Clear data = simplified business process = huge cost savings

The Situation

A computer power supply manufacturing plant was experiencing unacceptable delays in planning, building, and shipping products to order every month. Inventory costs were high and rising.   It was also taking weeks to close the books for any given month.  Business margins were shrinking and the plant needed to drastically reduce costs, accomplish on-time production, and to view accurate business and financial metrics at any moment during the monthly cycle.

The Problem

The monthly manufacturing processes consisted of four sequential steps:  Business Planning, Pre-Production, Production and Post-production to close the books each month..  These processes took 10 weeks to execute, meaning that the plant manager didn’t have the financial results for any month until 6 weeks after-the-fact.  It was suspected that there were a lot of non-value added steps and effort embedded into the business system and that this was mirrored by the IT systems.  Data was not clearly understood at each handoff and there was little visibility into the business process.  Static paper reports were produced by IT at various points in the monthly process, but were typically also after-the-fact and not useful for making mid-course corrections in planning or production in order to meet business goals.

MV360 Solution

As part of the analysis we discovered that the data was being held hostage in the business and IT systems.  We examined the business processes from the perspective of the data and saw many redundant processes in the business system – one step would manipulate the data one way, and the next step would put it back to the way it had been before. Multiple business processes existed simply to check the validity of the prior process.   By creating an accurate data model in support of the business operation we drastically simplified the business processes, and the systems to support them.  Separating the data from the process allowed the introduction of streamlined business operations to acquire data once at the right time and to accurately relate production requirements to inventory.  Data was further separated from the process by creating a data warehouse for analytic reporting. As a result data fed the analytic warehouse on a nightly basis, allowing a daily view into key business metrics.

The Result

The plant experienced dramatic positive business results.  The information cycle time for planning to monthly reporting was reduced from 10 weeks to 1-2 days.  Deliveries went from 75% monthly to 100% related to demand pull.  Inventory lot sizes decreased from 50 to 3, greatly reducing the cost of inventory.  Material transactions per unit were reduced from 19 to 6.  Dramatic personnel cost savings resulted from adopting the new data-driven process.  Because of the disarray of the data in the prior systems, it spawned many process steps where basically the “checkers were checking the checkers”.  The plant was able to eliminate 65 Inspector and Work Coordinator positions because they were no longer needed.  Supervisory and Product Control positions were reduced by 30%.  The number of system users and user-controlled reporting increased tenfold, but required only half as many IT support staff.