July 22, 2021 | Datavana
Ep27: Scott Taylor, The Data Whisperer and Principal Consultant at MetaMeta Consulting
Scott is the Data Whisperer. Scott has worked for almost 30 years in the data management space to try and “calm data down.” In this episode of our Datavana podcast, Scott Taylor (Principal Data Consultant at MetaMeta Consulting) chats with host John Kosturos about all things data maintenance. From purchasing data orchestration tools, to beginner steps for quality improvement, to why quality is important for storytelling. "Data quality is not the destination. It's an enabler of other things."
To avoid data disasters, quality and internal standards are required to formulate valuable insights to point your business in the right direction. "I’ve spoken to every kind of company and every type of industry all over the planet, everybody's got all these same kinds of problems."
Scott also talks about the importance of being able to effectively communicate the data problems of the business to the higher-ups through data storytelling. "I've never met a CEO or a business leader who feels that data quality is the number one initiative or top five initiatives."
Every Company Has Data Challenges.
"I'm fortunate in my career to talk to, and have spoken to, every kind of company and every type of industry all over the planet. Everybody's got all these same kinds of problems in terms of disparate systems that support disparate departments. They've got data that lacks internal standards. They don't have any kind of common definition and they're all struggling to try and get the value of that stuff pointed in the right direction to serve their business. Individual anecdotes come up with hierarchy problems, duplicates - a third of their files are duplicates. So they're trying to do some kind of customer churn analysis and they realize they're sending incentives to somebody who is already a big customer and doing fine because they've got to duplicate. Or categorization that doesn't make sense. People who've got a category structure, they run a report and they find out their biggest growing category is called ‘Other’. I mean really simple, basic stuff that people run into all the time, but I've just been overloaded and exposed to all these kinds of data horror stories that people have and trying to help them kind of get through it, get the funding, get the support to make things better."
Three Ways to Increase Brand Value.
"Every business wants to get bigger and more efficient, and provide more value. Now, when we talk about relationships; customer, vendor, partner, prospect, citizen, patient, etc. The terminology for those relationships should, and could be, very specific to the vertical that company is in. And the brand. What I mean by brand is every company has got a brand that could exhibit itself as a product, a service, an offering, a banner, or as a location. Again, the domain and the characterization of it is very particular to that business. When you think about bringing value there are only three ways to do that; grow the business, improve the business, protect the business. Great data can actually help you do all three at the same time and generally with the same data."
Why New Tools Mean Diddly-squat Without Data Quality.
"No matter what's new, you're still gonna need day to day data management. No matter what analytics graph, hub fabric mesh, or hybrid cloud the latest supplier is coming out with - without data, it doesn't work. It doesn't bring value. The content still has to be mastered expertly, stewarded, governed, supported, and owned. Otherwise those things don't work. Everything demos beautifully because the data and the demo is perfect. When you turn it on yourself, this stuff doesn't work. People on the business side get distracted by whatever that shiny new cool sounding thing is. And I think one of the biggest problems in the data space is this constant desire to come up with the newest, greatest, latest thing. That thing still needs good data. No matter where we were, no matter where we're going, you're still going to need great data to get you there."
You Can Handle The Data Truth.
"I believe you've got to determine that truth in data. I think about truth and meaning not like a philosophical personal development sense, but in a business sense. You can determine the truth. You can find the truth. You can handle the truth, but you’ve got to get the truth first before you derive any meaning. Which is where analytics comes in and data science, and it's not chicken or egg here. It is egg Omelette. You got to get that truth first before you spend any time on the meaning of any consequence. It's critically important that people really understand that and can communicate it to the folks that you know, you and I serve."
Always Invest In Data Quality.
"The people who have pitched the CRM implementation already have an ROI. They've already done the business case. But you can very confidently say those numbers that you put up are at risk if you haven't invested in the data. Because the system will simply not work the way you want it to. And when people open up that beautiful new software and they start to look at things that they don't believe, or they know are wrong. Then they’re not going to trust your system because it's the system they saw it in. Business people don't have time to figure out all these little nuances. And if you point out, ‘Well, it's not the software; it's the data. Well, it's not the data; It's the data management. Well, it's not the analytics; It's the methodology.’ All I'm hearing is excuses! You didn't do the work you needed to do to make sure the whole package was going to serve your business. It's got to be in there and people need to understand it."
Day To Day Data Management.
"What I see as more of a thematic throughout, given the experience I've had over decades is; no matter what's new, you're still gonna need day to day data management. No matter what, an analytics graph, hub fabric mesh, or the new hybrid cloud. Whatever that happens to be, without data it doesn't work. It doesn't bring the value. The content has still got to be well mastered expertly, stewarded, governed, supported, owned. Otherwise those things don't work. Everything demos beautifully because the data and the demos perfect. When you turn it on yourself, this stuff doesn't work just because you bought a new frying pan doesn't mean you're eating well tonight, unless you know how to cook and you've got the right ingredients."
- Why Data Quality is Important for Story Telling. Data quality is not the destination, but the path to guide the journey. Scott focuses on this narrative in his Book 'Telling Your Data Story: Data Storytelling For Data Management'. According to Scott, not enough business leaders are focused on data integrity. He encourages all striving for better data quality to focus on communicating stories to help find support and achieve goals. "You’ve got to get in and get attention for this. You've got to do it by putting together a narrative that makes sense to the business. So start your data story with things that the business cares about. Don't start your data story with, 'Our quality sucks!' or, 'Data is the new oil.', or, 'There's so much data.' Big data starts with the essence of your business; what’s the purpose of your business? The purpose of every business I've ever engaged with is to deliver value to their relationships through their brands."
- How Focusing on the 'Why' Can Help. Getting funding is always a tricky area, especially when you're in a separate department solving separate problems. Data is inherently an expansive topic, so it’s important to have a strategy in place to effectively communicate any and all problems. According to Scott, starting with the 'Why' is a great way to make your situation relatable to the decision makers. "Focus on the why! I don't know a lot of business folks who are interested in funding how you're going to do something until they understand, appreciate and recognize the 'why'. 'Why is this going to help me?' And I truly believe as you do that, every big initiative and a lot of small ones that organizations are trying to commit to have great data as part of it."
- The Beginners Checklist-Guide to Healthier Data. "If you've got duplicates; do you have a unique identifier? If things aren't rolling up right; do you have a good account hierarchy? If you can't do segmentation; are your categories all messed up? You need parent-child hierarchies, you need taxonomies for categorization." According to Scott, if somebody wants to get great data, there’s a direct process one can follow to begin the path to better data hygiene. "If you're not directing stuff in the right way and have the right understanding of market penetration; have you figured out the geographies? I'm backing into what I called the four C's; Code, Company, Category Country. You need unique identifiers. If you knew where everything was, if you knew who owned it, if you knew what kind of thing it was, and you knew what's unique, a lot of data problems would go away."
- What To Look For When Looking To Invest In Data. Scott says that if companies really want to tackle their data issues then they need to invest properly - it will cost you a bit of coin. Companies need to take serious consideration and care in their purchasing decisions. Developing a new frame of mind about system capabilities and objectives. Understand that any investment is likely to be long-term and high quality data maintenance is a must for ensuring new tools function at 100%. "It's a systemic long-term new way of life. And as you suggested, tie it to those other investments. So if your company is spending X million on a new CRM platform, you better make sure you're investing whatever percentage of that in the content that goes in there. The people who have pitched the CRM implementation already have an ROI. If you haven't invested in the data, they're at hard risk because the system will simply not work the way you want it to."