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One of the main keys to setting up an effective data quality plan is clarity. The information in the plan needs to be clear to every person who will be involved in following that plan. In addition to this, the plan will need to be concise while still including all of the details that are needed for successful execution. The first step is to clarify the end result. What is the ideal result to which this plan should be leading?

The Purpose Of A Data Quality Plan

For example, if a store wants to increase their sales by 15% over the course of the year, and the data quality plan is to be created in order to keep managers informed of sales trends across all branches, the end result is an increase in sales across all stores. The purpose is to keep the managers informed. The second step is to create a list of the most important focus points of the plan.

In the case of our example above, the data will need to be accurate, timely, and clear. The next step is to determine the technology that will help to ensure these qualities are maintained and that data enhancement is being taken care of. Systems will need to be put in place that will help to make certain that the information received by each manager contains figures that are accurate, updated according to the relevant time scale, and clear. Each figure in the data quality tool should be clearly represented in order to prevent any confusion or error in interpretation.

Guidelines Are A Necessity

In addition to this, a set of guidelines needs to be created that will help those who need to use the data to interpret it correctly in the context it has been set. The systems used for gathering and reporting the data need to be completely reliable so that each person dealing with the data reports is certain they can rely on, and act on, that information. Setting up the plan means checking each point along the process to make sure that the systems to be put in place have been tested and are fully reliable.

It is a good idea to include in the planning process, one or more of those individuals who will be using the reports. This will enable them to point out any potential problems or areas of confusion; it will also give them an opportunity to make sure that they fully understand the process and what is required of them. Clarity throughout all stages of the planning and implementing of the data quality report is essential in order to ensure that you get the best results.

Coming up with a data quality plan that will best serve the purpose you are creating it for means starting at the end. Starting with the ideal end result in mind, and going into as much detail as possible on that end result before you begin planning the solutions and technology needed will help you to hone in on the technology and data solutions that will be most effective in achieving those specific results.

The author:

RingLead offers a complete end-to-end suite of products to clean, protect and enhance company and contact information, leading to improved organizational efficiency, reliable business intelligence, and maximized ROI on CRM and marketing automation investments. Since 2003 RingLead has helped solve the dirty data problems of large enterprises, Fortune 500 companies and small businesses across the globe.