When I started building our Engagement Analytics solution, www.ibm.com/engage , I really had no clue how I was going to approach privacy. Its taken nearly 2 years and numerous conversations with users, lawyers, employee advocates, work councils, and executives before finalizing on an approach which I believe is less of a policy and more of a philosophy and one that is way more restrictive than most bigdata analytics vendors would consider. It states a "commitment to openness and transparency with our Users, sharing with them their own analysis, and keeping them in the driving seat in terms of the analysis they want to share". Which in summary means that they see all the analysis that is generated about them and that no-one sees their analysis except for them, unless they so choose to share.
Do I see the restrictive nature of this commitment as an impediment to innovation? Absolutely No! In fact quite the opposite, I see this as an opportunity to innovate. By taking a completely different approach, I believe we've created a space to differentiate our solution in several ways.
- Build Trust: Recently privacy has become a hot topic with big data analytics being viewed with a high level of paranoia and in many cases these concerns are justified as there is huge potential for exploitation. This is no different in the workplace where analytics can frequently be perceived as a stick to beat employees with. By defining a privacy philosophy that is simple and doesn't require a law degree to decipher, we help to build trust between employee (analyzed) and employer (analyzer).
- Demonstrate Mutual Respect: As employee engagement falls to all time lows across enterprises globally, and yet employee advocacy is becoming increasingly important, companies need to establish an employer-employee relationship built on mutual respect. By defining a transparent employee-centric privacy model that puts them in control of their own analysis we demonstrate mutual respect. Just because we can say "you work for us, so your data is our data" doesn't mean we should!
- Simplify Global Deployment: One of the challenges that frequently face companies when deploying workforce analytics are the country-specific legal and regulatory frameworks that must be satisfied. By creating a privacy policy that is so restrictive we significantly simplify global deployment of a people analytics solution.
Now you non-believers are probably saying to yourself "all I'm seeing here are Impediments, where are the Opportunities you talk about?".
As we've journeyed on this path to enlightenment — Ok, that's me being a bit facetious :-) — we kept banging into these privacy speed bumps that forced us to slow-down. In the beginning it was a little annoying, but after a while we realized that by taking things a little slower we got to lift our heads, look around, experience the journey, and stop seeing the speed bumps as obstacles. We started to think more creatively. So what does "thinking creatively" look like?
- As an executive, I need to understand how my teams collaborate so what's the value if I can't see their analysis. You can see the analysis at an aggregate (deidentified) level, you just can't see the scores of an individual employee. The organizational view allows you to understand how groups of people interact, how they share information, what types of interactions are most effective, the levels of engagement across your teams, of diversity, eminence, and expertise. You don't need to drill-down to the results of each individual. There is a second benefit to this approach, the very fact of not being able to track analysis back to each individual means that they can be more open and honest about what they share and the data they contribute to the system. This gives you greater and more accurate volumes of data to analyze, and hence greater insight.
- I can't run a Social Eminence Program if I don't have access to employee eminence scores. You most definitely can! There is a common problem today on social media where companies say they want to "engage" with consumers (or employees) and yet their first reaction is to "stalk" them on social media and analyze them behind their back. Is that how you treat someone with respect? Mmmm… Just imagine if instead you reached out and asked them for their analysis. You shared your value proposition (what's in it for them? access to clients, analysts, or conferences) and let them choose to share. Those that want to work with you will say "Yes" and those that don't will say "No". For those that said "No", it's unlikely they would've helped you at a later stage anyway, so you haven't lost anything. Looking at the privacy impediment from a different perspective has helped you establish a program where everyone is a willing participant; you've built a relationship with your Users which you will benefit from in the longer-term.
- How can I run a social performance management program if I can't access an individual's analysis? Again you can, you just need to re-evaluate what this means. The major risk with over-emphasis on analysis of social (or engagement) data is that you will get exactly what you measure. If you reward employees for having high Social Eminence scores, then what will they focus on… getting high social eminence scores. If we believe that an engaged workforce outperforms one that isn't than we need to focus on putting the tools (and analytics) in the hands of individuals, tied to business outcome, so that THEY can recognize the engagement patterns that lead to greater outcome for them; maybe that's closing more customer deals, generating more patents, or implementing more bug-free features. We want to optimize the whole and not the parts, and recognizing the successful engagement patterns of teams we can achieve this.
So for what it's worth, I'm firmly and unwaiveringly of the opinion that a restrictive approach to privacy will enable us to be more innovative, we just need to give things a little more thought and not go for the easy and obvious option. If we want to differentiate ourselves we need to think out of the box ;-)
