The Tale of The Six Data Islands
This is a repeating story we have internally nicknamed “The Six Data Islands” Challenge.
Our client, similar to others we have worked with, was a mid-size make-to-order manufacturer of housing construction material. Over the years, they had purchased and installed six different on-prem software systems: CRM, Manufacturing Resource Planning (MRP), Accounting, Revenue Booking, Service Management, and Outlook Calendar. The CRM was primarily used by the sales and management team for customer intake, however the customer and project-centric view was not carried over to the MRP because Order Processing was splitting projects into disjointed production sub-orders. The accounting department, on the other hand, took these sub-orders as the main order of record and used them to record financial information about deposits and payments. Once sub-orders came out of the manufacturing assembly line, they were placed on a common Outlook Calendar to be shipped. None of these systems talked to each other automatically which was the source of major headaches. Some examples were:
The company paid a talented and capable full-time analyst an annual salary to chase project data in these systems, stressing to reconcile sub-orders and other disjointed information about the full project. Any question where the answer required looking information up in more than one of these systems was a challenge. For example the simple question of “how many dollars worth of finished product did we ship to customers this month?”. Needless to say, she didn’t have any time for any actual analysis and forecasting.
The CEO needed to have a clear picture of next quarter and next year, the president needed a current and next month view and the CFO needed to see the impact of any single event on cash-flow projections and revenue forecasts. They had the data, but could not get the views they needed from these disjointed systems.
Management could not streamline their business processes because there was no way of knowing how shipments, deliveries and revenue would be impacted by any changes to the production schedule due to other rush orders and material backorders, etc. So they just continued as they had done before.
How we helped
We started by listening to the people who used these systems everyday and learned how the systems were really being used. We found several repetitive time sinking tasks and heard about some of the disaster scenarios that had actually happened in the past: messed up orders, customers lost, interpersonal frictions that lead to major conflicts, …
We also listened to the management about what they needed. What were the manually-made reports they routinely used? What were the types of reports and views they never got?
Having spent a great amount of one-on-one time with different folks within the factory, we got busy building. We created an architecture for data collection and warehousing and installed the infrastructure within the factory. Within 2 months, we created and installed data management software that connected each of the six different systems (The Islands!), reading from their systems and writing the data into one central data warehouse. Our solution contained automated constraints and exception reports that work to prevent conflicting data entered into any of the systems from becoming reconciled with the data in any of the other systems. These automated constraints and exceptions reports also alert management and system administrators in the event of conflicting data so it can be remedied early and at source. The software was created with the end user in mind; an appealing and modern web interface allows management to easily view data in-real time.
Working closely alongside our client, we implemented a software that was optimal for their particular use. Our software removed additional strain on the organization by resolving issues that stemmed from having disjointed data islands, such as late orders, customer loss and interpersonal frictions. Our purpose-made data collection and warehousing architecture centralizes data and streamlines data-driven decision-making. In a sense, it lets a company navigate among each of the six data islands.
