The role of the People Analytics leader - Part 2: Creating organisational culture & shaping the future


The Head of People Analytics is absolutely pivotal in determining whether an organisation is able to successfully implement people analytics and create a sustainable long-term culture of data driven HR.

Arun Chidambaram has helped four Fortune 500 companies build sustainable capability in people analytics, and is widely recognised amongst peers as one of leading proponents and visionaries in the field.

In Part 1 (Questions 1-8) of this series, Arun shared his experience on the skills and capabilities you need in a people analytics team, how these evolve over time and the options in how to align the team to the business. Arun also outlined his five-step methodology for undertaking people analytics projects, which many people have since commented how helpful they found it.



In Part 2, Arun and I cover the following areas:

  • Leading the team: An in-depth treatise on the role of the People Analytics leader including typical challenges faced, the skills and capabilities required, and the evolution of the role in line with organisational maturity and a dynamic external environment
  • Developing organisational culture: Ways to make analytics part of HR and organisational DNA
  • Shaping the future: A look at the future of people analytics and some of the developments we can expect to see
  • Ethics and trust: The importance of transparency, ethics and data privacy in People Analytics. 


Q9: The Head of People Analytics has to juggle multiple priorities, rising internal expectations and a rapidly developing field externally. What do you see as the key responsibilities of your role and how do you balance these?

David, you are right to say that people analytics is a very challenging and dynamic field due to the surge in interest and demand. I split my role into intra- and inter- team responsibilities (as illustrated in Figure 5 below). It is critical for the leader to know each element of this climate well to support their team and also provide a sustainable and high-value service to the business.

Figure 5   : The Inter- and Intra-Company responsibilities of the People Analytics Leader (Source: Arun Chidambaram)

Figure 5: The Inter- and Intra-Company responsibilities of the People Analytics Leader (Source: Arun Chidambaram)

People analytics is a combination of Process, Technology, and Skills (see Q10 and Figure 7) and attaining the right balance between the three is paramount in providing sustainable capability in the long-term.

It should be remembered that the analytics role varies between companies. For example, some companies group reporting and analytics together, whilst others make them distinct and separate. If we limit the focus to analytics, I believe the team will be engaged in nine broad distinct categories of work (see Figure 6 below). As a leader, you have to design business plans, create forecasts and make investment decisions as highlighted on the intra- side (of Figure 5).

Figure 6 –    Nine broad categories of work undertaken by a People Analytics team (Source: Arun Chidambaram)

Figure 6 – Nine broad categories of work undertaken by a People Analytics team (Source: Arun Chidambaram)

Q10: Of the three elements you refer to – Process, Technology and Skills – what are the main characteristics of each of these? Which (if any) is most important? Does this change over time?



For me this is the toughest of the three. You have to get senior leadership buy-in, you need to make sure you are fully aligned to the business plan, understand your organisational maturity for analytics, report to the right person, and develop strong partnerships with others on the intra- side.


I strongly advocate spending time both in and outside the business when it comes to technology. Work with your internal IT group that supports your enterprise analytics teams. This is where you can partner with data scientists with advanced visualisation and statistical backgrounds. They are great resources as are the other business analytics teams in your company. Partner with them to understand how they are working with new technologies. On the vendor side, engage and look to be part of their community, speak to your peers and identify partner(s) that can help you with the business priorities most important to your organisation. Create an environment of pilots and try new things with these vendors. Be careful not to get overwhelmed. You have to accept that you can’t buy every piece of cool technology you see! 


People analytics is fundamentally interdisciplinary in nature. You need I/O psychologists that can understand employee behaviours, economists and statisticians that can analyse the data and experienced HR practitioners who can help guide you with the cultural transformation. Hiring the right team is one of the most important steps in being successful and it’s important not to compromise when it comes to these skills. But equally as important is making sure you hire the right skills at the right time. If you hire a statistician before you are ready for advanced data science, you’re going to end up with one unhappy camper. As a leader you are responsible for setting the right path for the team and ensuring that each member is aware of areas such as:

  • the company culture of decision making
  • how HR works
  • data privacy
  • labour laws across the countries you operate in.

The leader has to balance the eagerness from the analytics team to do advanced work with the maturity level and readiness of the business and HR. It can be a delicate process and a critical one as if either is out of sync then the analytical journey can be in jeopardy.

If you hire a statistician before you are ready for advanced data science, you’re going to end up with one unhappy camper


Q11: What are the most important skills and capabilities the Head of People Analytics must have?

I have found that these five attributes have helped my own success, the teams I lead and the HR/business leaders I serve:

Be patient

Change management is hard in any field and people analytics is no different. There are a lot of moving parts in establishing a successful people analytics function. Timing is everything but as we have already discussed you have to think calmly in introducing new concepts linked to organisational maturity. The common understanding of analytics across HR colleagues is very diverse and you have to furnish the analytical support accordingly. In addition, there is fair amount time the leader spends on non-analytical processes so having patience is a key trait to being successful.

Innovation & Holistic Thinking

The people analytics leader has to have a diverse thought mindset given that they work with people from a variety of backgrounds. For example, business and HR leaders talk less about the data and require the relevance to the business whilst your direct team wants to get into a technical discussion about data and analytics. The people analytics leader also works with a diverse set of people from finance, IT, security, legal, privacy, academia, and external think tanks. Each tends to come with differing viewpoints and objectives so the ability to think holistically is a very critical skillset that an analytics leader should master.

Project and Process Management

The people analytics leader is typically leading a relatively new and evolving initiative within HR so consequently needs to lead from the front and steer most conversations and projects. The leader cannot just restrict their time to the technical aspects of the work but also needs to lead on the non-technical aspects too. For example if you are introducing Organisational Network Analysis, say as a pilot, it’s the role of the leader to identify and manage the project, find sponsorship, design the process, make a decision on make-buy-rent, work closely with legal and privacy, educate procurement etc. The leader has to easily switch between tactical and strategic thinking and get used to working with ambiguity and complexity.

Adaptive leadership

The people analytics leader manages a group of people who are very smart and in high demand. Data science is one of the hottest areas of business and there is an extreme supply shortage of this talent in HR. This means that leading the team can be challenging. As a leader you need to be very clear in setting and managing expectations as well as being open and attentive to the needs of the team. You will have to keep the team engaged, shield them from non-analytical requests, devote time to their development, educate them with regards to data privacy, help them understand how HR works and also the business culture within your company regarding decision-making. As a leader, you also have to create an ecosystem for the team to spend time on research and data. Be careful not to turn their work into an endless repetitive schedule of report generation and instead keep the creativity in them alive.

Broker/Catalyst of Analytics | Brand Ambassador

The people analytics leader has to connect with other analytics cohorts within the business and across the industry. The advantages of doing this include achieving economies of scale on analytical tools by utilising them across the company. Other benefits include knowledge sharing, resource sharing, and identifying career paths for your team (and other talent in the business). 


Q12: In the vast majority of HR organisations, data based decision making is still a growing and emerging field. How can you change the culture and embed an analytical mindset within HR business partners (HRBP), HR and the wider organisation? How do you identify and engage stakeholders in HR and the business to support you in achieving this?

The first thing to remember is that it’s not an ‘us’ and ‘them’ but a ‘we’. We need to first understand the role of the HRBP, HR leader or business stakeholder if we expect them to understand our work. I recommend a process whereby one of the analytics team is involved at the beginning of the project and then stays with the HRBP and business stakeholder right through implementation. By doing this you build mutual trust and become more effective in areas such as:

  • Properly defining the problem you are trying to solve
  • Leveraging the right variables including desired outcomes
  • Understanding the stakeholders you need to reach, the decision-making process and the storytelling and visualisation techniques that are most likely to lead to your insights being actioned upon
  • The external and internal data sources required as part of the project, and also any new data that may need to be collected
  • The legal partners and work councils you need to engage with
  • Data privacy and cultural concerns
  • Partnering with HRBPs and business stakeholders to better see the problem from their side

In terms of embedding an analytical mindset, by all means develop a training program for HRBPs and the wider HR team to enthuse them and make them more comfortable with data. Give them access to some of the tools. For example, I have found that providing the HR community with access to Tableau or a similar tool helps them feel part of our work. Above all, have a learning mindset when working with HRBPs and the HR community; listen more and talk less. Trust me, you will reap the benefit in return.

Have a learning mindset when working with HRBPs and the HR community; listen more and talk less. Trust me, you will reap the benefit in return


Q13: When I speak to other people analytics leaders, one of the big challenges is around prioritising the projects you do. How do you recommend prioritising project requests?

Creating a process to properly define and prioritise projects is a critical step in the evolution of the people analytics team to:

  • Ensure that the work of the team is aligned to key business objectives and challenges
  • Help HR and the business understand what the team is (and just as crucially what the team isn’t) there to do
  • Optimise the workload of the team. For example, by pairing particular projects to team members that have strengths or comparative advantages for solving the problem posed by the project or by taking regular stock with your team and have them be fluid in the work they accept and;
  • Support the growth of the team and investment plan for the discipline

Some of the steps I have taken in the past to support this are:

Plan and align

Creating a business plan and aligning to the HR operating plan early in the planning cycle so that you are very clear on strategic business demands. This reinforces the partnership with divisional HRBPs, supports planning and ensures that the right expectations are set with all stakeholders at the outset.

Create a climate where you can say ‘No’

Creating a climate where you can say ‘No’ to requests that don’t fall under the responsibilities of the team e.g. if reporting is not part of your team then be careful to say no to requests in this area. Otherwise you can expect to be inundated with a flood of requests that will distract you from the work you should be doing. Just because you have the information does not mean you should provide it.

Automate and democratise data

Developing a common dashboard that provides business/HR stakeholders with access to multiple metrics at the click of the button. On top of stemming the flood of requests you’d otherwise receive, it helps with the education of differentiating the provision of descriptive data to the business with analytics.

Share and communicate

Regularly sharing and communicating our work – including the process of our ecosystem: how we work, how we run models etc. I find that the more business/HR stakeholders learn about what a people analytics team does then the number of inappropriate requests you get falls.

Creating an ecosystem of stakeholders

Connecting stakeholders in the business with similar requests so that the project is undertaken once instead of multiple times. Using programs like R, you can run a generalised code to parse out insights for different groups on an as needed basis and essentially productise the request. An example of this is the analysis we produce regarding attrition.



Q14: The people analytics space is evolving quickly. How do you stay on top of all the developments in data sources (e.g. wearables), technology, analytical tools and the scope of projects (e.g. network analysis and organisational design) you can do?

I recommend spending a reasonable amount of time experimenting with new methods and techniques in a lab setting. Part of the collective role of the analytics team should be to identify and connect with new vendors, peer groups and attend key conferences and seminars as well as partner with internal business teams in analytics.

An important point to keep in mind is the need to loop in key HRBPs and HR leadership teams to keep them up to date with progress in the people analytics space through demos and other knowledge sharing techniques. A good example is with Organisational Network Analysis (ONA) where we started to first learn the science behind it and, in parallel, identify a suitable pilot project to leverage this science across the company. We worked with multiple vendors, academia, and thought leaders, and took it back to our lab to better understand the make-buy-rent options.

Try not to get overwhelmed with the hype in the marketplace. Focus on the business problems you are trying to solve and be mindful about your company culture. For example, if your organisation is not ready for projects that include the collection and analysis of wearable data from employees, then don’t do it. Spend time experimenting with new data sources and technologies and wait for the right time. Test before jumping to a solution and be patient.

Q15: What do you believe will be the main trends moving forward in people analytics?

One of the reasons why people analytics is such an exciting field to work is the dynamism and fast-moving development in the space. Some of the trends I expect to see are:

  • The convergence of legal, privacy and data science as demands, experiences and standards/governance become more common between these groups.
  • People analytics will become central to business decision-making and as a consequence will feature more prominently and earlier in the design cycle of HR strategies and programs.
  • Transparency will be the new mantra – the more transparent the company is and the more it democratises its data, the more it will thrive with newer techniques in data science (e.g. wearables, social sensing etc.).
  • As a function, HR will spend more time on measuring the outcomes of its programs and interventions with experiments becoming more commonplace.
  • Analytics talent from other business functions like IT, Finance and Marketing will increasingly see HR as an opportunity for career development. HR should see an increase in the supply of talent in the people analytics space. This will be required as demand for people analytics talent will rise exponentially.
  • As HR starts embracing newer technologies like AI, people analytics teams will be highly relied upon for the development and growth of this capability.  


Q16: Finally, how do we balance what we can do with what we should do? How concerned are you about areas such as ethics and privacy? What advice would you give to those seeking to grow people analytics capability on how to gain employee trust?

We’ve spoken throughout on how ethics and privacy is probably the biggest and most important challenge facing the people analytics discipline. This will only increase in light of the trends I’ve highlighted on emerging data sources such as wearables and AI as well as also legislation such as the European Union’s General Data Protection Regulations (GDPR), which comes into effect in May 2018.

The general advice I’d offer to those seeking to develop their people analytics capability is:

  • Be transparent to the business and above all employees in everything you do. Spend more time communicating why you want to do something and the benefit to employees rather than what you are doing.
  • Work closely with HR, Legal and IT early in the project and again before you communicate results. Make this a core component of your governance process.
  • Don’t take it for granted that your HR teams know everything about data privacy, legal requirements and ethics. Work with them to develop a mutual understanding of laws and regulations.
  • Pay close attention to how you communicate the work of your team, share success stories both within and when appropriate outside the organisation.
  • With new data sources such as wearables, start small with an experiment. Keep it in the lab, learn from it, share the results and only then think about expanding the project.
  • Keep the outcomes simple, measurable and tangible.



I am grateful to Arun for sharing his insights and learnings. I am sure that both Part 1 and Part 2 of this detailed interview will prove invaluable for those already working in or interested in a people analytics leadership role. I’ve certainly learned a lot.

You can connect and/or follow Arun on LinkedIn here and also via Twitter, which Arun has just joined, @SanaksArun.

This article was originally published on LinkedIn in February 2018 - see here.