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The ability to automate reliably and repeatedly depends on how accurately the data used is gathered and curated.
January 18, 2023
By: Erwin Busselot
We rely on data to inform client, vendor, and supplier relationships and much of the work produced in our print operations. Data comes in a host of formats, both visible and invisible. There is the data you gather to onboard a job, and there is data generated by an application to inform personalisation and customixation. There is the data in the back office systems and in the inventory, estimating, and production systems. Data is everywhere. Sometimes we forget that the accuracy of the data we use is not self-managing. It takes a data hygiene process to ensure data accuracy and avoid mistakes. Your ability to automate reliably and repeatedly depends on how accurately the data you use is gathered and curated. It may enter your process manually with a team member keying it into a screen based on information provided on paper, in an email, or through a conversation. The majority of all print jobs still arrive by email. It may also arrive in a feed from business applications, which may be passing data from other systems or generating the data. No matter how or where the data originates, setting up processes to regularly review inbound data sources, formats, and mapping between applications helps uncover data entry issues. Identify the manual data entry points. This is the most common workflow entry point for inaccurate data. If people fill out forms to capture data, are those forms used to capture data designed to ensure accuracy? Keying errors and misunderstandings impact processes downstream. Work toward solutions that validate entry at input to catch the most common problems. For example, an application can test data against valid ranges for page size, run length, finishing options, and paper type at order entry to avoid simple mistakes. Inventory and estimating systems can often test for valid data, too. Identify data integration points CRM data relies on, updates from sales team members and the back office, but with so many people involved, bad data will creep in, and data that is no longer accurate will remain. Many analysts and researchers believe that information in client databases has a high chance of being inaccurate. The team at Synthio say that 94% of B2B companies believe their client data is inaccurate. Imagine delivering a job to the wrong location or sending invoices to someone who is no longer at the client company! It happens! If the ERP and MIS systems are integrated, there may be many data exchange points. A change in any upstream system can cause the wrong data to be passed through to the receiving processes. It can be as simple as a new product number that falls outside of the range or format expected by the receiving system. What happens when bad data travels through the system varies widely depending on how the application programmers decide to validate it. It is fair to say that results are unpredictable and generally not accurate.
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