For many organisations, their investment in strategic people analytics results in a lot of activity without a corresponding level of business impact. Dashboards are implemented, data models are built, data literacy initiatives are run, but without a clear connection to business drivers and decision-making, these efforts risk not being worthwhile.
Realising value is about providing insights that shape as well as measure workforce strategy, drive efficiencies, and improve business outcomes. It should help leaders answer complex questions such as:
- Are we investing in the right skills to drive future growth?
- Is our workforce strategy aligned with market demands?
- Are we optimising costs without negatively impacting productivity?
These are the areas where strategic people analytics teams can and should make a substantial difference. Yet many organisations struggle to operate primarily in this space.
The barriers to success fall into three broad categories:
- Technical challenges
- Perception issues
- Capacity and capability constraints
Addressing these barriers is critical to ensuring people analytics teams deliver meaningful business impact and that their valued can be measured effectively.
A common frustration for People Analytics teams is the amount of time spent manually mapping data, cleaning datasets and dealing with inconsistent definitions across systems. Many organisations operate within a fragmented technology landscape, where data resides across multiple platforms with varying and often conflicting structures. Reconciling these inconsistencies can take up the majority of a team’s bandwidth leaving little time for strategic insights. As a golden rule if producing a simple headcount report takes more than a minute (or if this task falls under the remit of the People Analytics team) then your data model and ways of working need examining.
Getting your data foundations in order
Organisations must prioritise developing a robust data model that ensures consistency across systems, integrates across platforms and is fully scalable (we talk a little about readying your data for an HRIS implementation in a blog here). A well-designed model that utilises automation, adheres to governance principles and accommodates data validation can be complex to implement but the benefits of having a strong data foundation cannot be overstated.
The role of data governance in building trust
Data governance is equally pivotal. While it can be challenging to engage the HR function in governance discussions, clear ownership and accountability are critical for building trust and confidence in analytical outputs. Poor governance leads to unreliable data and erodes stakeholder confidence, although too much rigidity can prevent agility and timely decision-making.
Even with high-quality data and clear governance, the People Analytics team often struggle to establish itself as a strategic function rather than an operational reporting service. While operational reporting is valuable, it has a different purpose and requires a distinct skillset from strategic people analytics. Less data-literate stakeholders can use these terms interchangeably, leading to the expectation that the analytics team primarily functions as a reporting service.
A lack of executive sponsorship can further limit a team’s ability to focus on business-critical insights. Teams often become reactive, producing reports that do not influence strategic outcomes. To reposition themselves as enablers – or better still definers – of organisational strategy, teams must focus ruthlessly on high-impact business problems. One way to do this is through targeted pilot analyses which resonate with the wider business. By driving immediate and tangible improvements, a team can create demand for more of the same.
For example, instead of simply reporting on workforce demographics, a pilot project could analyse how workforce composition affects business performance in a specific market. This approach provides stakeholders with valuable insight while demonstrating a direct business impact and, implicitly, how good people analytics can directly contribute to solving business challenges.
The importance of cross-functional collaboration
A key enabler of this shift is building a strong relationship with Finance. Anyone who has spent time in people analytics will have found themselves in a situation with conflicting workforce numbers to Finance due to different methodologies and assumptions. Instead of getting stuck in endless reconciliations, teams should invest time upfront to understand these differences and align on definitions. This can shift the conversation from ‘Why don’t our numbers match?’ to ‘What is this telling us, and what decisions should we make?’
When senior leaders and other functions see people analytics as integral to strategic decision-making, it creates a mandate for increased investment, allowing the team to focus on business-critical issues rather than a long list of reporting requests.
Even with the right data model and sponsorship, many teams fail to focus on the right problems or lack the necessary skill mix to answer complex questions. They are often inundated with one-off requests, leaving little room to work on strategic analytics. Some teams also lean too heavily on analytical modelling and data science skills while lacking the HR and business context to interpret and communicate findings effectively.
Is analytics really embedded in your HR practices?
Establishing clear prioritisation frameworks focusing on high-impact areas can help address this issue. Additionally, embedding analytics within HR processes, such as integrating predictive models into workforce planning, or optimising HRIS functionality can ensure that insights are continuously leveraged rather than treated as standalone reports. A successful people analytics team requires the right blend of technical expertise and consulting skills. Without this even the most advanced insight risks being misunderstood or ignored.
Creating value in people analytics requires overcoming technical, perceptual, and capability related challenges. An additional challenge is demonstrating a clear return on investment. Organisational performance is influenced by many factors, from macroeconomic conditions to leadership effectiveness, making it difficult to understand how an analytics team has contributed. No single metric can fully capture its value. Instead, teams should focus on a combination of business outcomes (productivity gains, cost savings, risk mitigation) and behavioural changes (decision-making confidence, product adoption). These indicators, whilst not always perfectly quantifiable, provide a meaningful assessment of how analytics is shaping workforce strategy.
While the journey to realising and measuring value is complex, the potential rewards are significant. Organisations that successfully integrate people analytics into their strategic decision-making can gain a substantial competitive advantage. By taking a structured approach businesses can ensure their teams deliver real, measurable business value.
If you’d like some extra listening material, we’ve also released a podcast on how HR can improve the quality of its data – which you can listen to here. Or, if you’d be interested in talking to Nancy Allen, the author of this article, or anyone in our People and Workforce Analytics team, then drop a note using the form below and ask to speak to a member of the team – we’d be happy to chat.
