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Quality Analysis for Business Data and Why It Matters

For any large business operation, there is most likely a complex IT structure that enables communication both within and outside company walls. The IT network is chalk full of data that permits transactions and commands to be processed efficiently and correctly. Communication of data is what keeps a business operation going and as we head into 2013, the accuracy and dependability of data has never been more crucial to a thriving business and cost-effective IT budget. Within a company, actions are initiated by high-level people and then the values of these actions trickle down to lower rungs of the business model.

What the leader or leaders of a company believe is usually instilled in the company genetics from the beginning. These values are a large commitment, because current and future decisions are based around the company’s mission and guiding principles. These values extend all the way to business data, as these resources enable the company to function and prosper. If a company prides itself on being efficient and organized, data management must follow suit. Committing to quality data is one of the most vital moves an IT management team can make. An IT department is only has strong as its weakest data point, and any seasoned IT data specialist will agree.

In 2013, focus on the accuracy of data can improve or fracture a business supply chain. With quality of information, there are only two categories: perfect and imperfect. The importance of this discussion can be illustrated through a hypothetical computer manufacturing company. There are three steps that can help an IT management team capitalize through data quality within this mock company.

1. Check to make sure supply numbers match up

A huge component of any supply chain, a computer manufacturer in this case, is the data relating to the suppliers and how IT manages that data. Does the data accurately represent what the business needs? Does the shipment data show the same number of motherboards arriving as there are LCD monitors coming in? Are there duplicate numbers listed, causing excess processing? What is causing these issues? This computer business needs an exact number of supplies because there are an exact number of computers that they want produced. While databases are not an exact science, there are ways to make them very precise. For instance, analyzing columns of data individually before then comparing them to each other can help ensure quality. An example of this is organizing the zip code column for all of the outgoing delivery addresses. Rather than just focusing on the name of where the computer will be delivered, studying other columns can help simplify the files. What this example can do is show frequency of zip codes for better shipment efficiency, as well as faulty outlier zip codes. Now, the illegitimate zip codes can be contacted for update and the remaining can be easier grouped together from shipment processing. Although certain parts of the manufacturing process will require different column focus for analysis, quality reorganization of the zip codes will make the shipment part of the supply chain much easier and cost-efficient. Company costs, specifically related to IT, will go down as organization increases. Who knows, maybe this company was organizing shipments to clients in the same business sector. Now, with quality analysis of data, they can transition to shipping based on physical address. This would lead to more consolidated shipping with relation to address, thus saving transport costs and time.

2. Consolidate data applications where possible

In a place like a computer manufacturing company, there are many people and applications that process information day and night. Crunching and organizing information and data is a taxing job that involves dedicated employees and reliable computation applications. In large scale operations, such as our mock manufacturer, there are different processes going on all the time that rely on other applications in some way. In supply chains, even more specifically as we enter 2013, everything must be right on schedule as people live their lives in real time and expect nearly instantaneous results. Each rung of the supply chain along the road to the customer wants their product delivered, in the correct form, very quickly. Because of this, managing applications that control data communication need to be on point. Instead of having five people manage twenty applications that organize the supply delivery database, update the software so that one person can manage and troubleshoot the situation through three applications. Acquire software that enables all batch processing and other procedures related to the manufacturing to be viewed from a central screen. Rather than relying on several employees to monitor several servers, this would enable one employee to oversee and troubleshoot many processes on demand. Simple consolidation like this lowers chance of communication breakdown and centrally focuses responsibility and execution. Consolidation also focuses training and makes business values easier to transmit early on in a job role. This leads to more quality data and business practice because there is less chance of any information being missed in the early stages of employment or data management. Human error within the IT team will still be a factor, but to a lesser degree. The chance of data quality being upheld increases when there is fused application management.

3. Align data practices with business values

IT management is in charge of managing data that makes up the inside of the company body. The data should accurately represent what the company portrays itself to be in public. For instance, if the owners of this computer manufacturing company are environmental proponents, the data should tailor to this. There should never be erroneous data leading to excess product manufacture and faulty shipment methods. This wastes labor, time, gasoline for delivery, plastic, metal and energy to engage delivery. The little things are what need to be focused on in data management processes. IT is a special entity in the sense that it controls data in masses never seen before. Professional workers in the field are trained in a very interdisciplinary way and this should raise expectations for the perfection of data processing. Computers aren’t perfect, but they are very close when humans use their applications correctly to achieve legitimate data quality. If you know where the problem comes from, it becomes easy to solve.   In 2013, data and information power business. It’s important for business leadership to understand the importance of managing resources and communication properly when it comes to the internal structure of the operation.

Written By

Grant Davis is a Data Modeler by day and a writer by night. His passion for computers started when he discovered instant messaging in junior high school. When Grant isn't trying to climb through the computer screen he writes for BMC, a leading mainframe management provider.

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