Making Analytics Work

How can you make analytics work for your organization?

That’s the question we’ll be asking in each Profit Center column.

For many people, “analytics” brings to mind math whizzes, heads buried in data looking for new ways to make money. It’s true that analytics has numbers at its foundation, and it’s true that analytics can bring powerful mathematical methods to bear on complicated problems. But analytics isn’t – and shouldn’t be – magic. It’s a tool.

Amazon, Continental, Federal Express, Google, Harrah’s, Hertz, Walt Disney – all have embraced analytics as an essential tool for doing business. Whether scheduling flight crews, managing a fleet of hundreds of thousands of cars, or mining data to determine who’s most likely to respond to an ad campaign, these companies rely on analytics. The reason? Competitive advantage. Company computers contain vast quantities of data that can be used to operate more profitably. But that data must be converted to usable information. That’s where analytics comes in.

Analytics has tremendous value – value well worth pursuing. But bringing analytics to an organization can be challenging, especially if it’s new to a company. We’ll address the many challenges in future columns with one simple goal: to help you overcome the obstacles you’ll face when building a strong, analytics-enabled business.

So what are some of these obstacles? Perhaps the biggest is getting people to think differently. Change is always difficult within an organization, but especially so when it intrudes upon ingrained habits. A long-time truck dispatcher isn’t likely to look kindly upon software that tells him how to do his job. A sales agent who’s spent decades developing relationships with his customers may find it difficult to quote a price he’s not comfortable with, even if that price was determined from a detailed analysis of past sales data. Some skepticism is healthy, but not so much that it thwarts improvement.

Just as problematic as skeptics are people who look upon analytics with almost mystical reverence. They adhere to a belief that all answers can be found in data, and that analytical tools are so powerful it’s only necessary to get the math right. Individuals with and without advanced analytical training make this mistake. It’s a mindset that can lead to costly project delays with little to show for the effort. It also marginalizes human experience. Analytics is capable of performing analysis humans can’t, but it isn’t intended to supplant experience. The best analytics-based solutions, and those that cement themselves in the ongoing operations of an organization, strike the right balance between analytics and experience; between math and business knowledge.

Analytics professionals have their own set of encumbrances. Most are trained in some combination of operations research, statistics and computer systems. People fresh out of school often make the mistake of assuming everyone speaks a language of lambdas and sigmas. Over time, the best analytics professionals learn to express their ideas in non-technical terms. Still, communication between those with and without analytical training is always a challenge.

Like the words “economics” and “business,” “analytics” covers a lot of territory, and deciding where to begin is another challenge. Are you grappling with high delivery costs? Low or negative margins as a result of pricing policies? Are you trying to understand how to better serve your customers? Analytics proves beneficial for these and many other questions. Finding the right place – and the right level – to focus your efforts is important to realizing your goals.

Staffing for analytics endeavors can be difficult. Consultancies provide a good way to gain a foothold, but an analytics-enabled organization needs to build core competency in analytics. Without such competency, an organization must depend on the representations of outsiders. But even more importantly, it’s necessary for a business to seed the analytics mindset so it can grow and flourish. Analytics is a tool, but it’s also a way of thinking. Computer spreadsheets are a much better tool for adding a column of numbers than a pencil and paper. But even more, when we fully comprehend what spreadsheets are capable of, they open a world of possibilities. The same is true of analytics.

Another analytics related challenge is the choice of computer software. Powerful software exists for applying the methods of analytics. Some software focuses on very specific problems, like vehicle scheduling. Other software focuses on mathematical methods that can be applied to many different problems. Statistics, forecasting and optimization software fall into this category. Some analytics software is intended for a single user on a personal computer and is used to solve a problem once a month. Other software is designed to support hundreds of analysts on a daily basis. Some companies choose to buy software, while others choose to build their own. Each alternative has its merits and drawbacks. Finding the right approach can mean the difference between success and failure.

So with the many obstacles facing analytics, is it worth the investment of time, money and effort? Yes. Great companies look to the horizon and embrace change. Companies that don’t go out of business.

Analytics is the future. Businesses now find themselves with a wealth of data. It’s a relatively new state of affairs – the byproduct of computer software designed to manage transactions: sales, orders, payments, shipping. And what great companies know is that this data can be used to reduce costs and increase revenues; to build a better, more profitable business.

How can you make analytics work for your organization? That’s the million-dollar question we’ll be striving to answer.