Who can keep up with all the ‘gotta read’ content in the dynamic Customer Experience space? That’s why each month we curate for you some of the most socially shared articles along with a little Clear Peak perspective.
“…firms have defaulted to leveraging big data in exactly the same way they previously used small data: for reporting and business intelligence… It’s easy to see why this approach hasn’t quite delivered on the big data promise… Big businesses have absorbed Google-style tech, but are only just beginning to adopt Google-style thinking alongside it.”
The hardest part about moving to big-data is thinking differently. I see so many organizations put in a big data environment and build the same cube-style reports they were limited to back in the data-warehouse days. For organizations to really evolve, they need to bring in talent who have worked in pure-play big data environments. You have to be in that type of environment for a period of time before you can start thinking differently.
“Presumably, firms are investing in big data infrastructure because they believe that it offers a positive return on investment. However, looking at the surveys and consulting reports, it is unclear what the precise use cases are that will drive this positive ROI from big data.”
“Big data is less about size and more about introducing fundamentally new information to prediction and decision processes”.
Harvard Business Review highlights three excellent areas where predictive analytics is having major impact: Demand Forecasting, Pricing, and Predictive maintenance – but I’m surprised they missed what is probably the biggest impact area: Predictive Marketing. Customer Lifetime Value, Churn, Cross-sell and up-sell are sweet-spots for predictive analytics and are making massive impact today.
“In health care, predictive analytics are used to identify leading indicators of disease, spot patient trends, and help health care providers establish effective treatments. And as the health care industry embraces precision medicine to provide customized treatment, it will need to adopt more precise predictive models to identify high-risk patients and tailor interventions to meet their needs.”
Multiple Industries are using algorithms to better understand people. Retail is working on predicting how people will behave when given a choice. Marketing is using data science to figure out how people will behave when given a message. Health Care is working on predicting disease.
The real power will be when these three groups of data scientists come together: Choice + Message + Health. We’re all focusing on people, after all.
“CFO turnover rates at retailers have outpaced all industries in the last two years. As a result, the job description of a retail CFO has changed.”
Skills that aren’t traditionally part of the CFO toolkit — such as coming up with big-picture strategy, operating stores and websites, and parsing customer data — are also becoming more important, according to Bryan Proctor, who leads Korn/Ferry’s financial officer practice.
This article is a few months old, but in the light of last week’s news, it’s even more relevant. It’s interesting – in the 1990s, the CFO office was one of the most analytic areas in a retail organization when they owned all the Excel expertise. Then, there was an analytic revolution ~2000 – 2010 where the merchants began getting access to new analytic and predictive tools – and they became the most analytic group. In the past few years, Marketing is up-tooling with the new Machine Learning and 1:1 capabilities, bringing them the sophistication.
With all the new CFO turnover, I predict the next analytic revolution will be with the Financial group, as they catch up and regain control of analytics within the retail organization.
“When you promote, you must promote with purpose, and that purpose can’t simply be to “drive revenue.””
This is a recent post of mine that’s getting a lot traction. I hope you enjoy it.
“Shifting from a product focused company to a customer-aligned organization changes how a company must operate… Companies are competing against their customers’ expectations created by digital forward companies, as well as with their competitors.”
The move from a Product-Centric to Customer-Centricity is difficult. This article sums it nicely into three hurdles: Culture, Data, Operations. I see a lot of organizations that start and end with data, ignoring the importance of Culture and Operations. The article also shines a spotlight on the importance of ROI. I take that a step further and believe the transformation must have the Customer and ROI built into the core.
Thanks for reading. Look for more suggested reads in July.