People analytics is quickly becoming a cornerstone of modern HR management. By transforming raw data into actionable insights, organisations increasingly recognise its value in making more informed decisions and driving business value.

However, as its market demand and usage grow, so does the need to productise it on a large scale. It will save your people analytics team time, free up resources for other projects, and provide the tools for HR teams to make their data more accessible and meaningful.

In fact, our Insight222 2022 People Analytics Trends research found that Leading Companies in HR data analytics productise their internal people analytics to get the most out of their data.

However, scaling up people analytics and transforming it into a product within an organisation comes with its own set of challenges. This article will explore the hurdles faced in productising people analytics at scale and discuss strategies for these business challenges and achieving success.

Challenges of People Analytics Implementation at Scale

When it comes to productising people analytics at scale, organisations must identify and address several key challenges.

Data Quality:

Accurate data is the cornerstone of any HR analytics initiative, and it requires consistent data management and standardisation to ensure that all data points are both accurate and up-to-date. Without this level of quality control, end users cannot trust the insights gleaned from their people analytics implementation.

Data Governance:

Data governance is critical in large-scale people analytics implementations. It involves establishing processes and policies to ensure that data remains consistent, secure, and compliant with organisational and regulatory requirements. Without it, organisations risk exposing employees and their confidential information or violating privacy laws. Therefore, creating a data governance framework that outlines roles and responsibilities for proper data stewardship from the outset is essential.

Lack of a Data-Driven HR Function:

Without a data-driven HR function, it can be difficult to establish trust and credibility amongst stakeholders, as well as to ensure that decisions are being made in the best interests of the organisation. As such, embedding HR analytics within the HR function and democratising access to data insights is key to achieving success. It will help to ensure data-driven decision-making and that insights are shared with all stakeholders for maximum impact.

Strategies for Productising People Analytics at Scale

Fortunately for businesses, there are strategies organisations can implement to successfully productise people analytics at scale and achieve desired results.

Have the Right Data Infrastructure in Place

The first step in productising people analytics has the right data infrastructure in place to support large-scale people analytics implementations. This includes having a comprehensive and secure data warehouse and a single source of truth to ensure the quality and accuracy of all insights. Additionally, investing in appropriate systems and processes that enable fast access, storage, retrieval, and analysis of HR data is important.

It also requires a strong governance framework to ensure security, accuracy, and compliance. That way, organisations can ensure that their data is handled securely and remains compliant with all relevant laws.

Utilise Automation

Regarding technology, another key strategy for productising people analytics at scale is to utilise automation. Automation can reduce manual data collection and entry errors, as well as streamline processes for collecting, storing, and analysing datasets from multiple sources. This not only increases efficiency but also ensures that HR teams are able to access insights when they need them most quickly. And makes it easier for them to adopt an agile, data-driven approach to decision-making.

Invest in the Right Skills

The success of any people analytics implementation depends on having the right skills and resources in place. This means investing in individuals with strong technical and analytical skills leading people analytics teams, as well as those who understand the key principles of data-driven HR. It also requires organisations to have an agile approach to learning – from investing in upskilling training programs for HR teams to exploring the potential of using external data science and analytics experts.

Start Small and Build Momentum

As Aashish Sharma, VP of Workforce Intelligence at Raytheon Technologies, highlights in his recent discussion with David Green on the Digital HR Leaders podcast, when it comes to scaling people analytics, you have to "Think big, start small, and scale fast".

Ashish founded the workforce intelligence function at Raytheon Technologies. On the podcast, he shares how he and his team were successful at scaling people analytics across organisations by starting with a few smaller projects, building momentum, and then scaling them up.

Start with implementing easy-to-use, self-service dashboards that allow HRBP's to access insights for data-driven decision-making quickly. Then in small increments, add more complex analytics capabilities to support the organisation in the process of uncovering deeper insights into workforce data.

Building on these foundations, you can then construct a people analytics strategy that's tailored to the specific needs and objectives of your organisation and key stakeholders.

Put a Focus on User Experience

This takes us to one of the most important aspects of productising people analytics at scale: understanding the user experience and building a solution that meets the needs of end-users.

The success of any people analytics implementation is reliant on end users being able to access, understand, and utilise insights easily. That's why organisations need to ensure that their solutions are designed with user experience in mind.

As workforce intelligence leaders, you may be interested in shiny new modelling techniques or the latest AI capabilities, but your users may have a different level of understanding. They have different priorities, so it is essential to ensure that you are designing easy and intuitive solutions for end-users – from HR professionals to business leaders – to understand.

In the wise words of Laura Stevens, Vice President of Global Strategy, Analytics and Employee Experience at DSM:

"Never start a project without a very clear understanding of the end user, what keeps these users awake at night, and how certain insights will bring change. So I think people analytics is no longer about doing something interesting; we really need to move the focus to relevance."

The Importance of Managers

Having the right leadership in the deliver is also crucial. As Ian O’Keefe Head of Talent Analytics and Data Science at Amazon stated on The Digital HR Leaders podcast in reference to managers:

“The managers, in large part, are culture carriers for you and if you're relying on the manager's interpretation of data and insight to inform his or her judgment to make a better decision, management capability, leadership capability, the culture we want to carry forward in that conversation is a really important piece of it, too.  So, I think productisation turns the conversation of management effectiveness and culture into one that you can measure a little bit more so than you used to, and you can help improve perhaps a little bit more tangibly and tactically in ways that previously were probably more theoretical and maybe out of reach for some (organisations).”

Scaling People Analytics for Meaningful Business Value

Productising people analytics at scale is something that takes time to be achieved. It takes time, effort, and resources to establish the foundations of a successful people analytics strategy. But with the right approach, creating an effective solution that drives meaningful business value and empowers decision-making is possible.

Start small, build momentum, and ensure you are designing solutions with user experience in mind. In doing so, you will be well on your way to productising people analytics at scale and unlocking the power of workforce intelligence for your organisation and future too.

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