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Is workplace analytics coming to your workplace?

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Is workplace analytics coming to your workplace?

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With the difficult economic times managers are coming under increasing pressure to get more out of the resources available to them.  Central to this is to ensure that we’re getting the most out of each employee in our team.  Aligned with this is a fierce battle for the brightest talent in the marketplace.

These twin goals have created a growing appreciation for understanding the talent we have, and of course the talent we don’t have.  Workplace analytics is pivotal to this drive to understand our human capital.

A new report by HR company i4cp set out to explore the workforce analytics scene to determine what it is that separates the good from the bad.  It came to a number of conclusions:

  1. High performing organisations take a more calculated approach, using data for strategic, long-term planning.  Nearly twice as many high performers did this compared to low performers.  A similar number were also rigorous in assessing the payback and ROI of their analytics work.
  2. Turning data into information is the most pressing analytics challenge and high performers are better equipped to meet it. A commonly repeated lament among HR practitioners is the difficulty in determining what the data gathered means. This was the top data collection obstacle for all survey respondents.
  3. High performing organisations take full advantage of processes, automation and standards to ensure data accuracy, while low performers rely mostly on manual checking. Twice as many high performers report using company-wide standard definitions as a method for guaranteeing data accuracy. Both high performers and low performers check data reliability, but high performers use automated processes (68% to 38%) to a greater extent, which not only reduces errors but frees up employee time for more pressing tasks.
  4. High performers have HR leaders that are highly engaged in using analytics to drive performance; Low performers by contrast are content to supply data to the executive team. More than twice as many high performers have HR leaders receiving workforce data than low performers (81% to 33%), which suggests a more robust, analytics savvy HR department in more successful companies.
  5. Predictive analytics are underused for human capital measures even by high performers. Predictive analytics can reduce uncertainty and provide an evidence-based grounding to the decisions of both HR and the business.  Both high performers and low performers are still finding their way in developing the skills and technical capability to perform and use predictive analytics.

The idea that high performers use analytics more than low performers is not a new one.  A 2010 study by MIT came to a similar conclusion, revealing that high performers used analytics five times more than low performers.

So how do you go about starting on the data driven path?  The book Calculating Success: How the new workplace analytics will revolutionize your organisation outlines six key steps.

Step 1: Frame the central problem
As with any major project, you need to understand the context within which you’re working.  Why is this project important?  Earlier this year Forrester identified the importance of finding your ‘burning platform’ to aid transition from old to new, and this is just as crucial for a transition to workplace analytics.

Step 2: Apply a conceptual model to guide the analysis
Next you need to figure out what it is you want to measure.  It needs to be something that is fundamentally important to the business.

Step 3: Capture relevant data
It’s unlikely that you have a shortage of data.  The difficulty comes with making sense of the data you have, and then being able to act on your findings.  Try and simplify the metrics you measure so you can isolate the relevant information across business units.

Step 4: Apply analytical methods
Suffice to say, this could be a discussion in its own right, but applying the right analytical methods is key to getting the right insights from your data.

Step 5: Present statistical findings to stakeholders
As with any data, it needs to be presented in a way that makes it easy for stakeholders to take action.  This should be focused around the central problems you identified earlier.

Step 6: Define action steps to implement the solution
Once you’ve identified the areas for improvement you’ll need to create actions to improve them.  This is not a one off process so using the data to underpin a culture of continuous improvement will be crucial.

Do you use workplace analytics in your organisation?


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