Being clear on what you want is key
Tracy Currie //March 14, 2016//
Being clear on what you want is key
Tracy Currie //March 14, 2016//
Data is exceptionally valuable for companies making decisions concerning reducing costs and increasing revenues. Though it’s seemingly simple to run a data report, getting to the right actionable insight can offer both opportunities and missteps.
Being crystal clear on what you want from the data is critical. This means understanding the specific business problem being addressed and the data needed to reach your goal. Willingness to tweak the business questions to better address the problem along the way is also critical. Data analysis should be considered a journey of discovery versus a black-and-white, requirements-driven process. It often takes turning the data, like a kaleidoscope, before the right data pattern takes form.
Let’s look at how to use the right data to reach your business goals faster:
Don’t retrofit data points to create the question. Instead, ask: How can data support our decision-making? When data gaps exist, look for accessible third-party data such as weather, credit scores, or other key factors that can improve the quality of your insights. For example, field service calls can use data to reschedule a truck roll when inclement weather is forecast within 2.5 kilometers of a customer’s address. The customer doesn’t lose a day of work and the company saves the cost of redundant service calls.
The competition is coming! Traditional ways to explore (yet another proof of concept) and deploy (yet another 2-year IT project) are too slow. Alternative models, such as analytics or insights as a service, exist, but too often, they are the same old rusty jalopy with a fresh coat of red sports-car paint. Many data providers can help you crunch data efficiently. IBM Watson is one of the larger players to consider, but smaller, more nimble alternatives exist as well.
Let’s look at a real-world application. A Fortune 100 company used big data to improve customer retention and maximize marketing and promotion dollars. Historically, renewal offers remained consistent across its customer base. The company wanted to know how to maximize marketing dollars to retain the highest-value customers.
The company used internal data to identify upcoming renewals by location and credit history. Then it layered in third-party data, including competitor offers and the macroeconomics and psychographics influencing its customers by geographic area. The company segmented its highest-value customers and tailored offers by economic and competitive factors, by region, with a high degree of accuracy and cost efficiency. The result: The company improved upon its current churn model by 3 percent—nearly unheard-of in its industry.
Big data can reap big rewards if you use the proper analytics process. While your internal data is invaluable, using detailed rather than summarized third-party data can often expedite your path to profitable outcomes. Some say big data is all hype, but the reality is no matter what you label it, consumers expect businesses to tailor services and messaging. If you don’t, your competitor will.