Data Fantasy

Not everyone gets to say they love what they do for a living. That sentiment is not lost on me as I am one of the few (hopefully an exaggeration) who get to do what they love to do. I have to admit though, it has taken a very long time to get to this point. I have had my share of disaster jobs and although they probably just made me angry at the time, I now realize they prepared me for the excitement I live today. One thing I often reflect on is my interaction with vendors. I am, unfairly, going to lump everyone who does business with a company, not employed and managed by that company’s HR department, as a vendor. Don’t get me wrong, the vast majority of you are amazing people who genuinely care about the outcomes you deliver for your partners. The point is to try and understand the ever-present manipulation of leadership, in any organization, by sales staff from various service organizations who’ll say anything to get a foot in the door. Again, this is not every salesperson as I have many friends in this space who are tasked with that difficult and demanding role. However, there are a select few in that particular profession who are very good at filling the heads of unsuspecting executives with the idea that product ABC can easily and efficiently plug into your current data environment and deliver immediate results. Yes, this is a data-focused rant, so you can get off at this stop if you are not interested in data.

I spend much of my time as a data executive, undoing the damage perpetrated by sales people. These individuals peddle various data technologies to executives who are desperate to make a difference in their organization and, in turn, fall prey to silver-tongued pitches perpetuating preposterous propositions. Sorry, had to adjust my alliteration valve there a bit. I know there are some amazing technologies out there, so I am not offhandedly dismissing these folks or the profession; not by a long shot. I also know, however, that timely, accurate, and effective insights are derived from quality data. Data must be prepared, cleansed, and curated to ensure that it is fit for use and no technology on the market (yet) can replace good ol’ fashioned data governance. I can see the fire now as a hundred tech gurus head’s explode with anger because they know their software or platform does what they say it does and I don’t doubt them for a minute. How can I accuse the sales folks of manipulation while still supporting the claims made of their products? Simple, we are swimming in propaganda and words are the weapon of choice in the battle for company dollars. It’s typically not what is said that steers the executive in the wrong direction. When leaders are trying to come up to speed and stay relevant in the data game often they are just looking for that hand to help them up the next step. The problem lies in what is not said that drives some very commonly held beliefs around data systems such as plug-n-play. No one mentions the work required to get your data in order to plug into that perfect solution.

Let’s pretend that I am an executive at a large financial firm and I want to understand not only how many loans my organization is booking but also how many they will book next month as well as who on the sales staff will make that happen. Let’s say the data we need for this thought experiment is loan origination system data, human resources data about my sales force and Finance and Accounting data regarding what we pay these people to do their jobs among other business costs. Each of these data sets sits in at least three systems or databases, if not more and typically, not one of them has been linked in a way that relates the data without duplicating, excluding, or misrepresenting it in some fashion. How do you take those datasets and simply drop them into a system built by people that have no intimate knowledge of the nuances of your organization? “But angry data guy, they have an industry data model for this stuff”, you say? Since when was your organization created and grown from someone else’s template? My guess is that your organization is highly nuanced and although there may be some similarities to your peers, when you pull back the lettuce, there is a lot of secret sauce there. Seriously folks, those nuances matter and no salesperson or tech company should be telling you that your organization is not unique. It is very unique and that is what provides you with your edge.

So what do we do about this? Rather than leave you with an annoying rant full of disjointed analogies, I am going to make a few suggestions. Here are three of my keys to success in building and maintaining a successful data organization:

  • Assess the current state of your company’s data

There is data all over the organization and much of it is being used by various departments. That said, some of those departments are demonstrating examples of data management practices that should be replicated across the enterprise. Remember, consistency counts.

  • Build a roadmap that aligns with your strategic goals

I am often amazed that companies I have engaged with in the past have a robust strategy for the future full of strategic goals and initiatives but when it comes to data, they just have a business intelligence or reporting environment that generates reports and “dashboards” from their own little island. Your data practices require a seat at the adults table so that the insights you get, align with and support your strategic goals. Chief Data Officer or not, be sure to include your data executive in those important executive meetings where decisions are made.

  • Don’t believe everything you read or hear

It’s hard to believe that as far as we have come in the information age, we still drink the Kool-Aid when it comes to the unknown. When confronted with the chaos and complexity perceived when we hear about Amazon, Chase and Netflix using data to predict your every move, we get nervous and grab at anything floating nearby to stay alive. Does Amazon or Netflix still recommend things you have no interest in? Yeah, me too and armed with that knowledge, I am not yet worried that they will soon predict my next thought and take control of me.

So what’s the moral of the story angry data guy? Well, I guess it’s to simply take a breather and strategize rather than react. Don’t let someone else tell you where you are in your data journey, assess the situation and you tell them! Don’t have a data platform company create your data roadmap, you do that based on the goals you already have. And finally, don’t believe everything you read or hear and always question the motives and source of information about subjects that are new to you. It’s likely that whomever shared the info, has something to benefit from by sharing it.

Stay curious data-day!

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