Maximizing Your Data Collection Procedures

Information is a key element in the business world. It is used to keep ahead of the market and to keep a healthy fiscal bottom line. Data collection is the process of gathering and measuring information on variables of interest. For a business, good data collection techniques lead to profitable information. However, marketers waste 21 cents of every media dollar because of poor data quality or data loss. Another way to say that is that about a fifth of market research yields zero ROI. 

Why Is It Important To Keep Accurate Data?

Keeping accurate data means getting things right. This is oversimplified because that’s the gist of the formula for success in business; a strong bottom line is the simple answer to any level of complexity in business. When data is corrupted or destroyed, getting things right becomes more difficult, which means the bottom line suffers. This can happen in any different aspect of business, even if not directly related to sales.

One way that a business can lose out because of bad data, for instance, is through its customer contact information. Missing or invalid contact information can cost a large-sized company about $238,000 per campaign. Another way is to conduct market research, whether qualitative or quantitative, and get back corrupted, incomplete data or lose it. Suddenly, in this scenario, the information that you’ve just solicited from your customers remains unused or is used incorrectly. Aside from costing sales in the immediate future, you risk alienating your customer base.

A sound data collection procedure is essential to maximizing the value of your data. Avoiding corruption is key to receiving usable information. There are many time-tested techniques to preserve data integrity.

How Do You Maintain Data Integrity?

Quality assurance and quality control are two approaches that can preserve data integrity and ensure the scientific validity of the results. Quality assurance refers to activities that take place before the data collection begins while quality control refers to activities that take place during and after the data collection.

Quality assurance is all about prevention, which is the most cost-effective activity to ensure the integrity of data collection. This proactive measure is best demonstrated by the standardization of protocol developed in a comprehensive and detailed procedures manual for data collection. An important component of quality assurance is developing a rigorous recruitment and training program. 

Quality control is largely about documenting everything appropriately. The quality control activities are detection/monitoring and action. A clearly defined communication structure is a necessary pre-condition for establishing monitoring systems. A poorly developed communication structure encourages lax monitoring and limits the opportunities for detecting errors. 

There are many forms of monitoring, including direct staff observations during site visits, conference calls or regular and frequent reviews of data reports to identify inconsistencies and other irregularities. 

Quality control always identifies the requisite responses that are necessary to correct faulty data collection practices and also minimize future occurrences. Some examples of data collection problems that require prompt action include systematic errors, violations of protocol and fraud or scientific misconduct.

Why Is Data Important for Your Business?

Possibly the most salient virtue of data is that it helps you to make informed decisions. There may be fate or luck or any number of elements that you can’t control in the business world or the marketplace. Lucky for you, gathering and evaluating data is something that you have the power to do and which can yield powerful gains. 

Perhaps you are in the food business and you’ve paid attention to the trend toward gluten-free foods. By pivoting before the rest of the pack, your brand can unveil the premiere line of gluten-free versions of your customers’ favorite items. Data can help you to redefine your brand. 

Data is also the best way for companies to resolve their problems and issues. It allows organizations to visualize relationships between what is happening at different locations, departments and systems. If the number of products that is being mislabeled has risen, an investigation may yield compelling reasons for this, such as increased staff turnover or equipment that is not up-to-date.

One of the biggest risks that a company faces is that which accompanies bad data. Incomplete or incorrect data, whether it’s customer contact information, product information or ambiguity in a financial dataset, can lead to losing clients and incur losses in revenue, as well. What can cost a large-sized company hundreds of thousands of dollars or more can sink a small business. Understanding the value of the process of collecting, evaluating and employing sound data is a marketable skill for anybody in the business world.