VALUE

Transcript: Hi! I'm Robert Sidick from First CDO Partners. Let's talk about a big question - how valuable is Data Governance? It's a topic close to my heart because creating and managing data governance processes is what we do at First CDO. People mostly agree that data governance has value because proper governance of your data assets leads to quality data. That's primarily why it's there. And we do that because quality data is valuable. So the question really is, how valuable is your data? Unfortunately that's not an easy answer. First off, unless you're in the business of buying and selling data, it doesn't just pop up on your balance sheet. Actually it's probably not allowed to be there. And on your income statement you will only find the costs of managing and cleaning data. It's no wonder most companies are underinvesting in their data because when they spend a million dollars to improve it, the only thing that's clear on those financials is that they spent a million dollars. Showing the value that investment created is the challenge. This means that at most of the companies I've been at, investments in data governance and data management feels like a leap of faith because the ROI is often soft the best. This makes securing budget and resources a constant battle even more so than in other areas and I came up in IT. Another challenge - data is intangible. It's like a company logo. Yeah you can see it, but what's it worth all by itself? You have to put effort into making it valuable. So why do companies hesitate to put their data to work? Often, it's because their data is of poor quality or in the wrong format or it's tough to combine with other data or countless other reasons. What could fix that? You guessed it - data governance and other data management activities. But we already covered why it's hard to get investment in that area - it's difficult to show the value. While there's no one perfect way to calculate data value, there are options depending on your use case. Let's look at one approach to value a data set - the income approach. They say that beauty is in the eye of the beholder and so is data value. For example, customer data is very valuable to sales and marketing, probably less valuable to customer service and operations, and might not be worth much at all to HR. But that's okay because one great thing about data is, unlike most resources, it can be used simultaneously and repeatedly. Take customer order history for example. Sales can use it to predict what and how much that customer may buy in the future, marketing may use that same data to adjust its next marketing campaign, and customer service may use that data to process a warranty claim. Each team can extract value from the same data. So let's see how each of those teams value that data. Perhaps sales showed that having better insights from the customer order data was responsible for about a million dollars of additional revenue from Acme Corp in the last quarter or last year or whatever. So to them that data is worth a million dollars while maybe the additional revenue that they received came from relationship building or sales skills and talent or even just organic growth in the sector. And then marketing reports about $500,000 of additional sales revenue that they generated was due to having the right data to create an improved marketing campaign for Acme Corp. So that's what that same data is worth to them. Then finally you get customer service. Maybe customer service shows that they improve their NPS score and feel that $250,000 of additional revenue from Acme Corp was due to their revised, hassle-free warranty claims processing because it boosted customer loyalty and it boosted ordering confidence. So this process was improved thanks to the availability of the customer order data. Now as you can see, each group valued the data a different amount. This same set of data was worth a million dollars to the sales team, half of that to the marketing team, and half of that to the customer service team. So then, what's this customer's order data worth to the business? If these groups were the only consumers of this data, then this data set returned $1.75 million. Now you can use historical information like this to justify or predict future data value and get the investment you need. Now this is obviously a simple example. I know that it usually looks more like this. So, you'll want to keep your evaluation methods as simple as you can but still defendable. Now I'm barely scratching the surface regarding the complexity and nuance in valuing data and data governance activities and this is just one of many evaluation options you have your disposal. Given those challenges, we may never be able to lock in on a valuation method that would ever become GAAP approved, let alone one size fits all. However, you know that the data is valuable and you absolutely should try to value it. If you don't, you'll continue to struggle to get budget and consistently underinvest in data management and therefore, leave your data less valuable than it should be. So identify the value you can. Accept that you won't identify all of its value and that's okay - don't let perfect be the enemy of good. What you do capture will be better than what you have today which is an intangible, unmeasured gut feeling that investing more in data govern govern and data quality would bring substantial returns and that is a lot harder to sell - ask me how I know. Thank you let's do this again sometime.