive open book about People Analytics practices in R. Tell us about your experience in R. How R is better? Are there barriers to start using it?

A senior’s perspectives

LSH: You have a perspective of two decades in a very special organization: The European Medicine Agency. How did data-driven HR change during these years in it?

LSH: How did The European Medicine Agency, which is a data-driven organization by its nature, contribute to the development of People Analytics? What opportunity it offered, in terms of culture, talent, tools, and investments?

LSH: We usually use, as People Analytics professionals, the mantra of “impacting the business.” What meaning such a mantra has in the public sector?

LSH: What would be your advice to HR professionals who want to be more data-driven? From your experience, what is the right way to start?

LSH: Thank you, Hendrik! It was a pleasure to host you. I hope you’ll continue sharing your experience and resources. I’ll surely continue to follow your work.

People Analytics – Build the Value Chain

A secret factor in learning programs

Experiment with data – our own data

Featured in the book

Your journey to People Analytics makes you cry?

The hierarchical definition of People Analytics

The language of business

Demystify People Analytics

Democratizing data is a process, not an outcome

Related Course

The People Analytics Journey

Learning culture, rituals, and establishing People Analytics

Who are the People Analytics mentees?

Why People Analytics mentees find it so hard to change?

Overcome change barriers with learning culture and rituals

Related Course

The People Analytics Journey

Can you reinvent career development by using analytics?

LSH: Do you think that all bosses are created equal, regarding career opportunities for employees?

LSH: This surely contributes to talents’ success. But what happens when those talents become successful?

LSH: From the management perspective, it’s not so easy to let go of your best talent.

LSH: But hoarding your people means your team gets a bad reputation as a career dead end, right?

LSH: So how can this be done? Clearly, employee mobility is important to everybody – the employees, the teams, the managers, and the organization as a whole.

LSH: How do you leverage those insights into the People Analytics activities in your organization?

LSH: Thank you Orit!I look forward to hearing more about your journey in HP, and about the contribution of People Analytics to employee growth in HP, next week in the people Analytics forum in Tel Aviv!

Will People Analysts always be human?

I decided to be where questions are evoked

My future professional self as a People Analyst

First practical implication: Procurement

Second practical implication: Ethics

Demonstrating the future reality

A procurement process that includes Ethical probing

Technology is exploding in our faces

Humanity is here to stay

Key takeaways from People Analytics World, London 2018 – Part 2

#1. Keynote:People Analytics role in navigating into the future of work

#2. Disrupt:Be a game changer by techniques and attitudes that are being used in Marketing

#3. Demo:Create a business impact with strategic workforce planning

#4. Impact:Understand employee experience to address turnover intentions, and prevent regrettable losses before they happen

#5. Strategy:Identify problematic people processes which are causing business problems

#6. Disrupt:Absence metrics enable to compare different operational employee groups

#7. Strategy:Create value by People Analytics practice with limited resources

#8. Closing Panel:How does HR stay relevant, in the world of automation?

Key takeaways from People Analytics World, London 2018 – Part 1

#1. Keynote:Demonstrate how staffing creates an organizational capability that contributes to competitive advantage

#2. Keynote:Learn some practical lessons from super-intelligent elite sports teams

#3. Demo:Transform real-time engagement analytics to personalized management insights

#4. Strategy:Shape HR priorities using analysis and innovative experiments

#5. Impact:Think about analytics in the space of competency development and validation

#6. Demo:Align people processes that benefit from advanced analytics and adopt an agile mindset

#7. Keynote:Challenge yourself with the opportunity of strategic position by a strong evidence base

#8. Strategy:Look at data and analytics across the organization from a perspective of collaboration

#9. Impact:Break out common routines of Employee Engagement analysis and produce actionable insights that worth the executives’ attention

#10. Impact:Set your sights on using your capability to turn HR into a profit center

Workforce data is a mess! What can you do about it?

1. Understand the advantage of workforce data access

2. Understand the complexity of workforce data

3. Prepare to improve workforce data

4. Prepare to integrate data from different sources

5. Prepare to build stakeholders’ trust

6. Remember the cause: Serving the organization’s goals

Related Course

The People Analytics Journey

People Analytics in fast growing companies: Lead start-ups to data-driven HR

Getting to the root of employee turnover

LSH: Thank you Orit!
I look forward to hearing more about your journey in HP, and about the contribution of People Analytics to employee growth in HP, next week in the people Analytics forum in Tel Aviv!

#1. Keynote:
People Analytics role in navigating into the future of work

#2. Disrupt:
Be a game changer by techniques and attitudes that are being used in Marketing

#3. Demo:
Create a business impact with strategic workforce planning

#4. Impact:
Understand employee experience to address turnover intentions, and prevent regrettable losses before they happen

#5. Strategy:
Identify problematic people processes which are causing business problems

#6. Disrupt:
Absence metrics enable to compare different operational employee groups

#7. Strategy:
Create value by People Analytics practice with limited resources

#8. Closing Panel:
How does HR stay relevant, in the world of automation?

#1. Keynote:
Demonstrate how staffing creates an organizational capability that contributes to competitive advantage

#2. Keynote:
Learn some practical lessons from super-intelligent elite sports teams

#3. Demo:
Transform real-time engagement analytics to personalized management insights

#4. Strategy:
Shape HR priorities using analysis and innovative experiments

#5. Impact:
Think about analytics in the space of competency development and validation

#6. Demo:
Align people processes that benefit from advanced analytics and adopt an agile mindset

#7. Keynote:
Challenge yourself with the opportunity of strategic position by a strong evidence base

#8. Strategy:
Look at data and analytics across the organization from a perspective of collaboration

#9. Impact:
Break out common routines of Employee Engagement analysis and produce actionable insights that worth the executives’ attention

#10. Impact:
Set your sights on using your capability to turn HR into a profit center