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Posts Tagged ‘predictive modeling’

Predictive Analytics Helps Change the Face of Recalls

AutoRecallsThere are few events more costly to a business than a recall. The costs in terms of lost time, lost money, and lost public trust can be staggering.

And, of course, nobody wants to put consumers in danger.

Fortunately, predictive analytics has changed all that. According to Automotive News, data mining has just helped GM limit a recall to just 4 cars.

That’s right, four cars.

In the past, the auto maker might have recalled the model and inconvenienced tens of thousands of owners, despite thinking just a few cars had the defect. Or it might have let the defect slide, putting a few customers at risk of a crash.

But…[when]…a 2012 Chevrolet Volt was brought in for a warranty repair in Europe, General Motors had a third, better option.

On May 30, the auto maker assigned the engineer to dig into a data base that tracks the parts used in its cars, and it collected manufacturing records from the supplier–in this case, TRW Automotive. Within a month, GM had identified [all 4]…of the cars on US soil with the faulty valve, called the owners and sent a formal notice to the US Government.

…Maureen Foley-Gardner, director of field performance evaluation at GM, said the auto maker had used its database for 20 percent of field actions this year, up from 5 percent in 2012, and watched as the average action has shrunk by 40%.

This development is poised to save the auto industry a staggering $50 billion per year. And, as the article goes on to note, this accomplishment only scratches the surface of the kinds of problems that auto companies are solving every single day when they use data mining the right way.

If you’d like to start seeing big results in your business then it’s time to get the training that you need to use data mining correctly. Start with TMA’s free webinar, then move on to The Modeling Agency’s advanced training courses.

Which problems will you solve today?

Predictive Analytics Helps Sales Teams Become More Productive

salesrepresentativesAny business that has a sales team knows that reducing wasted time is one of the biggest challenges sales managers face. And nothing wastes more time than pursuing the wrong leads.

This is why good leads can make the difference between a good sales team and a great one.

A recent Forbes article discusses how one company is using predictive analytics to solve this problem. Forbes had a conversation with Jascha Kaykas-Wolff, the Chief Marketing Officer of Mindjet, a company who has used predictive analytics to make this difference.

Mindjet is using predictive analytics to understand which leads are the highest quality and have the highest probability of turning into sales. With several thousand leads and trials being generated every week, traditional lead scoring techniques were not reliably segmenting out which leads had the highest probability of closing. With dozens of attributes included in their lead scoring application, Mindjet still wasn’t effectively providing the sales team with highly qualified and prioritized leads.

Getting only the highest qualified leads to sales can make the most of their selling time is a high priority for Mindjet marketing. This required the marketing team to get beyond lead scoring and determine which factors most and least contributed to lead quality.

Mindjet’s efforts resulted in 4.4 times more qualified leads than the company had previously enjoyed. That’s a lot of closed deals and a huge return on investment that will continue to play out in the very near future.

Do you want to win similar results for your business? If you approach predictive analytics the right way, you can! You just need the strategic training to use these methods appropriately.

If you’re ready to get started, try TMA’s free webinar. Or sign up for any of TMA’s advanced training courses. The Modeling Agency will arm you with the tools you need to get great results for your business.

Solving Municipal Issues with Data Analytics

ChicagoEvery city faces problems and challenges. According to Information Week: Government, Chicago is beginning to turn to basic predictive analysis to solve some of those challenges.

They’re starting small, targeting the variables that lead to garbage cart thefts. The thefts create a surprisingly large drain on city finances.

Data analysis says that the thefts are more likely to occur in areas where alley lights are broken. City officials are responding by devoting resources to these repairs.

The new data analysis system is known as “Windy Grid,” and it’s still fairly simple. Mostly, it handles simple “cause-and-effect” tests on the results of Chicago’s data collection efforts.

However, the city is working to upgrade the system in order to make it a much more useful tool, one that could potentially help Chicago solve bigger problems.

“Developing a full-blown predictive analysis capability is much more ambitious. As envisioned, the system will flag for city leaders…indicators of coming problems including those that, unlike the out-of-commission street lights, they hadn’t considered.

The goal is to apply historical analysis to predict and prevent future problems. ‘We have the bones of this,’ Goldstein says, referring to Windy Grid. The next step is ‘taking it and saying if we’re seeing this in a given neighborhood, what’s likely to happen next?’

Goldstein’s team talks of ways to prevent graffiti, rodents, and garbage cart thefts. But what about Chicago’s more serious scourges, like its alarming homicide rate…or struggling schools?

Graffiti and rodents are mere starting points, says Brenna Berman, an ex-IBMer who’s now first deputy CIO. ‘This is the approach for how this department will be part of the answer for tackling the murder rate or addressing complex emergencies like snowstorms or improving the water infrastructure,’ she says. The harder-to-solve problems will take more data and analysis of more variables, but ‘it’s the exact same story for how you figure out which water mains are going to explode this year, so that we use our limited budget to improve the water infrastructure the right way over the next 10 years.’

Every organization faces challenges, even if few organizations find themselves tackling city-sized problems. The first step in making sense of data collection efforts is to receive the appropriate training. That’s why TMA offers data analytics training courses and a free webinar to help organizations make the most of these powerful capabilities.

Feel Free to Ignore Big Data in 2013

DataIn Inc.’s special report “How (and Where) to Make Money in 2013 (and Beyond)”, Erik Sherman presented 5 trends he feels you’d be wise to ignore in 2013. One of the trends he’s down on is big data.

If you’ve been paying attention to the news, you’ve likely seen the big data buzz. It’s everywhere. But the truth is, big data analytics is not practical data analytics that most businesses will need to employ regularly.

Big data is, as its name suggests, incredibly large. It could easily encompass millions or billions of data points. Sherman gives the excellent examples of Google searching for trends or machine-based weather prediction as practical big data applications. Unless either is in the scope of your business, don’t bother wasting time figuring out how to big data will help you.

Sherman eloquently says, “That level of data analysis is probably nowhere near what you need for your business. Most decisions are built on small data: dozens or hundreds or maybe thousands of data points. If you don’t have systems in place that let you regularly and predictably make effective use of the data you already have, then looking at big data is like saying you want to jump into the ocean to avoid getting damp from a summer shower.”

So what do you need? You need an understanding of data mining and predictive analytics, and how to put them to work for your company. If you are unfamiliar with either concept, see this definition and these practical examples of data mining. Data mining and predictive modeling can ensure you’re gaining actionable wisdom from your existing data.

To get started on the road to data mining and predictive analytics practice, register for a free one-hour webinar with The Modeling Agency. Ready for a more comprehensive education? Join The Modeling Agency for an in-depth training session.

Predictive Analytics Helps Businesses Get Better at Guessing

Predictive AnalyticsPredictive analytics – the use of data mining, machine learning and other techniques to look for patterns in data and make informed predictions – helps companies get better at guessing customer wants, needs and behaviors. In a recent article Jim Manzi of Applied Predictive Technologies explained predictive analytics helps companies get “about three percent better at guessing”. That may not seem like a large figure, and the effectiveness of predictive analytics depends on the size of the data and the scope of the project, but even 3% can certainly translate to a lot of cash in the right situation.

Predictive modeling allows companies in any industry to fine tune their sales efforts based on educated guesses what their customers will respond to best. “What we’re trying to do with predictive analytics is to get a little better at what you’re already doing,” said Manzi. “And so really our technologies could  in theory be used to build experiments and from that build models to say that a customer ID is more likely to respond to the following offer than another customer ID.”

Retail operations, banks, insurance agencies and the entertainment industry are just a few types of businesses that use data mining and predictive analytics to increase sales. For some practical examples of data mining, see this post on The Modeling Agency’s blog.

If you’re ready to learn more about how data mining and predictive analytics can work for your company, register for The Modeling Agency’s next free data mining webinar. Or for a more in-depth, hands-on examination, attend an upcoming data mining and predictive analytics training course.