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6 Reasons Why Improving Your Business Processes Can Significantly Improve The Quality and Quantity of Data

Most of you know by now how important data is to your business. Data can be referred to as the lifeblood of a business. The data that is collected, how it is collected, the accuracy of the data, and the insight gained can really set businesses apart from their competitors. We have all heard the term digital transformation. This is the process of integrating digital technologies into the business to create new or modify existing business processes, company culture and customer experiences, and fundamentally change how the business operates.

There are a number of benefits gained by embarking on a digital transformation journey, one of the biggest being the improvement an organization’s data. Opportunities for collecting the right data and gaining actionable insights are obvious. However, many businesses, large and small, have the same problems, collecting the right data, entering it accurately and in a timely manner can be challenging. Without proper data, business leaders miss out on the opportunity to use the data to make intelligent business decisions or even confirm some assumptions they have with data to support it. We have heard over and over how great it is for organizations to make data-driven business decisions. In fact, according to a survey conducted by PWC of more than 1,000 senior executives, highly data-driven organizations are 3 times more likely to report significant improvements in decision making compared to those who use less.

Organizations these days not only need more data but quality data because decisions made on inaccurate data is no better than a house built on faulty building materials. In a lot of ways, it can be a sort of catch 22 because better business processes often lead to more data and better quality data leads to the ability to perform analysis that leads to better and more efficient business practices. One question that comes to mind is “If you do not collect data (metrics) or measure it, then if you improve it, how do you know it has improved or quantify how much it has improved?” And if data is that important, then it would also surmise that data quality is extremely important as well. So, how can we not only collect more data, but improve data quality. You can start by improving business processes. Here are 6 reasons why improving business processes can significantly improve the quantity and quality of an organization’s data.

1. Consistency

Quality data collection starts with consistency. Having guidelines as part of a process for adding data to key systems, like CRM, HR, Accounts Receivable, or Inventory, for example, is a great start. Do all key data elements exist and are entered the same way across all record sets and time periods? Is it documented and followed by everyone in the organization? For example, a company that sells camping equipment would benefit from having a documented process for how to enter contacts into a CRM, requirements for documenting interactions with contacts and a clear process that everyone follows for moving contacts between marketing and sales. This can prevent a lot of missed opportunities. This will also go a long way to ensure that the data is available and users of the data will understand what to expect.

2. Timeliness

Knowing that an organization has the data needed to make business decisions or capitalize off it is great, however, if the data is not available when it is needed, it is a problem. What good is having data required to make a decision a week after it is needed? For example, if complete information about contacts is not entered into the CRM system until the end of the week, this could result in missed opportunities for follow-up contacts and additional sales. What if a qualified lead prefers to be contacted by text but this is not indicated when the lead is passed to sales and sales continuously sends emails that go unanswered. One approach is setting aside some time to audit data at the end of the week or month, to fill in missing data, but this requires an exceptional amount of discipline and probably will not work in the long term. Correcting data is boring, difficult, mind-draining, and costly. It will make employees scream, why wasn’t this entered correctly in the first place. A better approach is to enter it correctly upfront to prevent bad data from occurring in the first place. This also provides the greatest probability that the data will be available when it is needed. Integrating this into the business process will save a lot of time and aggravation.

3. Accuracy and Completeness

Data should be accurate and clearly represent its intended cause. It should also be complete enough to provide value. Is all data necessary to be useful available? For example, a customer name with inaccurate contact information is pretty useless for follow-up opportunities. The key data elements for every type of entity collected must be defined. Make it mandatory that this information is entered completely and accurately. Many factors may impact this including lack of knowledge, importance is not communicated to everyone, users too tired, other pressing tasks can lead to inaccurate data or incomplete data. Business process redesign can improve accuracy as well as completeness but this must be part of the culture. In addition, assigning responsibility for the accuracy of data to data owners can go a long way to more quality and trusted data throughout the organization.

4. Integration

Today, most organizations from the very small to large use multiple systems to manage various business functions. For instance, a CRM for contact management, an accounting system to manage accounting, email marketing to manage email marketing campaigns, an inventory system to control inventory, and a payroll system to pay employees. The problem is that much of the same data is required in more than one system. And far too often, employees manually enter the same information in multiple systems, causing issues like duplicate data, errors in data, and incomplete data. This is a great opportunity to include integration of the data between applications as part of business process redesign. That will not only save a lot of time for your employees but also reduce their frustration of having to manually enter the same data in multiple places.

5. Automation

Any business process redesign and improvements should include looking for opportunities to automate manual, mundane, repetitive tasks. However, this should not be done piecemeal by department but part of an organization’s overall digital transformation effort. Many companies have begun implementing robotic process automation or RPA. There are several advantages to implementing automation including less data issues caused by manual data entry errors, more timely data entry, gives employees more time for high-value work, and higher employee satisfaction. Automation is not new, it has been around for years. However, the capabilities have improved significantly in the last 10 years. Time is truly money and implementing processes that save employees time may be easily quantifiable in terms of money saved, but increase in employee satisfaction is more difficult but can be just as important. Therefore, the use of automation should be a key capability in redesigned business processes.

6. Culture

The culture of an organization is often the most important to the success or failure of any great transformation. Cultural changes are part of any lasting and effective changes to business processes. Successful efforts tend to be championed from the top. Businesses have to be intentional about their efforts. Data collection should be built into an organization’s processes and there is no better person to champion this effort than an organization’s executive team. It should not be thought of as a burden but as a core part of business processes.

In closing, no matter where your data is in the lifecycle, improving its quality is a long-term process. This work isn’t glamorous, but it will pay off in the long run and provide better data, decisions, and outcomes.

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