On Becoming an Analytical Innovator

In the previous section, we examined the flagship characteristics of the Analytical Innovators. In this section we examine the remaining companies — the Analytically Challenged and the Analytical Practitioners — and what these organizations can do to become more like Analytical Innovators.

The Analytically Challenged

The Analytically Challenged, 29% of our survey respondents, are less mature in their use of analytics and have not been able to derive as much value from them as the other groups.18 Few have achieved a competitive advantage with analytics, and even fewer have benefitted in the area of innovation. This is a stark difference compared to all other survey respondents, most of whom are deriving some competitive advantage and are using data to innovate. (See Figure 9: Analytically Challenged Report Fewer Benefits from Analytics.)

Analytically Challenged organizations have four distinct characteristics that separate them from their more analytically advanced peers:

  1. Data deficiency
  2. Weak information value chain
  3. Lack of collaboration
  4. No burning platform
Figure 9: Analytically Challenged Report Fewer Benefits From Analytics

View Exhibit

Analytics is not on the executive agenda in Analytically Challenged organizations.

Data Deficiency

Analytically Challenged companies are distinguished by the state of their data and what they are (or aren’t) doing with it. Unlike other companies, this group has generally not capitalized on big data trends, and their data management abilities are lagging.

One survey respondent in the Analytically Challenged category noted:

Analytics are only meaningful if the quality of the underlying data is unassailable. Until there is sufficient attention paid to data governance and quality assurance, analytics will remain little more than a lofty goal.

Data issues are a nonstarter for the effective use of analytics. If the data the organization is using isn’t at least reliable, accurate, timely and adequate, the results of analytics will be meaningless. And upstream, senior managers who prefer to drive decisions on their intuition will have cause to be skeptical.

Weak Information Value Chain

Another defining characteristic of the Analytically Challenged is their ineffectiveness at the analytics tasks that make up the information value chain, particularly compared to other organizations. Fewer than half (42%) of the respondents in this category report being effective at capturing information, and the capabilities in other areas are even weaker, with information dissemination at a markedly low 21%. According to one respondent:

We are collecting mass quantities of data.


1.The New Initiative on the Digital Economy,” press release, MIT Sloan School of Management, n.d.

2. P.C. Evans and M. Annunziata, “Industrial Internet: Pushing the Boundaries of Minds and Machines,” GE Reports, November 26, 2012.

3. Evans, “Industrial Internet.”

4. R. Bean and D. Kiron, “Organizational Alignment Is Key to Big Data Success,” January 28, 2013.

5.Governor Patrick Announces New Initiative to Strengthen Massachusetts’ Position as a World Leader in Big Data,” press release, Commonwealth of Massachusetts, May 30, 2012.

6. ”Governor Patrick Announces New Initiative.”

7. A. Pentland, “Reinventing Society in the Wake of Big Data,” August 30, 2012.

8. Tweeted by Joel Cherkis on 10/21/12.

9. J. Manyika, M. Chui, et. al, “Big Data: The Next Frontier for Innovation, Competition and Productivity,” May 2011.

10. Capgemini Consulting and MIT Center for Digital Business, “The Digital Advantage: How Digital Leaders Outperform Their Peers in Every Industry,” November 5, 2012.

11. E. Brynjolfsson and A. McAfee,“Big Data, The Management Revolution,” Harvard Business Review 90 (October 2012): 61-67.

12. T.H. Davenport and J.G. Harris, “Competing on Analytics: The New Science of Winning” (Cambridge, MA: Harvard Business School Press, 2007).

13. M. Lewis, “Moneyball: The Art of Winning an Unfair Game” (New York: W.W. Norton, 2004).

14. L. Melnick, "Moneyball Strikes Again: How to Use Analytics for Sustained Competitive Advantage,” October 3, 2012.

15. The two questions were:

(a) To what extent does information and business analytics create a competitive advantage for your organization within its industry or markets?

(b) To what extent do you agree with the following statement? Analytics has helped improve my organization’s ability to innovate.

Managers that checked “great extent” for both questions were placed in the Analytical Innovators category.

16. T.H. Davenport and D.J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review 90 (October 2012): 70-76.

17. “Chief Consumer Advocate: How Social Data Elevates CMOs,” white paper, Bazaarvoice and the CMO Club, Austin, TX, July 25, 2012.

18. Respondents in Analytically Challenged companies differ demographically in subtle but important ways from other survey participants. They tend to be in less senior management positions and have a slightly higher likelihood than other survey participants to work in operational functions. These demographic differences might be a contributing factor to their evaluations of their organizations as less analytically mature.

19. The prisoner’s dilemma refers to a non-zero-sum game that shows why two people may choose to betray each other even if cooperation is in their best interest. It’s based on the premise that two isolated prisoners involved in the same crime have the independent opportunity to either collaborate with each other by remaining silent or sell the other prisoner out. Each combination of possibilities results in a different outcome, with the best for both stemming from cooperation. The sucker’s side is the prisoner who remains silent but is betrayed by the other prisoner.

i. K.T. Greenfeld, “Loveman Plays ‘Purely Empirical’ Game as Harrah’s CEO,” August 6, 2010.