Why women (and all employees) should embrace Workforce Analytics

I just read an article entitled “Why Women’s Careers Need Big Data” which talked about a study which was presented at the recent SIOP (Society of Industrial and Organizational Psychology) conference in Houston. The study was looking to get to the root of what was impacting women’s career progression and was performed by David Futrell of Eli Lilly.

I’ve a couple of reasons for wanting to comment on this particular article; firstly, I believe it hits the proverbial nail on the head, and secondly, it demonstrates yet again why Workforce Analytics is something that employees should embrace and not be scared of. According to the article the study concluded that a key factor impacting women’s career progression was “commonly accepted success criteria and organisational structures“.

While the article referenced performance being tied to sacrifices which tend to impact women more than men due to family commitments, I believe the point is more subtle and pervasive. Many performance measurements tend to be inadvertently gender-biased because they often rely on self-promotion (those most effective at selling themselves in the performance review), personal achievements vs. collective ones, and value the highly confident extrovert vs. the highly productive introvert. If we believe all the studies, then these are all areas where women tend to be weaker than men, which makes performance systems inherently biased (and not just to women).

Enter Workforce Analytics…

One of the reasons I like Workforce Analytics is that it has the potential to level the playing field. It can measure what people are actually doing (checking in code or supporting a customer briefing) and align to business outcomes (no bugs in the code or customer deal closed). It can include value measurements that are not always so obvious because they are not directly tied to a personal achievement but are more tied to organizational achievement; such as their role the business network (sharing knowledge, mentoring, being a communication conduit between teams, etc.).

We are not there yet, mainly because we just aren’t capturing enough data to allow us to effectively apply these types of analytics, but we are getting there. Enterprise Social Networks are helping with this, and so is bigdata which is providing the infrastructure through which disparate systems and data can now be integrated and analytics applied across the entire set.

Workforce Analytics can be scary, however in the right hands and with the right level of governance, it can provide a hugely valuable tool for the organization and also for the hard-working employee who doesn’t feel his/her value is being recognized.

6 Comments to “Why women (and all employees) should embrace Workforce Analytics”

  1. I think the main challenge we are going to find is professional’s mindset: few professionals are willing to make people decisions based on facts – rather, several think that intuition is enough. I greatly support your quest for increasing data-supported decisions!


    • Yep, I agree that this transition to an analytics-driven business from an intuitively-driven one is not going to be a smooth ride, but rather a very bumpy one :-)

      This is a challenge across many different parts of the business trying to move to an analytics-driven model, so workforce analytics is not alone, although it does have some additional challenges that make it more complex on many levels (not least of all the current HR mindset). However, on the positive side this transition does happen, it has the potential to have the greatest impact across the business, and not just from a performance management perspective.


  2. “It can measure what people are actually doing (checking in code or supporting a customer briefing) and align to business outcomes”

    And could potentially support the automated construction of de-facto business process models that ultimately describe what an organization does. If you want to describe the release and deployment management process you could use analytics in support of this. Not just describing the “ideal”, but showing all the people involved (usually too many) and the lead times required (eg. this person usually takes 2 weeks to provide an approval).


  3. “Workforce Analytics is that it has the potential to level the playing field.”

    Workforce analytics measures the performance of your employees based on their performance, the best metric there is! You see what makes your top performer a top performer, the nitty-gritty details that separate the good from the best. It usually has nothing to do with gender and everything to do with how your employees go about their day-to-day.


  4. I definitely didn’t mean to imply that performance has anything to do with gender, however if I’m not sure that I agree with your point that workforce analytics is just reinforcing your employees existing performance measurements. It does indeed do this (potentially) since it can bring forward evidence to support performance measurements, however I believe that it can also uncover value employees that aren’t already making the “top performer” metric. In most performance metrics for organizations you have at least 50% of your organization in the middle of the bell curve and differentiating there can be difficult. Even with top performers, this tends to be frequently skewed to the folks best able to “sell their work” as opposed to those that do the best work. There are also other employee characteristics that are hugely valuable to organizations but are frequently not measured or factored performance measurements — who are the information brokers in your organization, the influencers, the team builders, …

    I don’t believe businesses have nailed performance metrics… and I believe workforce analytics can help.


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