People Are Key To Predictive Analytics

I recently wrote about remarks from General Colin PowellScott Hudgins from Disney and Orlando Magic’s Alex Martins who spoke at The Premier Business Leadership Series sponsored by SAS. Here are some additional tidbits that I found interesting throughout the event:

  • Paula Puleo, SVP and CMO of Michaels Stores, talked about how the retailer is “living its brand” and “putting Michaels’ brand into the hands of its customers.” She describes that the company used to “shout at customers” with Sunday circulars but have been building more of a dialogue with customers and employees over the previous 18 months. When she discussed the redesign of the frame section in the stores, she described the goal as: We help preserve the cherished moments of our clients. I am planning to interview Puleo and provide more details on the work that she’s doing in a future blog post.
  • Tim Belk, Chairman and CEO of Belk, shared these comments: “If you’re going to build your brand, you need to invest in your people” and “You need to make associates happy if you want your customers to be happy.”
  • Matt Cappio, SVP of Marketing Strategies at Bank of America, explained how the bank is using analytics to understand what’s most relevant to the customer and beneficial to the bank. It can identify offers that meet certain goals in ares like revenues and credit risk. It’s not just about having the technology spit out an offer. Cappio said: “We need to win our associate over as to the value of the offer or we will have a crisis of confidence.”
  • Jim Goodnight, CEO of SAS, discussed how massively parallel in-memory processing allows companies to do analysis on ALL of their data, quickly. Jim Davis, SVP and CMO of SAS, discussed a scenario where SAS reduced the time to complete a marketing optimization for a European telco from 8 hours to 2 minutes and 17 seconds.
  • Halina Karachuk, VP of Innovation, Research and Analytics at AXA Equitable, talked about “mining for diamonds” which is a process where they analyze their advisors’ book of business (client and product information) and identify the “next-best offer” for each household.
  • Eric Webster, VP of Marketing at State Farm Insurance, explained that the most important question for a life insurance underwriter is “are you a smoker?” It’s so important that insurers insist on a medical exam to validate this answer. State Farm is starting to use predictive models to reduce the number of medical exams; only using this expensive and time-consuming step when it’s most required.
  • Best selling author Jim Collins also spoke at the event. His core message was that great leaders wrap three attributes around their ambition: Fanatic discipline, empirical creativity, and productive paranoia. Collins’ analysis showed that great leaders and companies aren’t just lucky. He researched more than 200 “luck events,” which are situations that: are independent of your actions, have significant consequences, and are unpredictable.  It turns out that great companies aren’t differentiated by their good luck, but by their ability to deal with all of the luck events they run into — good or bad. Collins described this as their return on luck.

There’s a lot of different stuff going on in this post. Is there anything that connects all of these elements besides a conference center in Orlando? I’ll give a shot at wrapping it all together:

Predictive analytics will increasingly put deep insights into the hands of people at the point in time when they make decisions. But this won’t have a significant impact on companies unless they use the insights to identify value for customers and engage employees in designing new processes. This combination of left brain analysis and right brain human engagement will help companies more nimbly respond to rapidly changing environments full of both good and bad luck.

The bottom line: Powerful analytics is necessary but not sufficient for successful analytics

About Bruce Temkin
I am a customer experience transformist, helping large organizations improve business results by changing how they deal with customers. As part of this focus, I examine strategy, marketing, interaction design, customer service, and leadership practices. I am also a fanatical student of business, so this blog provides an outlet for sharing insights from my ongoing educational journey. Simply put, I am passionate about spotting emerging best practices and helping companies master them. And, as many people know, I love to speak about these topics in almost any forum. My “title” is Managing Partner of the Temkin Group, a customer experience research and consulting firm that helps organizations become more customer-centric. Our goal is simple: accelerate the path to delighting customers. I am also the co-founder and chair of the Customer Experience Professionals Association (CXPA.org), a non-profit organization dedicated to the success of CX professionals.

2 Responses to People Are Key To Predictive Analytics

  1. Wilson Raj says:

    Powerful summation of the event, Bruce. But what’s more compelling is your wrap-up. The powerful technology is certainly essential. But, the other critical parts have to fall in place as well as you mentioned: people and processes.

    I might also venture to add another dimension: culture. How can a business instill a sense of insight-driven decision making that pervades the entire corporate culture? The fundamental value of analytics and how it can benefit companies has to be championed at the leadership and board levels. The examples you cited are encouraging in that each company is working toward creating a culture that values deep insights and analytics as a necessity for their business advantage

    Appreciate your post!

    • Bruce Temkin says:

      Hi Wilson: Thanks for the comment. Things have been so crazy for me that I’m far behind in my response. I do a lot of work with companies on culture change, but I’m not sure you need large-scale culture change for predictive analytics to grow. I think a lot of senior people will adopt predictive analytics when they see easy-to-understand use cases with compelling results. In other words, I don’t think there’s resistance built up because of some pre-dosposition NOT to use these analytics, just a lack of understanding about how, where, and when to use them. I’m challenging all of the vendors in the field (including SAS) to develop compelling, easy-to-understand (for business execs) use-cases. Since I think that predictive analytics is a key capability for future CX efforts, I will also try and help my clients and readers to figure out how to tap into this important capability.

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