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If you work in people analytics, this’ll feel familiar:
Leaders want razor sharp workforce decisions, powered by reliable AI and predictive analytics. But the reality is, your team rarely receives the tools or support they need to make this a reality.
When funding, headcount, or technology fall short, you get sky-high expectations with skint resources. It’s like being asked to build a skyscraper with a basic toolset. This alignment problem keeps your people analytics strategy from realizing its full potential.
So how do you close that gap?
- You identify the HR analytics tools and technology you need.
- You get leadership buy-in for what you’ll achieve with those tools.
- You secure the people analytics funding you need so that you can invest in said tools.
At People Analytics Summit Toronto, Steve Hall laid out that exact process. Listen to his full talk here, and pour over the key takeaways below.
How to Build a Business Case for HR Analytics
To build your HR analytics business case, you need to clearly define:
- What tools the People Analytics team needs in order to accomplish its goals
- Why they’re necessary and worth investing budget in
- Who will have a say in whether your asks get approved
Step 1: Map Out the Decisionmaker Landscape
Before you build your business case, you need to understand who will have a say in approving it. It’s not just about identifying individual stakeholders, it’s about mapping the landscape they live in. Who influences them? Which departments are gaining more of a say? What are their priorities and what arguments will resonate with them?
For example, Sapient research noted a 30% increase in IT owning HR tech procurement in the past 2 years. You need to make an effort to find out where buy-in lives in your organization, and speak to/form a relationship with those involved.
During those conversations, make sure to:
- Demonstrate yourself as an unquestioned expert in people analytics challenges.
- Have a defined vision for what you plan to achieve.
- Show a clear understanding of how your tool of choice will get you there.
Communicate with everyone, even those who may not be explicit decisionmakers. Get widespread input and insights, in part because you never know whose point of view will influence the ultimate decisionmaker. Be as thorough as you can.
In his speech, Hall noted a case where a People Analytics lead spent months planning and securing buy-in, only to have someone who she hadn’t considered raise their hand and say this was the first they were hearing of her initiative, which delayed it by 12 months.
Step 2: Build a Business Case that Leadership Cares About
One of the biggest mistakes people analytics teams make when trying to convince leadership to invest in HR analytics is framing the problem incorrectly to leadership. Saying “this is hard for my team” – that’s not how you get funding for people analytics. Instead, translate your needs into the business outcomes that will resonate with stakeholders–essentially argue for HR analytics ROI.
For example, explain why the right technology will result in:
- Faster business insights
- A higher quantity of impactful decisions
- Greater accuracy in how those decisions are reached
- Reduced risk across the business
Don’t frame it around how your team will use the platform. Frame it around how the platform supports the business at large with a sophisticated HR data strategy.
Highlight the Cost of Doing Nothing
Good people analytics tools cost money, and that investment is the first thing leaders will hone in on. Your job is to redirect their attention to the real cost: the cost of doing nothing. Doing nothing is not neutral.
It has tangible negative effects, each with associated costs, including:
- Slower decisions
- Poorer quality decisions
- Missed opportunities
- Lost revenue
- Higher attrition risk
- Lower productivity
- Inconsistent metrics across teams
- A company wide data set that AI can’t fully understand or use
Effectively, all of the risks that come with not doing people analytics right, are the risks of not recruiting the right tool for your team.
Step 3: Identify the Right Solution
All of this labor leads to a net zero improvement if you don’t get the right people analytics tool. The most important thing to remember is that you don’t need a dashboard vending machine. Dashboards often just answer questions that no one is asking. You need a repeatable system for producing decision-ready insights. So why are dashboards not enough in people analytics?
What does the right system actually look like?
- The Single Source of Truth: It integrates disparate data sources seamlessly, connecting core HRIS (like Workday or SAP) with ATS (recruiting), LMS (learning), financial data, and performance management tools.
- Speed and Accessibility: Data is processed in near-real-time. Leaders can access multi-dimensional insights instantly, not weeks after a quarter closes.
- High Data Integrity: The "data house" is in order. Definitions (like what constitutes a "headcount" or "attrition") are standardized across the entire global enterprise.
- Democratized Insights: It features intuitive, self-service storyboards and interfaces that allow non-technical managers and executives to find answers safely on their own.
- AI-Enabled Capabilities: It leverages enterprise AI and natural language processing, allowing leaders to type direct questions (e.g., "Which departments are at the highest risk of critical skill gaps next quarter?") and receive contextual, accurate answers.
- Predictive, Not Just Descriptive: It moves past telling you what happened (historical reporting) and focuses on what will happen (predictive modeling) and how to fix it (prescriptive analytics).
The People Analytics team should vet potential tools with these criteria in mind, and can find more considerations to weigh in our comprehensive Buyer's Guide for People Analytics technology.
3 Common Alternatives That Derail Progress
Many teams fail because leadership mistakenly believes that one of the “easier” paths below will better serve the company. These include:
1. The “Let IT Build It” Fallacy
Countless People Analytics teams run into the question of whether their IT team should build a data platform in-house. It’s in your best interest to veto that option. IT has clear mastery in other areas, but they lack the context and expertise needed for the nuanced nature of people data. An in-house system also takes incredibly long to build, is functionally outdated the minute it launches, and requires constant downstream maintenance.
2. Thinking the HRIS Can Do The Job
HRIS platforms are great for storing data, but they weren’t purpose-built for advanced analytics. Simply put, they’re a system of record, not a system of insight. When you try to use them for something they weren’t built for, you constantly run into stumbling blocks. Predictive analytics in Workday, for example, is extremely difficult because you’re constantly stitching together snapshots of what was true at one moment in time in order to reconstruct a historical view. This is the exact wrong approach if you want to execute data-driven HR decision making.
3. The “Shiny Object” Trap
Stakeholders who don’t use the tool can get “stuck on” a tool that wouldn’t ultimately be the best choice for the people analytics team. In this case, you need to refocus them on fostering the long-term capability of the People Analytics team, not indulging an unsupported impulse.
These mistakes can lock you into a path that limits your future.
Final Thoughts
The benefit of people analytics doesn’t dead-end in the HR department. It ripples out across the entire organization, and should be treated with a gravity that reflects that.
When you get strategic and deliberate about how you’ll fund the tools you need, outcomes change in your favor. The first people analytics tool you should try on for size? One Model.
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