Analyze This!: Standardized analytical solutions
Expect to see more and more models and analyses based on mathematical and/or statistical techniques embedded in packaged (rather than custom) software applications. Moreover, this packaged software is likely to cost far, far less than a custom solution crafted by an analytic professional.
By ay Mehrotra
So the mainstream media have picked up on this analytics thing big time. The latest “hit” is a recent article in the New York Times that cites a recent study by the McKinsey Global Institute entitled, “Big data: the next frontier for innovation, competition, and productivity.” The McKinsey report is full of Saganesque prose (“billions and billions of dollars in savings possible as a result of harnessing the information embedded in the big data sets of today and tomorrow”), highlighting several industries and functional areas that its authors believe are ripe for large-scale application of the data, models and analyses that we all know and love.
Another prominent feature of this report is its stern warning about potential labor shortages for analytics professionals. Specifically, the authors project a shortfall of 140,000 to 190,000 folks with “deep analytical skills” by the year 2018. In addition, for the same timeframe these authors forecast a shortage of 1.5 million managers and analysts needed to “analyze big data and make decisions based on their findings.”
Similarly, in their book “Analytics at Work: Smarter Decisions, Better Results,” Davenport, Harris and Morison also make prominent mention of a potential shortage of analytical talent.
How will this resolve itself? Well, Davenport and his co-authors argue that skilled analytics resources from emerging markets will be tapped to bridge this talent gap, and there is certainly significant evidence of that already. But we can also expect to see more and more models and analyses based on mathematical and/or statistical techniques embedded in packaged (rather than custom) software applications. Moreover, this packaged software is likely to cost far, far less than a custom solution crafted by an analytic professional.
Early in my consulting career, I had bumped into this phenomenon. With great excitement, my colleagues and I presented our client with our “new” idea about combining call forecasts, queueing equations and optimization models to create call center agent schedules, only to be told that this had already been done by several software vendors in something called a “Workforce Management System.” Much later in my career, I directed a large team of consultants who did a large number of (lower priced) deployments of packaged analytic software and a smaller number of advanced (higher priced) consulting projects based on these types of packaged solutions.
I was reminded of this again recently, when I learned about a partnership between the Waypoint Group (www.waypointgroup.org) and WorldApp (www.worldapp.com). The Waypoint Group is a boutique consulting company whose core value proposition to customers is based on its ability to help clients assess and improve customer loyalty, with a deep competency in leveraging the “Net Promoter” framework. Much of Waypoint’s work involves capturing data from a client’s customers, interpreting the information that can be gleaned from this data, and providing clients with recommendations and priorities. Client projects typically include analyses chock full of correlations, conditional probabilities and multiple regression models. (Full disclosure: I have done some data analysis for the Waypoint Group in the past).
WorldApp, meanwhile, is a software company with a sophisticated platform for Web-based data collection and reporting. Though WorldApp’s clients use its technology to gather data from employees, partners and customers, the company does not claim to have any particular business domain knowledge. Instead, WorldApp’s key strengths are in its scalable, hosted platform for creating surveys and summarizing results.
The tagline on the product’s Web site (www.promoterpro.com) succinctly explains why this deal makes sense for WorldApp: “Survey software alone doesn’t work.” By partnering with Waypoint, it now has a tailored solution that can help a company to quickly answer a large class of business questions.
For Waypoint, however, the partnership seems is riskier. The PromotorPro offering will be considerably cheaper than a standard introductory custom project delivered by Waypoint, and as such there is certainly some fear of cannibalization. In addition, although there will almost surely be some sales effort required from Waypoint in order to sell the PromotorPro offering, Waypoint will be obligated share the revenue earned from these sales with its partner WorldApp.
Waypoint’s founder and CEO Steve Bernstein clearly considered these issues before launching this partnership. “Our biggest challenge with clients is getting them to commit to examine customer loyalty in a disciplined way,” Bernstein explained to me. “Having PromotorPro as a lower cost starting point will help us get more companies into the game — and after that we’re confident that many will find more than enough value to keep us busy and growing with more advanced projects.” This reasoning may indeed reflect classical economic theory , but Bernstein’s acknowledgement of this potential for creative destruction is bold and forward thinking for a professional services company.
The PromotorPro story also suggests that the projected shortage of analytic talent may lead to a great many analytics-based solutions that are codified in (relatively) inexpensive packaged software applications. Our hope is that this “productization” of basic analytic solutions does indeed create more opportunities for more sophisticated analytic work that creates significantly more business value.
My sense is that in some situations a need for more complex analytics needs will arise naturally. In others, however, the bulk of the business value will be captured by a well-designed standard software solution — and we can expect that potential customers will be quick to figure this out. As strategy guru Gary Hamel is reputedly fond of pointing out, “If customer ignorance is a profit center for you, you’re in trouble” .
Vijay Mehrotra (firstname.lastname@example.org) is an associate professor, Department of Finance and Quantitative Analytics, School of Business and Professional Studies, University of San Francisco. He is also an experienced analytics consultant and entrepreneur and an angel investor in several successful analytics companies.
- N. Gregory Mankiw, former chairman of President George W. Bush’s Council of Economic Advisors, had similar economic theory in mind when he said, “I think outsourcing is a growing phenomenon, but it’s something that we should realize is probably a plus for the economy in the long run” — and this politically damaging comment quickly led to his forced resignation.
- Colvin, G, “Talent is Overrated,” New York: Penguin Group, 2008, p. 11.
- 54May/June 2013 Many collect data, few know what to do with it. The core skill business professionals need to know. By Piyanka Jain McKinsey’s Big Data report, published in May 2011, lists a shortage of talent in the big data space. Interestingly, the shortage of big data business professionals (1.5…
- 44Organizations of all sizes and types are awash in data possibilities, yet most of them cannot capitalize on the potential for a variety of reasons. The good news, however, is that with the right decisions and focus, these possibilities can turn quickly into realized opportunities.
- 43Cathy O’Neil’s provocative book, “Weapons of Math Destruction: How big data increases inequality and threatens democracy,” created quite a stir in the analytics community when it was released last fall.
- 43May/June 2014 Big data is a hot topic, but harnessing its full potential can be elusive. By Alex Romanenko (left) and Alex Artamonov Big data is generating a powerful buzz. For firms that know how to harness it, big data can offer a significant competitive advantage. However, much of the…
- 42What a difference a few years make. It wasn't that long ago that business analysts and mathematical modelers were moaning about the lack of data with which to construct their models in order to better inform their decision-making clients. Now, the corporate world (and every other world you may live,…