Manufacturing Efficiency and the Importance of Data Quality
By: Gavin O’Heir
Your company and your products are only as good as your data. This statement bears repeating often because it is so important – quality data is your greatest asset. Manufacturing efficiency is the major goal every manufacturer strives to achieve, and it can only be accomplished by inputting, managing, maintaining, and utilizing high quality data.
Data informs every step, every process, and every response undertaken by your company. It informs product design and development, communicates customer needs, fulfills raw material requirements, and determines shop floor level manufacturing processes. Without high quality data, these and other key business and operational processes will slow down or, worse, grind to a halt. You cannot afford to have any of your systems clogged with low quality, incomplete, or redundant data. Your manufacturing efficiency depends on it.
Let’s be clear – data quality is NOT your IT team’s problem. It is an enterprise-wide, all-hands-on-deck endeavor that requires commitment, input, and focus from every employee, from the business suite to the shop floor. Significant improvements to data quality can be achieved quickly when everyone is pulling in the same direction and committed to purging poor data.
So how can you be assured of high quality data to improve manufacturing efficiency? Here are some best practices to help you achieve the quality you need:
Establish a data task force or governance team that is responsible for creating data rules and standards for data input, storage, management and use. The team should have the authority to address any and all data-related issues and correct problems.
Identify every way in which data enters your system so that you can account for every data input point and ensure that redundancies, incomplete or unnecessary information, and errors don’t pollute your IT environment
Use a data quality management (DQM) tool that will help with key DQM elements such as defining and auditing data cleansing rules, data quality planning and checklists, defining and evaluating data profiling rules, and reporting.
Standardize master data and how it’s entered so that every business system and process is working with the same standardized, accurate data set. This includes company name, address, contacts, billing and shipping information, and all other necessary data that enables you to fulfill customer requirements, process orders, interact with suppliers, manufacture products, and ship finished goods.
Don’t reinvent the wheel every time there’s a production glitch cause by poor data. Every work-around, every manual data entry and one-off solution to temporarily fix a problem has a ripple effect on productivity, inventory, reporting, and revenue that’s detrimental to the entire company. It means you have a data quality problem and it’s vital to fix it so you’re not wasting time and money constantly coming up with temporary solutions.
Engage all employees in data management and encourage them to point out potential issues so that it’s easier to correct them and prevent small problems from getting larger.
As you can see, there is a direct correlation between data quality and manufacturing efficiency. You cannot have the later without the former. If a company goal is continuous improvement and you’re focused on reducing waste, improving productivity and streamlining operations, you must fuel your efforts with high quality data. It is the one resource you cannot do without.