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5 keys to greater profitability through data analytics

Despite its dramatic power, data analytics isn’t an exciting concept for most people. The very term can cause eyes to glaze over and heads to swim. That changes the minute a business owner realizes how the secrets hidden within the data can improve profitability.

Data drives an increasing number of business decisions in the digital age, helping companies like Amazon and Uber transform the business landscape, but small and midsized businesses can reap the benefits of big data too, if they know how to use it.

Gathering the metrics that form the basis of technical analysis has never been easier. Robust customer relationship management software and similar business tools allow leaders to see a complex web of patterns and correlations that describe almost every aspect of the company, but simply having the data isn’t enough.

To gain meaningful results, leaders should focus on these five keys to achieving greater profitability through data analytics:

1. Ask the right questions. Looking at end results like sales, customer retention rates or revenue is informative, but these metrics are purely descriptive. What drives customers’ decisions to purchase or not purchase your products (advertising, brand loyalty, price)? Which vendors are the most cost-effective? Which products have the highest rate of complaints and returns? Narrowing the questions allows the data to reveal detailed relationships that form the basis for actions.

2. Use appropriate data. Most businesses struggle with a surfeit of data, rather than too little. To discover meaningful patterns, narrow your focus to evaluate specific data elements. Identifying operational inefficiencies needs an entirely different set of data than the metrics you’d use to understand customer wants and needs, to determine how to deliver the right information at the right time, or to evaluate market trends. Finding answers to some questions might require you to begin by manually integrating information collected by multiple systems, especially if a company's business management tools are more siloed.

3. Leverage specialized skillsets. Because big data is, as the name implies, voluminous, it’s important to apply the right tools to maintain data integrity and ensure an optimal analytic approach. While existing staff could probably find useful patterns, getting maximum value from data means calling in true experts. Many businesses choose to outsource advanced data analytics or to bring in external consultants. Midsized and larger companies may prefer to invest in a permanent in-house analytics team. Whichever route a company chooses, you’ll be well served by experienced analysts who can apply appropriate techniques for parsing the data.

4. Push beyond descriptive analysis. To change outcomes, it’s important to understand what is causing the patterns the data describe. A careful examination of the data will show you what is happening. The more important question, though, is why these things are occurring. What is likely to happen in the future, and what should you do about it? Using predictive and prescriptive analysis, data-savvy professionals can uncover key insights to inform business decisions that boost the company’s bottom line.

5. Take strategic action. Formulating a response to new information is the real test of leadership. How much change can and should the business embrace, and how quickly? Which risks are the most urgent? Which opportunities are the most time-sensitive? Will adapting to leverage an anticipated scenario create long-term benefit? Numerous questions like these arise from the answers data analytics provide, and resolving them wisely demands sound judgment as well as an intimate familiarity with the unique business context.

From identifying new markets and meeting customer expectations to managing risk and capturing time and dollar savings, data analytics holds the potential to revolutionize how business leaders navigate the daily challenges of running a company. Finding a clear path through an overwhelming volume of information can be challenging, to be sure. But the payoff for those who persist and make changes in response to their findings is a significant improvement in market positioning and profitability.

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Analytics Data science Small business
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