Even if you proclaim a corporate strategy that incorporates big data analytics with great pomp and circumstance at a town hall meeting, don't assume everyone knows your intentions.
There are three ways to use big data analytics in your corporate strategy: as a core product or service offering (e.g., Cloudera), as a supporting product or service (e.g., Progressive), or as a key organizational capability. If you're employing one of the first two approaches, the use of big data analytics should be conspicuous. If you're trying to build a big-data-driven organization, that message may not be so obvious. In this case, organizational change management is extremely important to your strategy, and it begins with a very basic step that's often taken for granted: awareness.
If you're using big data analytics as a key capability to support your corporate strategy, your first order of business is to ensure the entire organization is aware of what you're doing.
Measure analytic awareness
You can't manage what you can't measure, so make sure you always have a clear picture of how aware your organization is that big data analytics is the most critical capability required to support your corporate strategy. This doesn't mean everyone in your culture needs to become a data scientist; it does mean everyone should value analytics.
Since your team is immersed in the strategy work, it's easy to mistakenly believe your communication efforts have fully covered the extents of the organization -- never make that assumption without an actual measurement. I recently helped a client who was working on a high-profile project for almost a year, only to find out through an awareness survey that half of the impacted users didn't even know the project was in flight.
The best way to measure awareness is with a corporate scorecard. A scorecard is a highly-visible and accessible dashboard (e.g., front page on the corporate intranet) that clearly communicates strategic intentions, easily gives everyone immediate access to salient strategic metrics, and subtly (if not overtly) communicates the value you place on metrics and analysis.
To track awareness on your scorecard, include two values: analytic capability awareness and key capability themes.
- Analytic capability awareness is the estimated percentage of the organization that believes big data analytics (or something close to it, like data science) is the most critical capability.
- Key capability themes represent the responses to the second question in a fashion similar to a tag cloud: scrubbed or raw.
You can obtain these values from a two-question survey: 1) When you think about the key capabilities that are required to support our corporate strategy, what is the first one that comes to mind as being most critical? 2) What other key capabilities do you think are necessary to support our corporate strategy? Since both questions are open-ended, you may want to normalize (i.e., scrub) the responses a bit before publishing. Once you have a good measurement device in place, you're in great shape to build awareness if necessary.
Aim for close to 100% awareness
Your change team should be equipped with the skills and tools necessary to build awareness. You're looking for analytic capability awareness that is close to 100%, so be prepared to take action anytime you see this value below your threshold (95% is reasonable, though it can be higher if you like).
For starters, try to install an organizational habit of checking the scorecard daily. Your scorecard should advertise your intent to build the analytic capabilities of the organization both directly (by making a direct statement on the scorecard) and indirectly (by measuring analytic capability awareness against your stated target). Tease it on the corporate intranet's homepage, and then track clicks to see if employees are viewing it on a regular basis.
Don't rely solely on your scorecard, your all-hands meeting, or a periodic bulletin for awareness. Although these are good vehicles for communication and should be in your change team's arsenal, they are all one-way channels -- your communication plan should favor two-way communication vehicles (face-to-face is optimal). For example, make sure your strategy to build analytic competence is discussed by front-line managers in weekly meetings and in one-on-one sessions. Take time to visit with people but don't quiz them -- the survey will handle it; instead, you should reinforce the corporate strategy's key messages, including the importance of building analytic competence in the organization.
Also, take advantage of social media technology and all the wonderful analyses your data scientists can run against this infrastructure. The next best thing to a face-to-face conversation with employees is a virtual conversation with employees. Top companies are installing internal equivalents of Twitter and Facebook to enhance collaboration and promote employee engagement. You should augment your scorecard with a collaboration platform where employees can ask questions and supply feedback about your strategy. Then, your data scientists can analyze their conversations. If you've cultivated a culture of open and honest communication, you'll get a good sense for how people feel about your strategy, their key concerns about it, and where they still might be confused.
In organizational change management, there's a well-known principle that says, "you can't commit to something if you don't understand it, and you can't understand something if you're not aware of it."
Change starts with awareness, and all too often leaders assume everyone's on board with their strategy, when most don't even know it. If your strategy involves building an analytic-driven organization, it's important that you clearly and incessantly get this message to the entire organization by using the techniques I describe for measuring and engendering awareness.
Share your tips
How do you spread awareness about your big data strategy? Please let us know what techniques have worked (and maybe even not worked) for you.