Using Master Data Management to Create Bottom Line Savings

Transcription

1 Using Master Data Management to Create Bottom Line Savings

2 LINKING MASTER DATA MANAGEMENT TO PROFITABILITY Master Data Management (MDM) is the discipline comprised of business standards, rules, policies, and methods enabling the integration of data from multiple sources to deliver consistent, current, and authoritative data across an enterprise. While companies place emphasis on MDM as being important for decisionmaking and organizational efficiency, they don t always see the direct link between MDM and profitability. MDM actually has a substantial impact on profitability. We recently saw this firsthand when we were brought in to help a customer struggling with inaccurate data. This example shows both the challenges and impact of poor data integrity. ILLUSTRATING THE FINANCIAL IMPACT OF INACCURATE DATA Our reference point is a make-to-order manufacturer of highly configured and complex products. With complex Bills of Material that include many layers, including phantoms - their world consists of constant engineering change and new product introductions. Operations are similarly complex with several feeder areas supporting multiple end-product production lines and an amalgam of make-to-order and make-to-stock sub-assemblies. Their process data however had been allowed to stagnate. Time studies hadn t been performed in years and the routing data was highly suspect. With almost 200,000 items and 300,000 routing steps, it would have been impossible to perform formal time studies across the board. As a result of not having reliable process data, the organization was unable to quantify which models were more profitable and which were less. Profitability by customer or by model then could not be included for either sales strategies or marketing plans. As a result, bottom line profitability sagged as the sales force worked to achieve revenue targets without reference to profitability. page 2

3 In addition to their fundamental profitability problem, they faced other challenges: Their enterprise systems were old, difficult to maintain, and very complex The amount of data to manage was massive Their resources to embark on this effort were extremely limited especially the manufacturing engineers responsible for the data DATA INACCURACY IS COMMON AND COSTLY Over time and in nearly every organization in which we ve worked, there has developed a fundamental disconnect between the organization s data and the real world experience of the shop floor. At some point, this disconnect comes glaringly into the spotlight. The response of organizations to the reality of poor data quality takes many forms. In some businesses, the information in their formal manufacturing systems bears so little resemblance to the real world of the shop floor that no attempt is made to bring them back into alignment. They typically resort to spreadsheets maintained in ad hoc fashion. Others recognize the importance of re-aligning the data in their formal business systems and embark on data clean-up efforts. While these are laudable efforts, formal business systems often do not maintain the granular detail needed for shop floor continuous improvement activities. So while there may be a clean up the routings push, very little useful data makes its way to the shop floor. For far too many organizations, the end result is that the high-level planning activities for Sales and Operations Planning, Master Production Scheduling or Material Requirements Planning are based on fundamentally flawed data. This information is then used in financial transactions, which creates additional variances that again must be analyzed and rationalized. So what s a company to do? page 3

4 THE FIRST STEP IS TO COME OUT OF DENIAL ABOUT POOR DATA QUALITY The first step the organization had to take was to commit to a decision that poor data quality was unacceptable and hampered achieving corporate goals. The next step was to search for tools to enable the data clean-up effort and to find a fresh approach to data clean-up that would not break the bank. CONSIDER ARETEIUM FOR MASTER DATA MANAGEMENT Areteium from mcaconnect is a proprietary software toolkit that organizations use to model their operations quantitatively. It supports product information including bills of material and items. It also manages process information on routings, labor times, changeovers, downtime, etc. and then integrates the process data with the product data. Areteium can be set up to support individual production lines, entire plants, or an entire extended supply chain all with a common set of enterprise product and process information. page 4

5 The following considerations made Areteium a strong candidate for an MDM solution. Areteium is provided by subscription and hosted in the cloud. No IT involvement is needed to begin to use Areteium. Areteium can be set up and ready for a new organization to use within hours. Areteium is intuitive, easy to use and can be learned quickly. Areteium supports a wide range of data imports using simple data formats of Excel or CSV files. Most legacy systems can easily export to this format. Data from multiple legacy systems can be imported into Areteium to harmonize between legacy systems. Data is managed simply with the most crucial elements only to avoid the complexities of hundreds of fields. Bills of materials layers can be collapsed or consolidated on a what-if basis without impacting other work. This allows multiple remediation efforts to operate concurrently. Areteium provides the flexibility to manage data at a high level if averages are sufficient or at a very low level of detail, deeper than in most ERP systems. Mass changes to data are easily managed using Excel to support high productivity in data clean-up. A full set of integrated data inquiries can show missing data or incomplete data quickly that can then be researched. Once data is resolved, Areteium can become the central repository for process information across all production across the enterprise. page 5

6 TAKE A FRESH APPROACH TO THE PROBLEM Sometimes it s the obvious solutions that remain hidden. With a highly experienced workforce, the operators already knew how they did their job, how long it took on average, and which individual products that gave them fits. Instead of stop-watches, why not just ask them? This new approach led to a series of highly focused walk-throughs of operations to solicit whatever knowledge operators could share. A few token time confirmations were done and the data was loaded to Areteium. The validation effort ensured that the times reported from the interviews were reasonable in line with historical expectations. From there, only bottleneck operations needed to have more detailed studies done. All along the way, Areteium became a maturing central repository for a growing collection of process data matched to product data. Everyone began using the new data which eventually was used to update legacy systems now synchronized with data that had been vetted by both Operations and Finance. CREATE AN MDM CENTRAL DATA REPOSITORY As disparate sources of information are inevitably drawn together from both formal and informal sources, it is obvious that a central data repository must be established. The requirements are that the repository will: Maintain all of the information needed to support production operations including product, process, demand, inventory, configuration and order information. Support the depth of data required at the shop floor to reflect real world complexity. Support the organization s planning and decision processes Manage data integrity and consistency throughout including appropriate editing and data management techniques page 6

7 FACING THE MDM CHALLENGE Every organization is challenged to manage the ever increasing amount of data so that business decision makers can be fully informed and their decisions fact-based. For too many organizations, MDM is perceived as optional, a nice to have element rather than critical. Forward thinking organizations however understand that a lack of data integrity compromises their efforts toward performance improvement and directly impacts their bottom line. page 7

8 ABOUT THE AUTHOR Phil Coy is Managing Director, Strategy Services of mcaconnect focusing on manufacturing excellence. Phil is a thought leader advocating the use of technology to enable lean manufacturing and sustainable operations. ABOUT ARETEIUM Areteium is a cloud-based software tool that creates a complete model of future state operations, providing quantifiable data supported by what-if analysis. This allows you to make valuable, data-driven decisions to improve lead time, reduce waste, and deliver greater profits. With Areteium, you can achieve the benefits of your manufacturing operations transformation significantly faster! Your executive team will have confidence that your plans will achieve the expected results. Request a FREE 30-Day Trial of Areteium by ing solutions@mcaconnect.com! ABOUT MCACONNECT mcaconnect is a Global Systems Integrator and Microsoft Dynamics Partner (AX & CRM) that delivers and supports operational transformation to help customers achieve competitive advantage. By combining product and industry expertise with proven strategic alignment methods, mcaconnect is able to consistently deliver innovative solutions that help clients realize their vision, as evidenced by our repeated recognition from Microsoft and the millions of dollars we ve helped customers add to their bottom line. In 2015, mcaconnect was named Microsoft Dynamics U.S. Manufacturing Partner of the Year, Microsoft Enterprise Resource Partner of the Year and was a finalist for the Microsoft Customer Relationship Management Partner of the Year. page 8