Calculating Return On Investment For A Materials Data Cleansing Project
In general, most business cases for data cleansing are built upon the justification that quality data will deliver significant cost reduction and cost avoidance through the following improvements:

Efficient Part Search Ability
Maintenance Time Savings
Accurate Reporting Capabilities
Identification and Elimination of Duplicate Items
Reduction of Excess and Non-Moving Inventory
Reduction of Equipment Downtime
Reduction of Maverick Purchases
Reduction of Expedited Part Orders
OEM to MRO Conversion Opportunities
Maximum ERP/EAM Functionality
While all of these benefits are realistic and attainable, the question still remains, how do they translate into hard dollar cost savings and return on investment for the company? The key is to define the direct correlation between data quality and return on investment as it relates to operation costs and production capacity. After all, the main objective for any company is to improve the bottom line, which means operating at the lowest cost, while maximizing production capacity. Although the maintenance department may appear to reap most of the immediate benefits, data cleansing provides many long-term benefits that span far beyond just one department. Master data plays a much larger role in the organization, even for those who do not have a hands-on relationship with it. For instance, clean, consistent materials data that directly improves part search ability will result in maintenance time savings and improved efficiency when performing predictive or catastrophic maintenance. Subsequently, maintenance time savings and improved efficiency will equate to downtime reduction, therefore, increasing production output capacity. Now that’s the kind of return on investment that Finance is looking for.
Based on twenty-five years of experience and project success, the following industry standards have been identified and can be used to perform a conservative return on investment calculation for data cleansing.
On average duplication ranges from 10-20% within an uncleansed item master
Approximately 25% of the duplicate value is eligible for inventory reduction
Approximately 60% of Annual Purchases qualify for spend leverage opportunities
On average 5% purchase price reduction can be captured through spend leverage opportunities
On average maintenance personnel will save 0.5 hour per day
On average 30% of the item master represents OEM items
Approximately 10% of OEM items can be interchanged to a standard MRO
Approximately 25% purchase price savings can be captured on OEM to MRO conversions
On average excess-active items represent up to 20% of the total MRO inventory value
In addition, you will also require several company specific input values to complete the ROI calculation. Those values include:
Total Number of SKUs (Items)
Total Annual Part Purchases
Total On Hand Inventory Value
Number of Maintenance Personnel
Maintenance Hourly Burden Rate
Once you have obtained all required information, you or your service provider can proceed to perform an ROI calculation to clearly illustrate the immediate and future benefits of data cleansing.
While the price of Data Cleansing services may seem quite high at first glance, the immediate and long-term cost savings opportunities greatly outweigh the initial investment. In most cases, Data Cleansing projects will pay for themselves within 3-6 months from project completion. Once all of the low hanging fruit has been harvested through the data cleansing initiative, the objective becomes maintaining ongoing data integrity and providing sustainable benefits through ongoing cost savings initiatives, such as inventory optimization. Neglecting to implement a catalogue management strategy will result in a corrupt data relapse, which means all of that money you just spent on data cleansing will have been for nothing.
For more information on Data Cleansing or to request a detailed ROI Calculation, visit www.imaltd.com or contact info@imaltd.com.