Earlier this month I met with an industry analyst who shared an astonishing fact: a Top 10 Fortune 500 company recently built an in-house workforce analytics solution — and had 7,000 employees assigned to manage it. That’s right, seven thousand. The question many people would ask is, why are they trying to build their own workforce analytics solutions when there is an entire market dedicated to this?
The reason is simple — workforce analytics data is typically siloed within human resources teams and limited to things like employee demographics, sentiment, compensation and benefits, and performance reviews. This data alone isn’t enough to truly understand how work gets done, especially in a world of hybrid work and Generative AI. Workforce analytics solutions are prime for disruption.
Most companies have accepted that some form of hybrid work is here to stay. They’re now wrestling with related organizational and operational issues, from how to improve productivity and efficiency to planning and budgeting for the future. The problem is, with digital work, it’s difficult to convert massive streams of work activity data into business insights that help leaders leverage their most valuable resources.
When you have people working at home, people working at the office, some working 8-3, others 10-5, it’s hard to connect the dots between how all that effort (inputs) yields results (outputs). Which makes it even more difficult to know if workforce investments are paying off.
Labor costs account for as much as 70% of total business costs. Yet leaders continue to struggle to correlate workforce investments to metrics, often relying on blind faith that they are driving results.
I agree with McKinsey, that “companies that adopt a more people-oriented focus along with a more challenging and empowering organizational culture have a lot to gain. In addition to boosting financial returns, they can improve their consistency, resilience, talent retention, employee loyalty, and reputation — and these are the hallmarks of companies that thrive over the long term.”
Yet organizations cannot improve what they cannot measure, and today’s leaders are flying blind.
A Microsoft survey confirmed that 85% of leaders found the shift to hybrid work has made it challenging to have confidence that employees are productive, noting, “Many leaders and managers are missing the old visual cues of what it means to be productive because they can’t ‘see’ who is hard at work by walking down the hall or past the conference room.”
Some companies are forcing employees back to the office merely to “make use” of paid space, while others are investing in business transformation and training programs to improve efficiency and optimize costs. Eager to get ahead, many have embraced AI to accelerate those efforts.
With millions of dollars at stake, it’s no wonder some companies have 7,000 employees working to understand how their workforce investments measure up. I don’t know the details behind how that Top 10 Fortune 500 company implemented its workforce analytics solution. But I do know it shouldn’t take 7,000 people to comprehend how your team works — no matter when, where, or in what role they do so.
Too often I’ve seen companies struggle with solutions that paint either too narrow or too broad a picture of employee productivity — limited by time-bound static data and devoid of critical context. It’s nearly impossible to reconcile these different pieces into holistic insights to inform (and evaluate) strategic decisions.
Maximizing return on investments related to workforce utilization and labor cost, team productivity and tech adoption, and office space planning and management requires real-time work activity data that reflects the present reality of your hybrid work environment.
We’ve seen this in our own customer base, where the use of modern workforce analytics has driven powerful business results:
- One company improved productivity per employee by +36 mins/day, yielding $4.2M in productivity gains
- Another customer saved $800K in CRM licenses by identifying low-volume and inactive users
- A healthcare billing processor saved $500K using working-hours data to audit and reconcile hours billed by contractors for payment
- Another organization closed $600K in open requisitions by reallocating work from overutilized employees to underutilized employees
Measuring ROI can be a tricky proposition, and everyone has different ways of doing so. But regardless of how you measure and monetize workforce outcomes, the foundation you work from should be the same: based on accurate workforce data that easily and dynamically evolves with business needs.
Written by Heidi Brennan-Farris.
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