First, Get A Handle On How Messy Your Data Is;
Then Use Tools and Processes to Clean It Up!
More than 25% of your critical data is flawed, inaccurate, incomplete or duplicated, according to a release issued by Gartner last month.
Perhaps more disconcerting than knowing a quarter of all critical information is wrong, is that the overall state of data quality has not improved in the last two years. Gardner reported the same stats two years ago and does not expect much improvement in the near future.
What steps can your company take to clean up one of your most important strategic assets?
1. Acknowledge the problem – the first step is admitting there is a problem. Data quality experts say every company (not just manufacturers) has bad information.
2. Determine the extent of the problem – There are data cleansing software tools that can monitor and count the number of files, omissions, duplications, etc. As a minimum, companies can use Microsoft Access as a way to query records and pinpoint duplicate records and omissions. Companies should also conduct accuracy assessments to test the validity of their business information.
3. Put a dollar figure on it – One company estimated that it would take $500K -$1M to improve their data and quality processes. That may seem like a lot of money but it is minimal when you consider the expense companies incur due to inaccurate business information, customer turnover, missed sales opportunities, poor planning and production distribution. Companies can lose 155% or more of their revenue due to problems stemming from bad business information.
4. Put someone in charge – Companies should create a management position focused on data quality; some call it a Chief Data Officer, others Chief Information Quality Officer. Regardless, this person should be responsible for measuring data accuracy, bringing in tools to keep it clean and most importantly, putting in processes to ensure that the data is correct and current at all times.
5. Understand and comply with industry data standards – Whether your company is serving wholesale or retail channels, data attributes have to be uniform and standardized to enable distributors and retail trading partners the ability to accept data from multiple suppliers and ensure a smooth and hopefully error free order management system. Standardized data structure serves as the foundation for the supply chain; without standards there would be chaos. Therefore, know, understand and implement industry data standards – it will make doing business with your trading partners that much easier.
6. Use available tools – companies should employ root cause analysis tools to find out the origin of their data flaws and to define process improvements. The best tactic is to pursue a master data management solution offered by product information management application companies like Full Tilt Solutions, SAP, Heiler and Thomas Tech.
Improving data quality requires a concerted effort that includes a combination of people, processes and technology. All three aspects must be brought to bear in order to achieve lasting positive results, and this applies to distributors and manufacturers alike.
Contact Beth Badrakhan at (703) 562-4602 to find out how to participate in the IDEA Data Audit and Certification Program, which provides specific error reports and feedback that will help you address process and problematic areas.