10 Ways Not to Build an Analytics-based Business

Thomas Davenport published an article in Harvard Business Review entitled "Competing on Analytics." He concludes the article with a checklist of ten key points he feels are important to creating a analytics-based business.

We disagree with quite a few of these points and even where we agree, we want add real-world nuance.

The challenge of analytics is communication and creating a shared understanding. It's about focusing on high impact areas, moving forward one step at a time, being skeptical, being creative, searching for the truth. Any company can compete on analytics, and you certainly don't need to satisfy a checklist to do so.

Here's Davenport's checklist, with Juice commentary. We're putting together a list of practical steps anyone can take.

1. You apply sophisticated information systems and rigorous analysis not only to your core capability but also to a range of functions as varied as marketing and human resources.

Analytics is hard. Analytics takes resources. It takes effort for an organization to create and assimilate learnings from analytics. You need to focus your analytics at the key leverage points of your business. As Davenport points out in the HBR article, UPS focuses their analytics on knowing where packages are, Marriott focuses on revenue management. If you try to do everything, you won't do anything well.

2. Your senior executive team not only recognizes the importance of analytics capabilities but also makes their development and maintenance a primary focus.

Of course analytics are good. But so is branding, innovation, operational excellence, customer focus. Companies are defined by what they don't do just as much as what they do. If you're going to make analytics a primary focus, you will need to make sacrifices elsewhere. Which of the above are you willing to de-emphasize?

Capital One, oft cited as the credit card king of analytics, aren't customer service champions nor are they particularly innovative.

3. You treat fact-based decision making not only as a best practice but also as a part of the culture that’s constantly emphasized and communicated by senior executives.

This is hard to argue with. However, it's easier said than done. In our experience, getting to a culture of decision making requires your business to have real, solid wins using analytics to make people care from top to bottom.

4. You hire not only people with analytical skills but a lot of people with the very best analytical skills—and consider them a key to your success.

The problems raised by the Mythical Man Month apply to analytics. Just as doubling the number of programmers on a project won't halve the time it takes to complete a project, doubling the number of analysts won't make your company twice as smart.

What you need are well placed and versatile analysts - analysts that are in constant communication and debate with key decision makers.

5. You not only employ analytics in almost every function and department but also consider it so strategically important that you manage it at the enterprise level.

What does this mean?

One thought: This refers to having a Chief (Analytics|Knowledge|Data) Officer. This may be a good idea. Here's an interesting interview with Usama Fayyed, Yahoo's Chief Data Officer about the value of having a chief data herder at a data intensive company.

If, on the other hand, this means centralizing analytics and building a single data warehouse, we disagree. For most companies, building a big "atomic baloney slicer" for analytics is not going to work out. These approaches take too long, are inflexible, and don't adapt to your business.

6. You not only are expert at number crunching but also invent proprietary metrics for use in key business processes.

Why is "proprietary" a good thing? What you do want is to develop a few metrics which are core to the success of your business. If you are in a well established industry, it's likely those metrics have been defined and are well understood. There's a lot of value in well understood metrics that everyone in your business understands. The challenge with analytics is communication and creating a shared understanding.

7. You not only use copious data and in-house analysis but also share them with customers and suppliers.

Insight is not measured by volume. As for sharing with customers and suppliers, it's a rare company that has evolved that far (e.g. Toyota). Focus analytics where you have the most leverage to change your business.

8. You not only avidly consume data but also seize every opportunity to generate information, creating a “test and learn” culture based on numerous small experiments.

There's lots of ways to build insight from data. It can be test and learn, it can be customer visualization, it can be scoring systems.

9. You not only have committed to competing on analytics but also have been building your capabilities for several years.

Yes. Analytics is a learning process - a journey, not a destination. The best companies have been working on learning for a long time. You can compete on analytics without having worked on it for years. Just get started.

10. You not only emphasize the importance of analytics internally but also make quantitative capabilities part of your company’s story, to be shared in the annual report and in discussions with financial analysts.

You risk hypocricy if you follow this advice. Culture starts with internal stories. External stories will arise naturally and organically from internal stories. If you focus on external stories the best you can hope for is to find yourself in a Harvard Business Review article.

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. All source code is released under a BSD License unless otherwise specified.

10 comments | Show all comments only the last 5 are shown


May 4, 2006
Priya said:

At the end of the day, Analytics is "decision support" function. It can only SUPPORT decisions/ not support them on the basis of data. While one can find "Insights" hidden in numbers, its not simple to find them - as it is critical for an analyst to also understand the market reality like a sales/ marketing person does. Putting together the jigsaw pieces is a function of numbers+gut-feel+ pulse of my customer (which comes from my front end teams).


May 8, 2006
Zach said:

I agree with the notion of analytics is a part of a jigsaw puzzle as we try to piece together reality. And there are definitely limitations in the ability to drive decision-making through data.

That said, I'm a little uncomfortable with the notion of "decision-support" function. I think most companies place analytics out to the side as a separate shared service to inform decisions -- then are happy to disregard the data when it contradicts their "gut-feel" or "pulse of the customer." We have run into many instances where those gut-feels are really just deeply ingrained and untested assumptions about how the business works. Faulty assumptions can become a crutch that decision-makers lean on way too much.


October 14, 2006
Ajay Kelkar said:

This is a fascinating discussion. As an executive who is in the thick of trying to make analytics happen in a leading Indian bank ,I can empathize with almost all the comments being made. My only addition would be that in my view,to truly drive this capability ,you need to invest serious $ in Change management. Without changes in process,incentive and structures..competing in analytics would be an impossible hurdle!!


December 12, 2006
» What about the (Analysis) Grunts? - Juice Analytics said:

[...] Meanwhile, Davenport minion Jim Novo responded to our criticism by stating: “if a silo wants to keep an analytical “lead” in it’s own little box to do the navel-gazing, silo-focused analysis that impacts it’s own little box, then that’s OK. Just know that this analysis, while meaningful to the little box, cannot be used or trusted anywhere else in the company and so is of very little value in a macro way. But it’s safe; the silo can proceed with the $10 “micro tweaks” and have full accountability while the competition is making macro process changes worth millions using centralized analytics.” [...]


February 8, 2007
Competing on Analytics Webinar with Tom Davenport today at 1:00 PM EST | Open Source Analytics said:

[...] Tom’s HBR article titled “Competing on Analytics” is based on his profiling of early adopters of Analytics that compete today based on data driven strategies. The research is also expected to be published in a book format in spring 2007. Tom’s article led to a fairly strong debate in the blogger community. Some see it as learning from the successful experiences, while others point out that while it may be true for the organizations that have been doing analytics for long, it may not factor in some other realities. You can see some of the interesting discussions here: Juice Analytics: 10 Ways Not to Build an Analytics-based Business, Juice Analytics: The Heart of the “Competing on Analytics” Matter, and Neil Raden: Power to the People: Analytics for the Masses. [...]

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