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Are companies taking action with data quality?

Rachel Wheeler Archive

Companies in every industry are aware of their dire need for higher levels of data quality. Simply gathering information from consumers is not enough - if that knowledge is riddled with mistakes, either because of human error or technical malfunction, it won't be able to deliver companies the results they're expecting.

The quality of data is becoming more of a hot-button issue. In an effort to purify their banks of information, companies are using address management solutions and other tools that can help them get rid of the imperfections in their data.

It's a good thing, too. Once companies can address the data quality issue, they can turn their attention to other matters - such as actually getting results from all the information they're collecting.

According to Forbes, finding the tangible benefits of data can be easier said than done. Chris Meyer, Tim McGuire, Maher Masri and Abdul Wahab Shaikh - four partners at McKinsey and Company - maintain that too many companies struggle to make their data-driven findings truly relevant.

"Data is meaningless unless it helps make decisions that have measurable impact," the McKinsey executives stated. "Unfortunately, many decision makers are ensnared rather than enlightened by big data, preventing data and insights from making it to the front lines in relevant and usable forms. Too many big data projects are formulated without input from front-line operators, or consume so much time that the insight goes stale before it can be used."

Companies can improve in this area. Quality of data is a start, but quality of results is the next step.

Start with the right raw materials
To achieve results in the end, companies need to begin by collecting data from their full range of customers, covering all the ground that they can. If they're only keeping tabs on a small subset of their clientele, it won't do them much good. However, Forbes cautions that business leaders also shouldn't obsess too much about "chasing after the perfect data set." If they go too far in that direction, they risk wasting time and money on an impossible ideal.

Set clear, achievable goals
Before beginning the process of collecting and purifying data, companies should decide what end goals they expect to achieve. Perhaps it's a matter of improving their sales practices, providing better customer service or utilizing new technology. Whatever the case, businesses should have clear goals from the start. This way, they can stay focused on their objectives and avoid getting sidetracked.

Work quickly and effectively
In an increasingly competitive business climate, everyone is trying to collect data and turn it into tangible results. The key, therefore, is to deliver data-driven insights at a higher speed than one's rivals. The latest trend is delivering information in real time - for example, if retail companies can make decisions based on sales that happened a mere few seconds ago, they'll be more in tune with consumer tastes than their competitors. Data quality is one thing, but data velocity is another that's equally important.

Change the culture in the long run
Forbes advises that over time, business leaders should aim to "build a factory" culture. In this context, it's not about producing goods - it's a matter of cranking out intelligence. By urging employees to bolster their everyday talking points with data-driven insights, corporate executives can change the business' mindset about data. Instead of being a niche concern that's only relevant to IT, analytics can become a mainstream part of the conversation.

But without emphasis on data quality, this reformed culture won't do much good. Businesses should focus on both the prevalence and accuracy of data in their future endeavors.