The Importance of Data for Operations Management and Decision Making
The importance of data for operations management and decision making
In order to be able to make well guided decisions, one needs well based facts and therefore one is in continuous need of quality data. The same goes for operations management; data of substance is a must to run a company in its optimal levels of efficiency, effectiveness and capacity. The five levels of Data Quality Maturity according to Gartner are Aware, Reactive, Proactive, Managed and Optimized. Using these levels and applying them to organizations one can determine the data quality they possess. Of course one has to make a reality check because the theory doesn´t always adapt and molds to the reality, the Costa Rican environment portrays a good example of poor quality data. On the ongoing essay one will address the topics stated beforehand.
After taking a look at Gartner´s model and studying its levels, it is clear that the Costa Rican environment in general, fall into the first two steps of the model: Aware and Reactive. I feel most organizations in Costa Rica are part of level 1: Aware, because they have no critical analysis in terms of data quality. Most businesses tend to believe and as the article says believe computer data as “correct by default” which is a huge mistake. Computers are great tools for analysis and definitely simplify many complicated processes but in the end the information a computer gives is directly related to the information it has been given. There lies the problem. Many Costa Rican businesses believe that once data has been given to a computer it will magically adapt and generate new stats for the future. This is wrong, one should continuously cleanse the data in computers and no consider it a correct by default.
Another issue seen in the Costa Rican environment in level 1 companies, is the tendency to ignore data quality problems that are obvious and expect that they will disappear on their own accord. The moment one identifies a data quality issue one
In order to be able to make well guided decisions, one needs well based facts and therefore one is in continuous need of quality data. The same goes for operations management; data of substance is a must to run a company in its optimal levels of efficiency, effectiveness and capacity. The five levels of Data Quality Maturity according to Gartner are Aware, Reactive, Proactive, Managed and Optimized. Using these levels and applying them to organizations one can determine the data quality they possess. Of course one has to make a reality check because the theory doesn´t always adapt and molds to the reality, the Costa Rican environment portrays a good example of poor quality data. On the ongoing essay one will address the topics stated beforehand.
After taking a look at Gartner´s model and studying its levels, it is clear that the Costa Rican environment in general, fall into the first two steps of the model: Aware and Reactive. I feel most organizations in Costa Rica are part of level 1: Aware, because they have no critical analysis in terms of data quality. Most businesses tend to believe and as the article says believe computer data as “correct by default” which is a huge mistake. Computers are great tools for analysis and definitely simplify many complicated processes but in the end the information a computer gives is directly related to the information it has been given. There lies the problem. Many Costa Rican businesses believe that once data has been given to a computer it will magically adapt and generate new stats for the future. This is wrong, one should continuously cleanse the data in computers and no consider it a correct by default.
Another issue seen in the Costa Rican environment in level 1 companies, is the tendency to ignore data quality problems that are obvious and expect that they will disappear on their own accord. The moment one identifies a data quality issue one