Though Master Data is core to the business and business systems of most companies, many are reluctant to interrupt existing processes to fix what they perceive may not be broken. Underlying this thought is that there is not sufficient savings to clean up bad data. That is rarely the case and below we provide a pair of business cases that can prove our point within your own company.
CASE 1: Eliminating Duplicate Spares
As part of any construction project for a plant—chemical plant, refinery, or manufacturing facility—the engineers who design the facility and specify the equipment require “Operating Spares” be in place to support 2 years of operations. These spares are generally expensive parts or components with long delivery lead times and are always part of the critical path for a process. They are required by contract, but not generally on a 1-to-1 match with the plant components. That means that if you have 4 generators in your system, the plant engineering/construction company will specify that you purchase 4 spare generators. It is in their best interest for you to buy them because they make money on them. But it is in your best interest to determine how many spares are actually needed given the standardization of some core plant components. By building out your Master Data while the plant is being built (and before commissioning) you can avoid spending money on excess spares. If you have more than one plant in nearby proximity, the savings can be more substantial.
One of our clients operates several petrochemical plants with common spares. Because they chose to build out their Master Data during a plant upgrade, they were able to cut their spares inventory by 53%, saving over $96 million on maintenance spares alone.
CASE 2: Eliminating Free-Text Spend
A key focus of most Procurement Departments is Strategic Sourcing. This requires either that materials purchased use an item master record or that their descriptions are specific enough to determine the exact item required. This allows Procurement to negotiate with several suppliers for the best price and put the purchase of those items on contract. As a general rule-of-thumb, companies can save 15% on contract spend vs. non-contract spend.
Unfortunately, when requisitioners and others request items using free text, maverick spending and inaccurate fulfillment often occurs. By utilizing a tool such as the Structured Text Generator to create purchase descriptions, commodity codes can be tracked and structured text purchases can often be tied to a specific manufacturer part number. For a company with a total spend of $500 million, 30% of that spend can usually be attributed to free-text spend ($150 million.) By eliminating the free-text spend and converting those items to contract-based purchases, companies can save over $20 million (15% of the $150 million.)
The process doesn’t even take into account how much more accurate searches for product can be with the Structured Text Generator. This saves time and often identifies existing contracts for materials previously purchased using free-text.
If you have excessive buying, maverick spending, or unplanned maintenance, it may be related directly to your unstructured and dirty Master Data. Contact PiLog today, and let us help you build your business case for improved profitability.