Aiming With Analytics

For years I’ve struggled to get across the concept and value of a data supply chain because I am often faced with explaining to executives why they need to spend money on their data quality (their raw materials) before they start applying AI models (their finished goods) to their operations.

Then, one day recently, I thought of Robin Hood.  And no, that’s not to say that I am suggesting robbing from the rich and giving to the poor.  It has more to do with Robin Hood’s weapon of choice – the bow and arrow.

The arrow

An arrow is a perfect analogy for the data supply chain.  But you first must buy into the fact that not one piece of an arrow by itself will hit a target.

For example, you can’t throw an arrowhead at a target with any great possibility of hitting it.  That goes for any other part of the arrow as well.

Try hitting a target with only the fletching (the feathers at the end) or the shaft (the stick that connects the feathers to the arrow head.)  My guess is that you won’t be successful, and you will frustrate yourself in the attempt.

So, if you look at the anatomy of an arrow and compare it to the data supply chain, here’s what you get. There are basically four parts to an arrow:  the head, the shaft, the fletching and the nock.  Each can be compared to some part of the data supply chain.  Let’s start with the arrow head.

  1. The arrow head

The arrow head is, according to Wikipedia, a tip, usually sharpened, added to an arrow to make it deadlier or to fulfill some special purpose.” 

In the world of data analytics, this is a good definition of an algorithmic model that can help “fulfill some special purpose” within your organization.  Most companies today are figuring out how to use their data-driven statistical models to help predict their revenue, identify which customers will buy, monitor their operations or create bots that manage parts of their software applications.

There are even Chief Analytics Officers (CAO) in companies where these models and algorithms are deemed essential to the business.  Like arrowheads, these analytical models are artifacts of a corporate culture that understands that decisions should be based on facts.

But the arrow head cannot hit a target if it is not supported by the rest of the arrow.  The part that connects the arrow head to the feathers is the shaft.

2. The shaft of the arrow 

The shaft of an arrow is the long, straight, stiff stick of hard and soft wood that transports the arrowhead to its target.

In our comparison to the data supply chain, I like to think of the shaft as the business intelligence (BI) or reporting capability that a company has. This part of the data supply chain helps to organize data, provides some intermediary insights and gives management metrics by which to run the business.

Most companies today have a reporting capability.  Often reports are generated by individual applications or by combining data from across applications.

Either way, the result is usually a report delivered either real-time or on a regular schedule to managers who make decisions from the data provided.

Without these reports, managers would have to delve into raw data to get every fact they need.  Just as the shaft carries the arrow head, reporting gives the analytical model builders a glimpse at where models can best be applied.

3. The fletching or feathers

And finally, the data itself is represented by the fletching or feathers at the end of the arrow’s shaft.   A fletching is usually formed from two feathers knit together.

The front fletching is camouflaged and the rear one is bright so that the archer can see where the arrow is headed. The fletching is the stabilizer for the arrow. Without it, the arrow would not fly straight and would never hit the mark.

From a data perspective, a data warehouse or a data lake acts as the fletching within the company.

The data generated by applications, gathered by marketers or created by operations teams is collected and made available to the reporting teams. Just as with an arrow, the quality of the fletching or the data is of utmost importance when trying to ensure accuracy in reporting or analytics.

Just as the fletching knits more than one feather together, data warehouses connect data from different systems and provide new views of information.

4. The nock at the end of the arrow

Now, an arrow does not launch itself.  It must be inserted into a bow and launched toward its target by well trained archers.  The part of the arrow that the archers use the most is the nock at the end of the arrow.

This notch serves to connect the arrow to the bow and launch the arrow toward the target.

In the world of data, this “nock” is the capability, either in IT or the business units like Finance, that links information to the rest of the company.  In some corporations, this nock is the chief data office that serves as the liaison to the rest of the company.

The takeaway

Archers — or small business owners — who want to hit their targets would benefit from understanding that each of these parts of an arrow are aligned toward one goal – helping the arrow hit the target.

The Robin Hoods are the business leaders or the archers within a company; they are the ones that need to hit a target. They know that the supply chain for information starts with data that supports a view of information through BI reporting and makes it possible for analysts to create algorithms that will predict and guide company growth and profitability.

For all the would-be Robin Hoods, the best archers in a company, remember that information arrows are your best weapons in the fight for revenue, market share and productivity.  Talley-ho!

#datasupplychain  #datagovernance  #data #dataquality  #CDO  #CAO

Theresa Kushner
Theresa Kushner
Theresa Kushner is a self-styled data-vangelist who brings her passion for all things data into her consultancy. Having held positions in F100 companies for most of her career, she now dedicates her time to helping start-ups and small/medium businesses scale using their customer information. She applies the skills she acquired as an executive at Dell EMC, VMware, Cisco Systems and IBM to help leaders apply data governance and 21st century data management techniques to their business intelligence and advanced analytics programs. She helps companies determine whether they are ready to take advantage of advanced techniques such as artificial intelligence, machine learning and robotic process engineering. She also helps guide companies in using more effectively for customer experience the data they collect on a daily basis. Ms. Kushner co-authored “Managing Your Business Data from Chaos to Confidence” with Maria Villar in 2009 and 2015 collaborated with Ruth P Stevens on “B2B Data-Driven Marketing: Sources, Uses, Results.” Ms. Kushner is a graduate of the University of North Texas where she received a Master of Arts in Journalism. She serves on the Advisory Boards of UNT Mayborn School of Journalism as well as data.world.

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