Demystifying People Analtyics - Part 4

In the previous three articles, we discussed how to get started on the analytics journey and the compelling need for it. We also looked at some of the success stories that drove impact using predictive analytics.

However, to reiterate, the business objective and the reason behind using analytics as a part of the core strategy have to be established. In this last article of the series, we are exploring how to overcome various challenges that an organization may encounter and different approaches to establish a people analytics practice.

One of the key questions, whenever a new initiative is launched in an organization, is will it sustain? Will it be able to prove its value over a continued period? The beauty of an analytics function however lies in the amount of time spent in building it, as the availability of clean data increases so does the possibility of getting better results out of it.

However, before starting on this journey these eight key aspects need to be pondered over and planned:.

Building buy-in at all levels: Any new initiative requires a lot of momentum to sustain itself even when initial enthusiasm fizzles out. For that, advocacy has to be built not only at the management levels but amongst all the stakeholders, and data champions need to be created within the HR team itself. A clearly defined value proposition can take the team a long way.

Key questions: Who are the stakeholders? Who are the beneficiaries? Who are the early adopters? How do we build an appealing business case for analytics?

Assessing & building capability:: An honest look at the current capability and infrastructure and creating a plan for sustained learning for existing and new team members has to be built in at an early stage. This will include building an analytical mindset, a working knowledge of applied mathematics & statistics, and some knowledge of tools and techniques.

Key Questions: Which resources can be leveraged for their existing skill-sets? Which resources would be keen to learn and apply? What kind of learning modalities need to be built-in for sustained learning? How much time does it take to upskill vs hire?

Identifying right business performance metrics: This step addresses the Why of analytics? What is it that we are trying to measure and why?

Key Questions: What are the areas which currently need a deeper understanding? What is the relevance of each of the metrics to the stakeholders?

Ensuring that all relevant data gets captured A clearly defined process and structure is essential to store information in right, retrievable formats. This needs to be combined with a reporting interface, and statistical analysis tools.

Key Questions: Typically, what kind of information will enable a better understanding of causal relationships between people and performance? What are the various data sources? What kind of information is being captured? Is there a way for the analytical engines to interface and ingest data from various sources?

Identifying low-hanging fruits or potential quick wins: We spoke about sustaining momentum, one of the best ways to do that is identifying projects which have a significant impact and could give quick results to build trust in the entire process.

Key Questions: What are the current business issues? Do they seem to have a connection with people's performance?

Creating a multi-disciplinary team: A successful analytics team needs to be multi-disciplinary. As much as we need advanced data-crunching capabilities, we also need those who have functional expertise in various domains to understand dependencies and interlinkages.

Key Questions: What are the main functions for which nuanced understanding is required? Do we have enough people who understand the business context and have skill-sets for analytics? Who are those mediators who can bridge the gap?

Adhering to Data privacy laws: It's important to collect, store, and use data in a way that complies with regulations. Taking into account the local and international data privacy and security laws is one of the key considerations along with ensuring ethical practices.

Key Questions: What is the data privacy law that an organization needs to adhere to based on country of operation? What information is useful and what is not required for sake of analysis? Has consent of employees been taken to use the information for analytical purposes?

Implementing and Following up: Once data has given significant insights, implementation becomes the key, the actions that need to be taken must be taken. Also, data post-implementation needs to flow back into the system to make the entire process robust and accurate for future use. For this, not only do you need people who will take the action, but also those who will help in building a conducive environment for change to happen.

Key Questions: Who are the key change agents? How should a well-defined process look like with appropriate loop closures?

Once the above questions have been answered, multiple approaches can be looked at to embed an analytics team for HR Function.

Creating Center of Excellence: As in the case of Chevron, a centralized data analytics team with people from across the board to identify and work on critical problem areas. Having a dedicated team whose sole focus is looking at business and people performance data and catering to a multitude of stakeholders works well for larger organizations with deep pockets and a larger appetite to deal with ambiguity.

Creating a smaller team within HR Function: A team of specialists rolling up to CHRO who have functional expertise as well as advanced analytical skills. This type of structure will help in building direct accountability in the team to ensure that most of the policy decisions are data-driven and not based on intuitive understanding.

Creating project teams: Identifying problem areas as projects and creating a short-term multidisciplinary team to take those as projects within a given time frame. This could be a great approach to try out as a pilot before going full swing into building a people-analytics team and it also gives a baseline on the current capability of the teams.

Going forward, it is clear that HR will need to blend in technology and analytics in its day-to-day operations to drive better business performance and to ensure that the organization stays competitive and agile.