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2 Measures to Unlock the Value of Your Data Analytics Investment
By Laura Patterson - President and co-founder of VisionEdge Marketing, Inc.
Friday, 28th April 2023
 

Decisions, Decisions, Decisions: It’s estimated that the average adult makes about 35,000 decisions every day, so that’s about 2000 decisions per hour.

In today’s business world, many of these decisions are about customers, competitors, personnel, operational, and strategic investments. Data is a crucial asset that can help any business leader make informed decisions and gain a competitive advantage. Data analytics and insights are the keys to unlocking this potential.

According to Octolis, many companies are investing 2-6% of their total expenses on data analytics, which includes tools, salaries, and services. For many companies, this investment is six figures. With this level of investment, it’s becoming increasingly important to be able to measure the value of your data analytics investments.

Let’s explore two measures any size company can employ, and some examples of how tracking and improving each measure benefits your business and proves the value of existing and new investments:

  • Cycle time. Reducing cycle time enables your organization to respond more quickly to changing market conditions, customer needs, and internal challenges.
  • Impact. Measuring impact enables more effective data-driven decisions about how to allocate resources and where to focus your efforts.

The Growing Importance of Data Analytics in Today’s Business Landscape

Organizations recognize that data is a critical asset and valuable resource for providing insights and uncovering patterns into customer behavior, market trends, and operational efficiency. Analyzing this data has emerged into its own industry. In their Data Analytics Market Research Report: Information by Function, Type, Organization Size, Solution, Deployment, Application, and Region- Forecast Till 2030, Market Research Future anticipates the data analytics market to acquire a valuation of approximately USD 346.24 Billion by the end of 2030.

The report further predicts the market will flourish at a robust CAGR of over 30.7% during the assessment timeframe. This growth reflects the growing importance of data analytics in today’s business environment.

Why the increased growth? Because most organizations believe that by effectively analyzing data they can:

  1. Identify new opportunities
  2. Optimize business processes
  3. Compete better

For example, a manufacturer can use data to determine which products are selling well, which industries are buying those products, and how to optimize their inventory and supply chain.

In addition, data can be leveraged to create new revenue streams. For example, retailers use data to create personalized recommendations for their customers, driving increased sales and customer loyalty.

The challenge is that it takes time to know whether decisions related to achieving these three benefits and others actually pay off. Given the level of investment, it’s understandable that organizations want measures they can use NOW to assess whether the investment is worthwhile. For companies who struggle with measurement, we recommend two measures to understand the investment value: decision cycle time and the number of decisions impacted.

Cycle Time: The Importance of Quick, Informed Decision-Making

In an essay by Benjamin Franklin that appeared in George Fisher’s 1748 book, The American Instructor: or Young Man’s Best Companion, he wrote, “Remember that time is money.” This saying may mean different things to different people, and one of the meanings for business is that delaying an initiative comes with a cost, such as a lost market opportunity.

Therefore, decision cycle time, the amount of time it takes for an organization to make a data-based decision is a valuable measure. Decision cycle time provides a measure of how quickly an organization can respond to changing market conditions, customer needs, and internal challenges.

Decision-making is time-consuming. A study by McKinsey found many businesspeople spend more than 30 percent of their working time on decision-making, and more than half of this time was thought to be spent ineffectively. McKinsey calculated that for managers at an average Fortune 500 company, this could translate into more than 530,000 days of lost working time and roughly $250 million of wasted labor costs per year. They found that winning organizations—which are represented by only 20 percent of respondents in their study-make high-quality decisions fast, execute them quickly, and demonstrate higher growth and/or overall returns from their decisions, relative to their peers.

This is why it is worth measuring how long it takes to go from data to analytics to insights to a decision. Any organization can track how long it takes for it to move from data collection to decision-making. To create this calculation, remember to include the time it takes to collect and analyze data, as well as the time it takes for decision-makers to review the data and make a decision.

Relatively simple cycle time and/or time tracking software can help identify areas where improvements can be made, such as streamlining data collection and analysis or improving communication between decision-makers.

Impact: The Importance of Insights for Better Resource Allocation

Measuring the impact of data analytics and insights is essential for determining the value of these resources to your organization. The annual Voice of the Enterprise survey conducted by S&P Global Market Intelligence revealed that only a little more than 25% of the participants said that nearly all their decisions are driven by data, while 44% said most are. A simple way to measure the impact of data analytics and insights involves tracking how many decisions were influenced by the insights derived from analyzing data.

For example, what decisions if any were influenced by data to determine which new market to enter? An organization can go one step further and determine whether the decision had a positive impact on the organization. For example, did a data-driven decision to make a change in a customer service process improve the customer satisfaction scores?

In this example, this type of measure entails tracking customer satisfaction scores before and after the change was implemented. If you decide to do pre- and post-decision measurement, it’s important to measure one decision at a time to accurately determine the relationship of the decision to the result of the decision.

Measuring impact is critical because it provides your organization with a clear understanding of the value of your data analytics and insights. Tracking the impact enables your organization to make more effective data-driven decisions about how to allocate resources and where to focus your efforts.

Data-Driven Decisions Play a Vital Role in Continuous Improvement

Measuring decision cycle time and impact can help your organizations identify areas where improvements can be made in your data analytics and insights processes. For example, if a decision cycle time is too long, an organization can identify bottlenecks in the data collection and analysis process or gaps in communication between decision-makers. Similarly, if the expected impact is not being realized, your organization can identify gaps in your data analytics or decision-making processes.

Data is one of the most valuable assets for any organization. It can provide critical insights into operations, customers, and market trends. When you reduce decision cycle time, your organization has the opportunity to respond more quickly to changing market conditions, customer needs, and internal challenges. By tracking impact, your organization can make data-driven decisions about where to focus its efforts and allocate resources.

The use of these two measures can lead to increased productivity and revenue, reduced costs, and improved customer satisfaction. Both are relatively simple measures any size organization can use to assess the value of their data analytics investments and processes.

Let’s talk about how you can improve your data analytics and insights processes to make quicker and more informed decisions that drive success.

Laura Patterson is president and co-founder of VisionEdge Marketing, Inc., a recognized leader in enabling organizations to leverage data and analytics to facilitate marketing accountability.

Laura’s newest book, Marketing Metrics in Action: Creating a Performance-Driven Marketing Organization (Racom: www.racombooks.com ), is a useful primer for improving marketing measurement and performance. Visit: www.visionedgemarketing.com

Disclaimer: Any VEM information or reference to VEM that is to be used in advertising, press releases or promotional materials requires prior written approval from VEM. For permission requests, contact VEM at 512-681-8800 or info@visionedgemarketing.com. Translation and/or localization of this document requires an additional license from VEM. Note: All content within this website is property of VisionEdge Marketing. Any use of materials, including reproduction, modification, distribution or republication, without the prior written consent of VisionEdge Marketing is strictly prohibited. Reprinted with permission.

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