How Analytics Could’ve Saved the Death Star and Become a Force for Your Business

How Companies are Disrupting their Industry View Analytics

This blog was originally published on inc.com.

Many in the tech world consider Dreamforce to be the must attend Big Data event of the year.

Put on by Salesforce, now in its 13th year, final attendance was over 170,000 people this year.

There is a reason attendees consider Dreamforce the place to be. The event offers a wealth of innovative ideas from its 2,700+ sessions. Being a marketer by trade, I wasn't going to miss Dun & Bradstreet CMO, Rishi Dave's session about analytics.

 

Dave, a huge Star Wars fan, summoned analogies and references to the iconic film series and other geeky sci-fi which made the presentation fun.

He started by comparing startup companies that are disrupting their industry to the Rebel Alliance in Star Wars, "a small band of rebels who were able to disrupt the most powerful force in the universe, The Empire. It was ultimately data that enabled the Rebel Alliance to detect the one flaw in the Death Star and develop and execute a plan to destroy it."

Only for startups, the seat of their "enemy" is not the Death Star, it's the Fortune 500.

Dave pointed out that since 2002, 50% of the Fortune 500 has vanished, which can in part be attributed to the innovative approaches taken by startups and their proper analysis of market data.

Anticipatory data can be a critical differentiator between being an innovator on the cutting edge of meeting customer demand and being completely disrupted.
Rishi Dave, Chief Marketing Officer, Dun & Bradstreet
 

When Fortune 500 companies fail it is partly due to a "Black Swan" event, which according to Dave is driven by, "arrogance, over-reliance on past events to predict the future, and not researching all the possible data that is available to them."

Dave is an advocate for using anticipatory analytics to enable companies to plan for the unthinkable and avoid a "Black Swan" of their own that could potentially derail the company.

 

With anticipatory analytics, predicting the future is no longer science fiction!

Anticipatory analytics build on predictive analytics which tells us to analyze many attributes over many years to make the best and most informed business decisions possible.

Dave made a clear distinction between companies that use anticipatory analytics versus those that rely solely on historical data. His take is that using anticipatory data can be a critical differentiator between being an innovator on the cutting edge of meeting customer demand and being completely disrupted.

Consuming data in real-time and leveraging it to build a model is what companies that are innovating and disrupting are doing. Companies that rely solely on historical data are most often the ones that fail, even after rising to greatness because their competitors are more effective at using data.

Subtle signals in data can be transformed into insights and uncover new ways to anticipate future business trajectory. Anticipatory data enables companies to analyze activity signals, behavior trends, event frequencies and changes in traditional data sources.

Four Key Things are Needed to Use Anticipatory Analytics:

  1. Faster Data Management: We now have the ability to consume data via cloud-based software in real-time. Whether it's web traffic or data from an online point of sale system, it can be accessed via cloud systems that have the capabilities of making the data available instantaneously.
  2. Merge the Past and Present: Old school analytics don't just disappear. There is still a need to look at the past to better understand what the real-time data is telling you.
  3. Processing Real-Time Signals: Companies need to have the ability to consume these real-time changes that are happening in their company database. They have the ability to identify behavior changes from the cloud or through the connections made across all their data sets and can act on them immediately.
  4. Perpetual Learning: Companies must continually improve their models based on real-time data and constantly learn from them. Organizations that stop learning eventually stop meeting customer demand.

In the past, companies looked at historical analytics as being the sole predictor, because they simply didn't have the technology to do anything else.

Anticipatory analysis uses predictive techniques but brings in real-time data. The past does not always predict where companies will go. Relying on old data to determine the future of a company usually leads to arrogance and complacency, which means the company's future will be in doubt.

Just look at the long list of Fortune 500 companies that were once mighty and seemingly invincible that are no longer here.

Dave left us with one final thought, "If your company is not using all the data and analytics available, you will be disrupted."

Catch Rishi's full Dreamforce anticipatory analytics presentation here.

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John White is the CMO and founder of Social Marketing Solutions. He is also a brand ambassador for beBee (a startup social-media site based on affinity networking with 11-million global users). John writes at the crossroads of social media, entrepreneurialism, startups, and marketing. John holds an MBA in marketing. He lives with his wife and two daughters in Fort Collins, Colorado. @juanblanco76

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