Our Data Sucks!…Can you help us fix it?…Do we need a PIM?
October 16, 2018
Data Takes a Front Row Seat for the World Series
October 23, 2018

Tales From 2 User Conferences

Chad Cosper, VP, Corporate Development at Amplifi

Over the last month, we have had the opportunity to visit with partners, competitors, and hundreds of customers and prospects at 2 different user conferences sponsored by our friends at EnterWorks’ (Engage18) and StiboSystems’ (Connect18).

Now that we are back in the swing of our “normal” work days, I wanted to take a few minutes to reflect on the things we learned and shared during these valuable experiences. (Also, check out our CEO’s reflections on the progression of the industry posted while we were in San Diego for Connect18.)

What We Learned

Not surprisingly, the biggest takeaway from both experiences is that the need to manage data in a way that can make it actionable is still very much top of mind. I say “not surprisingly” because I have worked in the Data Management field for more than 12 years. In that time, I have seen enterprise organizations embrace the need to:

  • Integrate data from disparate systems into a single location for governance
  • Standardize and de-duplicate data
  • Improve and enhance the quality of customer and product data, alike, for use in data analytics
  • Add additional domains of master data beyond customer and product, specifically, supplier and location, etc.
  • Introduce data governance teams and processes to ensure that enterprise data is consistent in all consuming systems

What we learned in these latest conversations with companies undertaking MDM and PIM projects is that, in addition to continuing the priorities previously described (some delayed, some stalled, some simply just getting started), most, no matter what stage they are in, are looking to tie master data projects to quantifiable business results. Instead of the more traditional conversations, we talked with customers and prospects, alike, about business-driven goals such as:

  • Eliminating departmental silos and replacing them with an enterprise-wide system of record for all master data
  • Ensuring that location-specific data can be translated and localized from a single system
  • Associating all supplier records and inventories to specific delivery locations to streamline ordering and ensure specific stores have the required inventory
  • Creating rich product records that include access to accurate product descriptions as well as photos, videos, and other high-value unstructured product content

While we did meet a few participants who continue to struggle with how to sell an MDM vision to the C-Suite and talked to a lot of companies struggling with the ideal way to architect the best data model for their particular environment, the biggest takeaway for me was how far the market has progressed in terms of maturity.  No longer are we having conversations about what MDM is and how it works, rather, we are now talking about what MDM can help you achieve – and that is HUGE.

What We Shared

As I mentioned, we got to listen to and share our thoughts and experiences with lots of customers, prospects, practitioners of MDM, and just, plain, data geeks like us.  But, audiences at both conferences also got to hear a bit about our unique perspective on data and the business outcomes that data management can provide.

Our VP of Delivery Services, John Phan, delivered a keynote speech at Engage18 entitled “Enabling the Data Value Chain,” during which he introduced the concept of the Data Value Chain, which he defined as “the process through which raw data is transformed into tangible business value.”

John Phan Delivering a Keynote at Engage18

  • Data
    • Raw data – spreadsheets and databases full of raw data points that are not meaningful to our human eyes. We are not looking at rows and columns of numbers and text strings and immediately understanding what it is we’re really looking at.
  • Information
    • This is data that has been organized and is understandable and accessible to us. We may not know immediately what the useful parts of the information are, but we could sit down and understand what we’re looking at.
  • Insight
    • Once data has been organized into digestible information, data scientists analyze and pull from information sets actionable insights – conclusions from which operational decisions can be made.
  • Action
    • One of the most fundamental lessons about the data value chain is that without action, you do not derive value from your data. Your data may still BE valuable, but without using your data, none of that value will be realized. Just like with money, when you’re a teenager storing money in a piggy bank, you’re not realizing any value from it. It’s not earning interest, and until you put it to use – it sits there, actually becoming less valuable due to inflation and the time value of money. Your data, too, becomes less valuable the longer it is unused. So once you’ve stored, organized, and analyzed your data, you must take action.
  • Value
    • Once you have taken action, you will begin to derive real value from your DVC. The value may be immediately tangible, such as increased revenue or decreased operational costs. The value may be less immediately tangible, such as increased employee satisfaction, which will, in turn, allow you to attract and retain the most talented employees, ultimately driving your business toward long-term success.

Data Value Chains exist in EVERY part of the Information Lifecycle, and data is perishable, so the more time it takes you to get the data you need for your use case, the less valuable that data is. And, it is important to think differently about your data in order to recognize the data value chains that exist in your organization because when you fully enable your data value chain and reach the strategic stage of data management maturity, the sky is the limit. You start freeing up your human capital to make strategic decisions.

Phan suggested that everyone do just that.  Flip their thinking about data – start with these questions:

  • What data value chains exist in your organization today?
  • Which data value chain is the most valuable?
  • What outcomes could you achieve if you enabled the correct data value chains?
  • Who are your top data experts?
  • How long does it take you to find the data you need?
  • Do you know where to go when you need data?
  • Are you using your data strategically?
  • Do you treat your data as an asset?

 

Ken Rundus of Dal-Tile at Connect18

At Connect18, Ken Rundus of Dal-Tile, the industry leader in manufacturing tile and stone, talked about how his enterprise chose to embrace PIM as the foundation of Digital Transformation efforts – and how Amplifi and Stibo Systems helped them generate some pretty amazing Return on Investment:

  • Eliminated 15 spreadsheets, producing a time savings of 142 hours per SKU
  • Reduced cycle time for new products by 6 weeks
  • Retired multiple legacy applications, eliminating future license and support costs
  • Consolidated product marketing to one source of truth
  • Increased the visibility of the status of each product in the development lifecycle.

We look forward to many more user conferences with our valued partners in the future – and hope to see you at one in the future.