Larry Odebrecht published this article first on LinkedIn here.

I recently reviewed an article in the most recent Harvard Business Review (HBR) July / August 2022 edition that tapped into something super central to my recent career experiences doing Digital Data Transformations. For the past few years, I’ve observed two approaches to this work:

  1. I’m going to call this the “full press leadership approach”. In this version, leadership fully grasps that they are way behind and they reach out to the smart technology folks who do a full analysis with the intent of understanding every corner of the data and all the needs… typically spending years pulling together a comprehensive Entity Relationship Diagram (or a close cousin) of one and diving into every major use case. As time moves on so does the political will and the effort turns to drudgery. In a newer spin, the firm creates a Data Lake to speed the process but because they don’t have strong data governance practices it dissolves into a data swamp (further exasperating the lack of political will).
  2. The second approach is tied much closer to user stories and it moves more from the ground up. It’s arguably a healthier way to approach things because it’s much more tied to business value, but it also fails due to a lack of central orchestration of the data and you either need a plumber to fix the spaghetti bowl of data pipelines you’ve created or you need someone to drain out the swampiness you’ve created in the process.

Both of these paths (in addition to the obvious leadership challenge) also create something that we don’t talk about nearly enough: Data Debt. Data Debt is analogous to Tech Debt in that we know we’re going to have to spend blood and treasure to drain out the challenges, unwind the pipes, and create a brighter future.

Here’s my conundrum: if the leadership-led effort fails and the grassroots effort fails… what’s left?

Enter the role of Data as a Product

Disclaimer: I have always hated that phrase. It sounds like you’re trying to make the case that data can be monetized (it can) by simply slapping the label on it and not doing the practical and pragmatic work of putting together a business case that leadership can look at and poke holes in. This isn’t that.

What we’re talking about is actually organized as a product team with the focus and dedication that a product team would have. Leveraging Agile the right way to make sure that the backlog is well groomed and that the Product Manager and the Executive Sponsor are tied out with a very crisp understanding of priorities (an even closer tie to business value than the grassroots).

In our work we’ve seen that companies that treat data like a product can reduce the time it takes to implement it in new use cases by as much as 90%, decrease their total ownership (technology, development, and maintenance) costs by up to 30%, and reduce their risk and data governance burden.

So, that leaves another central question open: what is the product? That’s where this HBR article really played to what our team is seeing in the marketplace. What we normally see is a spaghetti bowl of data sets that are very tied to a specific use case and then varied supportive technology that ties that data set to the business use. That kind of approach means that there’s someone (probably many someones) who have to live in that and manage it – limiting if not eliminating the ability to strategically direct data.

Data Products bridge that middle better. I have recent experience working for a health technology company that was really struggling to understand their customer experience both from a Customer Centricity perspective (what is it like to work with our company?) and a Product perspective (are our company’s products returning value?). The correct solution is a Customer Data Product but the client struggled to get here because the upstream source of the data and the way the data was being consumed kept muddying the stark reality that the product being consumed was customer data. 

I’m seeing many of our clients wrestle with the same thing. I’ve seen it in large health systems, in the wholesaler market, and we’ve seen it in the adult beverage industry: focusing on what those core Data Products are as a way to understand the format that upstream data should be in and (more importantly) the way your customers will consume the Data Product is the key to making progress.  

Source: Harvard Business Review (July / August edition 2022). “A Better Way to Put Your Data to Work” by Veeral Desai, Tim Fountaine, and Kayvaun Rowshankish.

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