The role of the People Analytics leader - Part 1: Building Capability

Part 1: Building the team and growing organisational capability. See also Part 2 on the roles and responsibilities of the people analytics leader, how to create an analytical culture and the future of analytics here

As I’ve written before, there are a number of characteristics shared by organisations that have successfully developed and built sustainable capability in people analytics and data driven decision making in HR.

One of the characteristics shared by leading companies is the presence of an inspirational leader – the Head of People Analytics. This article by Jonathan Ferrar, which features in the 40 best HR & People Analytics articles of 2017, captures the ingredients required to be a successful people analytics leader.

A Head of People Analytics who ticks all of the boxes described by Jonathan is Arun Chidambaram, who has been working in the people analytics space for over 15 years. During this time, Arun has helped four Fortune 500 companies build sustainable capability in people analytics.

Arun is deservedly recognised by his peers as one of the leading authorities and visionaries in the space. He is regularly invited to share his insights at conferences as he did last year at People Analytics World in London (see highlights here) and People Analytics & Future of Work in Philadelphia (see pic below and highlights here). 

Arun Chidambaram speaking at People Analytics & Future of Work in Philadelphia in September 2017

THE ROLE OF THE PEOPLE ANALYTICS LEADER - PART 1: Building the team and growing organisational capability

I’m delighted that Arun agreed to share some of his insights in this two-part series on ‘The role of the People Analytics leader.’ Part 1 that follows covers areas such as:

• The skills and capabilities required in a people analytics team and how these evolve over time
• Different options with regards to how the team should be aligned to the business
• A methodology for undertaking people analytics projects
• Crucial milestones in developing the maturity of your team
• Key learnings and tips for success

Q1: Hi Arun, Based on your experience, what are the range of skills you need in a people analytics team?

(Arun) The skills and composition of the team depends on a number of factors including the maturity of the organisation with regards to analytics and also whether the team is also responsible for reporting. If we put the reporting part to one side, the analytics teams I have built and led combine members with backgrounds in data science, behavioural economics, engineering and mathematics. Reporting directly to the CHRO or one of the CHRO’s leadership team is important as it demonstrates to the business and HR that analytics an integral component of the people strategy.

Q2: How should the team be aligned to the business?

Typically, most people analytics teams are initially aligned both by division and key HR interest area. In my experience, this alignment can work well at first, but as demand from the business grows you need to think differently. You need to do this in part to optimise capacity but also to ensure the team is working on projects that are important to the business. Prioritising the work can quickly become an issue and this represents a major challenge for the head of people analytics. To mitigate this, I interview and have regular dialogue with the HR leadership team to jointly identify the top 3-5 topics that are key to achieving the business and HR strategies. I then assign a member of the team as a SME on each topic to manage both traditional and innovative analytics projects.

Prioritising the work can represent a major challenge for the head of people analytics

Q3: Please can you explain what you mean by ‘traditional’ and ‘innovative’ projects?

Certainly, traditional work is restricted to fine-tuning existing general HR programs and leveraging analytics for more value e.g. in areas such as succession planning. In contrast, innovative work involves the use of new and emerging methodologies such as organisational network analysis (ONA) to help solve business problems. How you balance the time you spend on each type of project depends upon your organisational maturity. 

Figure 1 below illustrates the importance of being cognisant of organisational maturity. The top line on the graph shows analytical capability growing at an exponential rate. The bottom line represents HR consumer awareness, which from my experience grows both more erratically and also at a slower pace. Knowing where you fit and the extent of the gap helps the transition and balance between traditional and innovative. 

Figure 1 – Know where you fit and the extent of the gap – Organisational maturity of people analytics (Y Axis = Investment/maturity/offerings etc; X Axis – Time) - Source: Arun Chidambaram

Q4: How does the structure of the team evolve over time? How does this relate to organisational maturity?

Good question and team structure is a subject I’m very passionate about. It goes without saying that the structure of the team will differ between companies, but I believe that the level of organisational maturity also plays a significant role in how this structure evolves over time.

The model I use (see Figure 2) describes my thinking in this area:

Figure 2: Evolutions in the structure and business alignment of the people analytics team (Source: Arun Chidambaram)

Division Aligned

A typical HR structure has a business partner supporting each business with specialised fields like reward and diversity falling under a COE. The most common people analytics structure I’ve witnessed aligns one team member to the HRBPs supporting a group of business units/divisions. As your organisation gains maturity, demand will far exceed supply, and this structure is at risk of falling apart.

HR Theme Aligned

A second way to structure your group, in addition to division alignment, is to understand the key HR priorities for your company and align your team to focus on these key themes like workforce planning and talent forecasting. This method helps in prioritising your work and tackles the demand tsunami to some extent. However and just like in the business unit/division alignment, this structure will not be able to sustain the heavy forces of demand as the people analytics capability gains traction.

SME Aligned

Lastly, as demand grows and maturity continues to develop, I believe that the people analytics function will need to be structured into two main areas: i) Client Facing, and; ii) Subject Matter Experts (or non-client facing) (see Figure 3 below).

Figure 3 – Structuring and aligning people analytics teams with subject matter experts and business facing consultants (Source: Arun Chidambaram)

In this model, a client facing group within the people analytics team connect with business units and HRBPs to understand the problem, manage projects and run post-hoc analysis and interventions. Whilst this group should have basic core analytical skills, their expertise will be weighted more towards consulting, storytelling, communication, and project & program management.

The SME (or non-client facing role) requires deep subject matter expertise across critical disciplines such as data engineering, research and data science, experimentation and design thinking, visualisation/reporting and technology. I envision each SME area being led by an individual who would be devoted to their area of expertise.

Today’s team structures typically exposes members to both sides (SME and Client Facing)—and the potential challenge of this model is that some analysts will find it hard to let go of the other side as they face the decision on what direction to specialise in.

Q5 Based on your experience, what are the key milestones in building a firm foundation for people analytics within organisations?

Drawing on my experience, I’d condense this into five major milestones:

1. Creating a sustainable and long-term analytical capability with an emphasis on delivering business results
2. Forming close partnerships with other analytical cohorts in the business and developing a community of practice to share process, techniques and technology
3. Developing a rigorous 5-step methodology, which all projects go through and which has been critical to success
4. Building relationships with legal and data privacy to better understand the use of data in talent analytics
5. Forming a talent analytics lab for testing analytical thinking and experimenting with new initiatives such as Organizational Network Analysis (ONA) 

Q6: Please can you provide more detail on your 5 Step Research Methodology, and how it has been critical to your success

The methodology for each potential project starts with a dialogue between HR and business colleagues on the problem statement and follows five rigorous steps from writing a research proposal to supporting the business in post hoc analysis and participating in post-action reviews as outlined in Figure 4 below.

Figure 4: Five-Step Research Methodology for People Analytics (Source: Arun Chidambaram)

The five steps can be summarised as:

1. Problem Scoping – this step involves talking to HR or relevant team members to understand the business issue and its impact
2. Conceptual design – for each research proposal that is accepted, my team then formulates the conceptual designs of the project
3. Data – collecting and managing data from the various sources required to investigate the business problem.
4. Analyse - this is a technical step in the process where we spend time building, analysing and testing models
5. Post hoc – this critical step includes assessing the impact of the intervention and measuring the outcome/ROI as well as checking that the model is working to specification and if necessary adjusting as required.

The 5 Step Methodology helps the team as well as HR and business customers in reaching a mutual understanding of the business problem and solving it in an efficient and timely way.

Q7: What are the typical challenges and key learnings you have encountered when building organisational capability and leading the people analytics function?

Establishing what is essentially a new capability in the organisations where I have worked has been both rewarding and at times challenging. The key learnings include:

• Understanding the analytical maturity of your organisation (see also Figure 1 and the response to Q4) is absolutely critical in sustaining this capability
• Balancing both qualitative and quantitative science
• Working closely with legal and privacy - don’t assume your HR team should or indeed does know everything about data privacy rules
• Differentiating analytics from reporting - both are important but you need to be clear on your vision and goals for people analytics.
• Creating the right and optimal structure for the people analytics team to support business goals
• Listening to your HR stakeholders and business colleagues and collaborate more
• Being transparent in your work and focusing on what you are doing more than how you are doing it.

THANKS TO ARUN – STAY TUNED FOR PART 2

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

• An in-depth discussion 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
• How to make analytics part of HR and organisational DNA
• A look at the future of people analytics and some of the developments we can expect to see
• The importance of transparency, ethics and data privacy in People Analytics.

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 January 2018 - see here.