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.