The Importance of Data for Operations Management and Decision Making

The Importance of Data for Operations Management and Decision Making Essay Sample

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 has to do something about this issue and fix it, look for the root of the issue, understand the problem and solve it. One has to be reactive and proactive in data quality to be at the cutting edge decision making. For Gartner´s model, level 2: Reactive, many Costa Rican companies come to mind which are at this level. In this level companies see data quality as resource for high level strategic decision making; only the upper management level use data in a way which will benefit the company as a whole and every other employee only see this data as something that doesn´t concern them because they don´t make the final decisions. This view is wrong, data should be used in every level of a company, disregarding whether you are a senior manager or a floor operator, quality data benefits the company as a whole. Perhaps a floor operator comes to realize that a process can be redesigned saving precious assembly time. This data comes from the floor and will benefit the company as a whole. In this level people wait for problems instead of looking for fixes before they occur. The data that is handled doesn´t allow companies in this level to be proactive and solve issues before they arise. It is an approach in which as issues arise then solutions are looked for, which wastes time and efforts from the company.

Then comes level 3: proactive. I feel that in the Costa Rican environment few companies are part of this level. The sad thing is data quality isn´t part of the Costa Rican culture and therefore not of importance to them. Even though this is the general view, some companies take a proactive approach in regards to data as Gartner suggests. The creation of key roles that provide data should be a must in every company. Departments such as the financial, sales, production and marketing should provide continuous data for a good decision making process. By consolidating data from all the departments the company can see where problems might surge and take a proactive approach to solve them. For example for next month production capacity will be 1000 units and sales intends to sell 1250 units then a problem is bound to happen. By consolidating data one can take a proactive approach and solve and issue before it happens, instead of putting out fires. Level 4 in Gartner´s model is Managed.

Sadly just a few enterprises in Costa Rica are at this level, and the ones that are, are multinational companies. In the Costa Rican enterprise environment national companies should look up to and copy the multinational models when they favor them. A managed data quality in an enterprise can be a key aspect for a company in terms of decision making. Companies should be at this level measuring regularly the accuracy and quality of their data and making continuous adjustments for better data and in hand better decision making abilities. The data quality dashboards should be employed in every company because they are visible for the whole company and show how data quality affects in a direct fashion how the company is run and how the decision making process is affected from the data it is given. Level 5 which is known as optimized is reserved for companies which are in a different league.

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