Nobody wants to be the bearer of bad news, which is why CEOs sometimes don't get the straight story about strategic data. The solution includes data scientists and three non-traditional data systems.
CEOs and other members of top management have a huge problem with the truth: They rarely hear it, even when it comes from strategic reporting.
It's alarming how thoroughly data is sanitized before making its way to the CEO. Nobody wants to tell the CEO something he or she doesn't want to hear, so, there are filters--even in strategic data warehouses and marts--that carefully massage data into alternative facts.
This is a problem if you're the CEO. How can you run the company if nobody's telling you the truth? Fortunately, with a bit of leadership and an excellent data science team, you can get the information you need to properly lead the company. Consider three non-traditional data systems--the Exploratorium, the Proving Ground, and the Learning Center--that the data science team can build to help insulated upper management know the truth about their company.
SEE: Ebook--Executive's guide to IoT and big data (TechRepublic)
An Exploratorium is a place where you can ask questions. The first step in uncovering the truth about your organization is having a curious mind--you should value questions over answers. Start each day by asking yourself, "What is it that I don't know about my company?"
The beautiful thing about the modern age of data science is that you don't have to rely on answers from people who are afraid to tell you the truth. A data system has no fear of early termination, so that's the better place to ask your question. However, it must be built properly.
Most strategic data systems today are built with layers of intelligence--as they should--but an Exploratorium embodies a different paradigm. Many advanced data systems transform data into information by inference, that is, giving the data a "so what?" factor. Unfortunately, this inference comes with a lens--a perspective on how the inference should be made--and therein lies the problem. Once people realize this information will be viewed by the CEO, there are a lot of people interested in influencing how this data gets translated into information. The Exploratorium just presents data--the raw facts--as they are. It's structured for exploration instead of inference.
A Proving Ground is a place to challenge assumptions. Another good question to start your day with is, "What am I wrong about today?" It might seem odd and inappropriate for a CEO to be wrong in his or her assumptions about the company, but this is exactly the kind of question that will lead you to the truth. Needing to know the answer to questions like this is an even better reason to stay away from human advisors and stick to data systems.
A Proving Ground is an artificial intelligence system that uses data to challenge an assumption. For instance, you might tell your Proving Ground, "I believe our customers are happy with our newest product. What do you think?" The Proving Ground would then scour the company's data looking for evidence to either support or reject your assertion. If there's overwhelming evidence that your claim is not true, you might have a problem.
The Proving Ground works well with the Exploratorium. Once holes are pierced in your initial assumptions, it's time to do some investigation. In our previous example, if our Proving Ground found an unexpected level of complaints about the new product, the CEO might turn to the Exploratorium to investigate how customer service is handling these complaints and what the product development team is doing to fix these problems.
A Learning Center is a place where you can learn how to navigate through your Exploratorium and make the best use of your Proving Ground. This isn't an analytic system per se, but it's an important component of your overall search for the truth. There's nothing more frustrating than wanting to find an answer and not knowing how.
It might also be good to get those humans involved again, but this time stay away from advisors; instead, retain a small support team whose only job is to help you use your new tools. No unsolicited advice allowed.
SEE: Hiring kit: Data architect (Tech Pro Research)
As a CEO, with so many people telling you what you want to hear, it's hard getting at the truth. That's why it's better to find the answers yourself.
You should leave your office and walk the halls, but even then, you may be shielded from the harsh realities of your company. With today's technology, you have the power of vast amounts of data at your fingertips, but it must be structured properly for it to be useful.
Charge your data science team with the construction of an Exploratorium and/or a Proving Ground to get the real answers to hard questions. Otherwise, you won't know what you don't know.
- Why one big data CEO sees Gartner's Magic Quadrant as a blessing and a curse (TechRepublic)
- Under pressure: 4 main stressors for big data leaders (TechRepublic)
- 5 ethics principles big data analysts must follow (TechRepublic)
- BASF: The value of raw data and how to benefit from it (TechRepublic)
- Big Data's 2017: Can more meta thinking free us from current malaise? (ZDNet)