Can you trust every bit of data and information coming across your desk, your screen or shared during a meeting? Probably not. How much of it is good? How good is it? One would like to think most of it is good, even quite good since millions have been invested in measurement and data collection systems, in report development, in database and data warehouse to ensure the right data and information are always available at your fingertips at all times. Today, the speed of business is such that regardless of how good, reliable, fresh and “trustable” the information is, we will use it in taking immediate action or in shaping future actions and decisions.
Then one day, we pick out an inconsistency and start pulling the data, the information, the reports apart. At this moment we realize the magnitude of the challenge of ensuring data quality throughout the life cycle of each data element that makes it way to a user or a system for immediate or future actions. There is a long list of things that can go wrong: wrong measurement system, poor calibration, undetected defective meters, manual data entry error, transcription error, wrong correction factors, engineering unit mismatch, stalled readings from sensors, missing or bad data in a file or in data historian stream, corrupted records, data loss due to communication system failure, wrong date and time reference, data from another system not available on time, gross error, bad presentation of the information, etc.
In process and manufacturing, information systems should be implemented with a system of check and balances to maximize the quality of data and the economic potential of data. Creating an environment where data can be trusted is not an afterthought. Data quality, similar to product quality, needs to be built-in our business and data management activities so that we can trust data for action at all times.
At Pimsoft, we care about data. Using Sigmafine® as a foundation, we implement the check and balances needed to ensure that anyone in the organization, relying on process and manufacturing data, is getting the best available and technically possible data quality at all and any times. Sigmafine uses proven methodologies based on physical conservation principles and supported by statistics and engineering standards to carry out these check and balances. Our users can testify to the importance and relevance of data quality in maximizing the value of information.
When it comes to data and information, value and quality are inseparable concepts. You cannot maximize the value from information without trust in your data. Pimsoft and Sigmafine deliver sustainable data quality governance and practices that will have a tangible and lasting impact on your business.
If you are interested to know more, join us at the at the SFUM 2015 on October 20-22, our upcoming annual Sigmafine Users Meeting. You will hear from users about the value of “trustable” information and learn how Pimsoft delivers data quality to its process and manufacturing customers. Learn more here.