Whether you are a solopreneur or Apple, you know that analyzing business data is useful for good decision-making. However, even though we keep hearing examples of great analytics, many executives shy away from it. The studies vary in their estimates, but somewhere between 41% and 75% of leaders report substantial challenges using analytics.[1], [2]
For some leaders, the challenge is accessing and understanding their complex data sets. Others indicate discomfort in relying on analytics for their most important decisions. Still, others report not believing that data and analytics initiatives were driving success in their organizations.
If you are secretly one of these business leaders, this article will help reframe your stance on analytics. By the end, you’ll have several examples of applying analytics to achieve greater success with your own team.
How Much Money Have You Left on the Table without Analytics?
Your business has been successful, and that is fantastic. I’ll cheer you on all day for that. But my question for you is: were you as successful as you could have been?
If you’ve succeeded so far without using analytics, you might be astonished at what you can achieve with them. There is almost an endless list of ways you can leverage your business data to reduce costs and increase revenue.
For example, a restaurant chain might analyze residential demographics when considering where to build a new location.
Beyond simply looking at residential demographics, the chain might also assess local office space for potential weekday lunch business.
Finally, the chain can compare the potential competitiveness of a location by identifying restaurants with similar customer bases.
With these analyses, the restaurant chain can substantially improve the time to break even in a new location.
Targeting New Markets Segments, and Lines of Business with Analytics
We all know that customers are not a monolithic set of individuals. Rather, they represent diverse wants, needs, fears, and pains.
Talking to your customers through surveys, interviews, focus groups, or soliciting reviews provides a deeper understanding of who they are. Analyzing those data in the context of customer browsing, inquiries, and purchasing behavior can unlock new insights.
For example, savvy retail companies use customer segmentation analysis to identify subsets of unique customer preferences.
When new interests are discovered, such as preferences for eco-friendly products, the company can better cater to those interests.
The retailer might begin curating a line of eco-friendly products for those customers. Alternatively, they could identify opportunities to upsell or cross-sell products in the eco-friendly market.
Finally, if the retailer’s products align with as-of-yet-untapped customer markets they might consider strategic entry into the new market.
Using Analytics to Streamline Operations
Every business requires relevant and efficient processes in place for long-term success. When the subject of efficiency comes up, analytics is rarely far behind.
Analytics can help you across your operational landscape to identify and improve inefficiencies. Areas where analytics excel in streamlining operations include:
For example, a manufacturing company can use predictive analytics to anticipate equipment breakdowns, substantially reducing downtime and maintenance costs.
Many industries focus on inventory management to control holding time and spoilage. Executives can leverage analytics to reduce overstocking and the costs of unsold inventory.
Finally, e-commerce businesses using automated sales funnels need to be aware of performance at every step in the chain. Similarly, conversion rates for in-person sales teams can be tailored to customer preferences with analytics.
Enhanced Customer Experience Through Analytics
Your customer’s experience matters. It’s why businesses with great products and services, but poor customer experience, go under. Similarly, great customer experience can make a mediocre product or service highly successful.
Using analytics to improve your customer experience goes well beyond the old-school satisfaction survey (although these are important). Analytics can support the customer’s journey, from problem awareness to long-term loyalty.
For example, in subscription-based businesses, customer churn is a critical metric tracking the number of members who leave the service. Executives can use analytics to identify customer pain points in the user experience and make improvements.
By targeting user experience to reduce churn, business leaders will increase retention and improve the overall bottom line.
Similarly, a fitness center might use conversations with members to identify concerns or challenges with achieving their fitness goals. The owners can use analytics to review notes from these conversations and online reviews of their gym to minimize churn.
Finally, companies with significant social media presence might use analytics to assess content for commonalities associated with higher engagement. Content creators can use the analytic results to generate new content that customers find more useful.
Analytics for Strategic Decision-Making
From a strategic perspective, the executive’s best friend for decision-making might be the what-if analysis. Faced with multiple options for a decision, you can evaluate the potential impacts of each option and move forward confidently.
Strategic decisions such as expanding into new markets, launching new products, acquiring another company, and more all benefit from careful analysis of their downstream implications.
For example, in the face of potential regulatory changes, a company can simulate the likely impacts under different scenarios. Armed with the simulations from a what-if analysis, executives can await the final decision without the stress of uncertainty.
A logistics company might use an optimization algorithm like the traveling salesperson problem to optimize their fleet routing. With a few adjustments, the operations team can optimize routing to minimize distances and fuel consumption, thereby saving money.
Finally, because companies often fail due to over-expansion, executives can use analytics to determine whether expansion is likely to be successful. Your growth analysis might focus on forecasting market penetration and saturation, operating capital, and sales revenue to achieve success.
Conclusion
By this point, I hope you are beginning to see how analytics can help your business succeed. Of course, I don’t recommend trying to do all these analyses simultaneously. Instead, take a step back and consider the most important questions you want to answer. Then move forward by balancing your time and expenses for analytics to ensure you maintain a good return on your investment.
And IF you’re still on the fence, maybe it really isn’t the right time for you to implement analytics. If so, I would encourage you to think about what would need to change in your business to change your mind. Best to be prepared than caught off guard.
[1] SalesForce 2023. 73% of Business Leaders Believe Data Reduces Uncertainty and Drives Better Decisions – So Why Aren’t They Using It? Accessed on 9/15/2024. Available online at: https://www.salesforce.com/news/stories/data-skills-research/.
[2] Wavestone. 2024. Data and AI Leadership Executive Survey: Executive Summary of Findings. Accessed on 9/15/24. Available online at: https://wwa.wavestone.com/app/uploads/2023/12/DataAI-ExecutiveLeadershipSurveyFinalAsset.pdf
