The Four ‘C’s of Data for Executives

by Jim Cain

We’ve reached a tipping point in data.  Not only is everyone talking about it (my mum confidently quotes stats on the pandemic and talks about trending), it’s everywhere (I just read a book about a supervillain data scientist, advanced stats rule my hockey news feeds, and the level of analysis of data around the 2020 US Presidential election was unreal).

Ironically, this global embrace of data is creating major stress in businesses.  Despite over a decade of using phrases like ‘data-driven’, ‘big data’, ‘data science’ ad nauseum, there really hasn’t been as much progress on running with numbers as most businesses would like.

The pandemic has made this more significant for two reasons:

  • Many traditional senior executives were forced into massive work from home programs, which in general have been a combination of successful and disruptive.  This has made a very important audience of decision-makers start asking ‘What else could we be doing differently to automate and improve our business?’. Instead of being change blockers, COVID has created a large cohort of change drivers – and the pressure is on.
  • I’ve heard this from several people – “The pandemic is like a time machine that moved the world five years into the future.” Systems that were already under stress – think fast fashion and traditional retail in general – have been given no time to plan and pivot, and are suffering accordingly.  This is especially true around the admittedly cheesy consulting terms of ‘business transformation’ in general and ‘data-driven business’ specifically.  Many enterprises decided to procrastinate on properly embracing data, and are now under the gun to do a lot quickly.

Provided you are a business decision-maker who agrees with the points above, you are probably struggling a little with the right way to start thinking properly about how data needs to work in your business.  Way too often decisions are made (often with the active support of aggressive salespeople) about trying to ‘win at data’ by buying something.  Not only does this approach not work, it sets you back, costs you money, and most importantly costs you buy-in and support from your organization.

In over a decade of working with senior management in large enterprises who are having the same struggles, I’ve come up with a helpful framework that I call the four ‘C’s of data for executives.  The purpose of this framework is to allow leadership the ability to strategically think about data in their business, without having to become experts in all the new trends or minutiae of the underlying technologies (in fact it’s better in some cases if you don’t).

The four ‘C’s should be used as a construct for every conversation you have about data, as they constitute 100% of every data program you’ll be involved in.  Here they are.

The 4 C’s

1 Create Data:

Data needs to exist in order to be used. What data do we need, and how is it being created to feed this program? Is the data that has been created correct, clean, and governable?

2 Connect Data

If data exists, how am I going to properly get it to the place where it can be utilized? Connect is the first step of taking that raw, hopefully properly created data and starting to bring it together to be used by the business, again, ideally in a way that is repeatable, entrusted, and proper.

3 Control Data

If I’m spending money to create data, how can I store and control it so that I can use it again? Control is the act of taking data that you created and brought together and bringing it into a place where it’s owned and able to be controlled and leveraged as an asset by the business.

4 Commercialize Data

If I’m sitting on a large amount of quality data, what are the things I can use it for to move the business forward? Once you’ve got data created, connected, and controlled, how do we commercialize or leverage that data to generate positive effects on the business

Think of any data initiative you’ve been involved in recently and apply the four ‘C’s and you will see what I mean.

Let’s take something basic, like a new marketing campaign technology your company is investigating.  The salesperson from the adtech vendor tells you that their “next level programmatic retargeting solution will generate millions of dollars in new revenue for your business.  It only takes a few lines of javascript to deploy”.

For starters, this is TOTALLY a data initiative, as much as it is a marketing one.  The four Cs approach is a way to break every data initiative up, regardless of whether it’s marketing or not into the four most critical areas that need to be considered in order for it to be both successful and properly adopted and something that has a long tail impact on the business. Data-driven programs aren’t just for reporting and data science.

Secondly, this initiative really only has a plan to Capitalize on data.  We’re not sure if proper data is being created for this tool to use, we’re assuming that their javascript will provide a proper connection to their system, and we aren’t going to be controlling anything – all the data will be the property of the vendor, and the only reporting you can really use will be theirs.  I’m not implying that this program is a bad idea, but implementing it without considering the four ‘C’s will increase the likelihood of program failure and minimize the total value you can create.  Furthermore, if this program is enacted by marketing without liaising with  their colleagues in IT and Data Science, returns will be significantly less than possible.

You don’t need a math degree or ten years of software development experience, but a high impact decision-maker in the 2020s needs a really solid understanding of how data works to build programs that win.  The 4’C’s are a great foundation for getting started.

Jim Cain

Founder and CEO, Napkyn Analytics

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