Most C-level executives I've met aspire for their organization to be data-driven, but when probed on what exactly do they mean by "being data-driven," their answers fall short of their vision.
Caught in the web of flawed information, these well-meaning decision-makers end up spending millions of dollars on solutions, talents and transformations that do not help them even move an inch closer to their goals - which apparently are not as well-defined as it should be.
While we all know "why" we should be data-driven, little do we know HOW. And more importantly, we're not even sure whether what we're doing truly makes us data-driven or not.
While I'm no C-level executive, I'm someone who's worked across a wide array of industries and I see the same pattern repeated over and over again. A CIO, an IT Head, a Data Director all trying hard to be data-driven but are actually aiming in the dark. Now while this may be a controversial take, I firmly believe that every great ambition starts by taking small steps.
I've compiled a small list of ten pointers that I often use to help individuals in "data-driven" projects to identify if what they are doing truly makes them data-driven or not. Feel free to add to this list!
1. Does Your Organization Even Know its Data & Data-Related Issues?
For many organizations, data is an IT problem {(I've written about this extensively. You can read it in detail after you're done with this post ;)}. This means business leaders don't even know their data. They have no idea that their data may be plagued with problems like:
- Duplicated records
- Incorrect entries
- Invalid data
- Issues caused by deliberate human input or human-error
- Different versions of the same data stored in different data sources
- Entities with incorrect SSNs, outdated or irrelevant information
Yea, so unless your organization's leaders are aware of the "quality" of their data, there's no way your organization can be data-driven.
The very requisite to being data-driven is to have clean data.
2. So Do You Have Data You Can Trust?
Let's use a case study here:
The CIO of ABC Group, a large online retailer believes the organization is data-driven. After all, the organization just spent over a million dollar last year to implement a new CRM system with advanced insights and analytics. They also hired data analysts to derive meaning from data. Part of a product launch strategy, the company wanted to run a strategic campaign targeting specific customers. When data was pulled from the CRM, it turned out that most of the information was duplicated, addresses were incomplete and invalid and the data analysts hired were spending 80% of their time cleaning data manually. The campaign had to be delayed. Although the company did perform a data mapping during the migration phase, they neglected data quality issues, focusing only on the mapping of data elements.
This drives home the point, does your organization have data it can trust? Because if it doesn't, there's no point in using fancy systems or platforms.
3. Do You Have a Team That Shares the Same Vision?
In my personal experience, employees are often afraid of change. The shift to a new system, a new platform, a new mindset is often met with resistance. While the organization leader may believe in making data-driven decisions, team members may believe in making experience-relevant decisions... you know the, 'we've always done it this way,' argument settles in and ain't no one argues with a method that was tried and tested.
Being data-driven is not an organizational process - it's a mindset, a mindset that understands, appreciates and believes in the power of data.
Unless your organization has the right people, the right experts and the right mindset, being data-driven is just another shallow buzzword.
4. Has Well-Defined Processes & Efficient Operations
Simple logic applies here - if your company is chaotic, there's no way you can be data-driven.
Seriously, companies with processes all over the place, with a poor culture, with political dominance, with an outdated mindset cannot and will not ever be data-driven.
The reason? Like I said above, being data-driven is a mindset. So let's say a data analyst highlights the problem with data quality and they are instead asked to, 'just fix it,' or they are not given the approval to use a necessary data preparation tool because it's, 'not in this year's budget,' can make it challenging to be data-driven. I've say way too many companies with poor culture failing their transformation plans and it's not pleasant.
5. Opting for the Hard Way than the Easy Way
I can't count the number of times clients I've spoken to decide to build a solution in-house for which they have ZERO expertise, only to end up wasting time, money and effort.
It's almost comical, but it's also tragic to see a company sleepwalking into a disaster. Just because a company has a software team doesn't mean they can build a CRM, an ERP, or a data management tool in-house. This s**t takes time! Did you know merely creating, testing and finalizing an algorithm for data cleaning takes at the least six months?!
This knee-jerk reaction to building in-house vs buying automated solutions is what causes many companies to delay on their transformation plans. It's only after they spend millions of dollars do they realize that an automated solution at half the price could have got the job done at much better precision, without affecting their goals.
In an age of data consumption, it's only natural for companies to aspire to be data-driven, but to really be data-driven, companies will have to go through a shift. Cultures, dynamics, mindset, goals will need be redefined because being data-driven is about being conscious of the power of data. It's like you're holding a crystal ball of information - what you do with that will define your organization's success.
So! Is your organization truly data-driven? Would love to know.