The Value of Data Integration is Pretty Easy to Define
Part of what I like about being a consultant is that I get to work with different kinds of clients. For the most part, the first step is to define the value of applying some technology that will change the capabilities of both IT, as well as the organization as a whole.
It’s easy to see that most enterprises are heading toward hype-driven cloud computing, which includes IoT and Big Data. However, what’s systemic to any change is the need for better data integration, and that drives value that most enterprises never knew existed. Guess what? The value of data integration is very easy to define. Here’s how.
The value of data integration is really about understanding what it means to the business to have access to near perfect information. Case in point, a past client of mine was managing inventory based upon what occurred a year earlier. Seasonal buying patterns, customer behavior, and so forth, was predicted by history. It dictated their purchases for materials to create inventory, and this pattern had repeated itself for the last 20 years.
While this is a pretty common approach to predicting the future, it also means you’re pretty much always going to be wrong. In the case of my client, they consistently over-manufactured or under-manufactured. Thus, they wasted money by producing over demand, or lost sales due to lack of inventory availability at the time of demand.
Missing, as you may have guessed, was a data integration solution so that the core manufacturing management processes had access to key information to better align production with existing demand. Enter affordable data integration via cloud computing. While they could have leveraged predictive analytics to get them closer to the truth, it was cheaper to implement a just-in-time-inventory approach.
Using data integration technology, they were able to link right into supply chain systems that recorded orders from retailers. These orders were then seen by the manufacturing system in near real-time, and they scheduled production that included buying just the right amount of materials. In other words, they no longer rely on near perfect information about the demand for their product, and can manufacture as needed to directly meet the demand.
Putting the customer service value of this approach aside for now, this integrated approach has several points of obvious value, including the ability to remove most inventory costs from the process. Just in time inventory, if practiced correctly and with the proper data integration technologies in place, can align production directly with demand. This includes buying the right amount of materials, scheduling the right number of workers, and even providing customization capabilities that were previously unfeasible.
Place a dollar figure next to each of these items, and you’ll come up with the value of data integration. In this case, it saves this client $5,000,000 a month. In addition, the customer base and the market quickly saw the increased efficiency, and revenue increased $ .5 billion over the next year.
Of course, all companies are different, and thus will have different values assigned to the use of data integration technology. The point we’re making here is that the value is pretty easy to define for every enterprise. Perhaps it’s time to look around your business.