Data. It is all about people.

I love data.  I know the power it can bring in its simplest form; and the artful design required to build out the most complex creations.  Data is logical.  It makes an impact.  Data is the difference between opinion and fact.

Data can also be confusing and frustrating.  Data is easily manipulated and the output far removed from the source.  It can be overwhelming in its raw form and questionable once scrubbed and made presentable.

These are the two possibilities of every data story.  Just like Harvey Dent’s coin toss, you may never know which outcome you’ll be faced with: the happy data success story or the state of perpetual frustration and confusion.  

 

For me, data success is not about the tools.  There are plenty of data tools on the market of course, many that look fabulous and others that are fabulous.  I won’t downplay the negative impact a poor platform choice can make, but your successful data solution can be derailed far sooner in the process.

Every data story starts with a person.

Which brings me to people. Every data story starts with a person. It is a person who has a need for insight; a desire for a more complete perspective; the satisfaction of ensuring they have relevant data points in front of them and can connect the dots before making a decision.  I believe this fact gets lost at times in the data-rich world we live in.

Data has become the most sought-after element in today’s business landscape.  Companies are pulling in more and more data sets.  Vast quantities of information that they just can’t live without; a situation that in some cases has more to do with the perception of what their competitors are doing than with the reality of their current situation.

As a data champion, this should be near utopia for me, yet it isn’t.  Far from it.  I see and hear companies awash in data they cannot hope to make sense of.  We are developing metrics because we can, not because they “move the needle”. (Side note: can we just bury that saying now?  May it rest in peace next to “game changer”) 

What I see lost in the sea of data are the intersections with people.  Forget pulling in large quantities of data.  Integrate a new data set into your current data sources where they make strategic sense, based on a well communicated and developed need from a real human being.  This does not discount experimental data sets and their potential – but leave this to the experts (yep, more people) and don’t introduce this information into production data until thoroughly vetted.

In the era of transparency we now have more access to information we simply don't understand.

Reduce confusion.  In the era of transparency we now have more access to information we simply don’t understand.  What is the source of the data?  What happens in the cleansing process?  What logic is applied and what has been filtered out?  Err on the side of caution when creating headers.  Opt for descriptive over brevity.  Business glossaries and documentation are valuable, but if no one looks at these tools you are not reducing confusion.  If your analysts do not have a complete understanding of the information they are working with, how can they confidently and competently produce insight? 

Remove the invisible asterisk next to each result.  You know, the one that indicates uncertainty.  Data quality is not easily understood by all stakeholders.  Clearly break down the spheres of data which you can control and those where the quality may never be 100% in your control. 

I firmly believe the best knowledge transfer occurs in person.   Provide your teams the time and environment to allow that deep level of comprehension to happen.  Quite often all of this this knowledge is contained in one individual leading to a potential single point of failure for an incredibly important part of your business.

Invest in your people.

There are so many technical facets and expenditures involved in growing your data solutions. Do not overlook the obvious non-technical key to your success.  Invest in your people.  Without an educated team of data users, analysts and stakeholders, working in an environment that supports their enrichment, you will be flipping a coin and hoping for the best.   

Glendalynn DixonComment