On Becoming an Analytical Innovator

This is part 7 of 10 from the 2013 Data & Analytics Global Executive Study and Research Project.


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. However, there is no specific plan in place to actively utilize the data and only a vague concept of why we need it. … In other words, no real plan. We are capturing data just in case.

Lack of Collaboration

If we do not improve on our collection, integration, analysis and productive use of information across data silos, we will destroy our business.

This quote from a survey respondent, an IT executive at a European bank, gets to the heart of another characteristic common among the Analytically Challenged: lack of collaboration across the organization. Silos have long been identified as a barrier to the use and management of information from both a data and a cultural standpoint. As companies have amassed more data from disparate sources, systems across organizations have emerged that are not always integrated. Different functional areas have built their own data stores, and IT departments have often been hamstrung in trying to keep up with it all. Another respondent said:

Too many nonintegrated silo systems is a huge problem for implementing better analysis and using the existing information as a competitive advantage.

Technology can improve, if not fix, the issue of data integration. However, more difficult to address are organizational silos spawned from a culture that lacks collaboration. One respondent in the Analytically Challenged group notably lays out sharp criticism of senior management:

I find the corporate political climate surrounding analytics to be one of smiling deception. Many EVP level managers … are threatened by analytics. I fear that self–interest … is the biggest hindrance. Organizational dynamics are always at the core of enterprise solution adoption. … I fear it probable that many officers may be shackled and apprehensive, caught on the sucker’s side of the Prisoner’s Dilemma.19

No Burning Platform

The fourth characteristic of Analytically Challenged companies is that they appear to have no key driver to use analytics — no real burning platform compelling them to make the foray into analytics, let alone to improve their data management. Without something threatening to spur them to action and leave the status quo, there will not likely be much change. As one Analytically Challenged survey respondent noted:

Everyone believes that if we’ve managed so far and so well without a robust strategic approach to data analytics, we can go on doing so in the future as well.

These companies are clearly change-resistant. A telling example: Only 13% of the Analytically Challenged strongly agree that their companies are open to approaches that challenge current practices, compared to 60% of Analytical Innovators who feel that way. Evidently, many Analytically Challenged organizations are feeling no pressure to do things differently. Another respondent from this group offered:

Unfortunately, the pain of declining profits and markets will have to take the lead before management will seriously look to analytics as a source of competitive advantage. No pain, no analytics seems to be the business model.

Supporting this notion is our finding that only 29% of the Analytically Challenged organizations indicate that analytics is a top-down mandate, compared to 55% of all other respondents. There is a case to be made that not only are these organizations analytically challenged but they are also analytically apathetic.

Moving Forward with Analytics

Analytics in the organization has a huge future. I’m very interested in where big data goes over the next few years. My organization doesn’t get it at this point; there are some pockets of the company where teams are pushing for increased analytics, but the C-suite doesn’t yet see the value.

This survey response seems to capture the attitude of many respondents in the Analytically Challenged group, who expressed general frustration with their organization’s view on data and analytics. The obstacles they face due to data deficiency, a weak information value chain, lack of collaboration and no burning platform are formidable.

Though it is unlikely that a company will progress from Analytically Challenged directly to being an Analytical Innovator, the data advocates in these organizations can help ignite change. The mission for the individual who wants to be an analytics catalyst: Lead analytics change by showing value.

We’ve identified three key issues stemming from the characteristics noted above that individuals can begin to address: technology latency, lack of collaboration and inertia.

Technology Latency.

The Analytically Challenged are stymied in their progress by core data issues, from upstream at the capture, quality, integration and access phases to downstream, where data is analyzed and disseminated. To address these areas, companies must invest in improved infrastructure, processes and technology skills. Wholesale change of these competencies across the organization is impossible without executive commitment to data. Therefore, improvement must start at the localized level.

Action items for the analytics catalyst: Identify a small but important issue that will benefit from the use of analytics. Use the resources that can be found in the organization and highlight what needs to be brought in from the outside. Find the internal geeks — those who are hungry for analytical work — and take a seat at their lunch table. Gather credible, timely and accurate data. Make use of the available analytical technology, and focus on identifying solutions to your issue that have a clear and measurable impact.

Lack of Collaboration.

The silos in the organization, whether built from data stores or management protectionism, are a major impediment to the effective use of information. Talk about breaking down these silos is not new. But enterprise-wide change in this arena could require a substantial information infrastructure investment, not to mention a dramatic culture shift. However, collaboration can start to occur at the individual level.

Action items for the analytics catalyst: Reach across the hall to those who have data that is important to addressing your issue. Enlist their help as partners in increasing the value of their data in decision making. Build ongoing relationships by including them in the process moving forward. Facilitate discussions among peers in different departments on bringing data together to address specific challenges. Give to get — share information of value to other departments to encourage reciprocity.

Inertia.

Unfortunately, Analytically Challenged organizations are constrained in their use of analytics by their executives’ unwillingness to change the status quo. These executives see no need for large investments in the infrastructure, systems and talent necessary to drive decisions with analytics because they believe that what they have been doing is working just fine. They are suspicious of data, particularly if it contradicts their intuition. So far, there has been no life-threatening event to their organization that has spurred thinking beyond the status quo. Outside of creating a burning platform to ignite a need for changes in decision making, those advocating the use of analytics simply must prove its value, one small win at a time.

Action items for the analytics catalyst: Develop an executive communication strategy for your analytics use case. To increase the credibility of the effort, engage your cross-sectional team to participate. Translate the analytical results into business insights and recommended actions. Show a clear ROI in terms of cost reduction, improved operations or increased revenue. Focus discussions on improving the business issue rather than on the method.

The Analytics Practitioners

The second and largest segment we identified through the survey responses is the Analytics Practitioners, which represent 60% of respondents. These companies have made significant progress in their analytics journey, and many are reaping strong benefits. However, the key metric that separates them from the Analytical Innovators is outcome. Recall that the Analytical Innovator group consists of those respondents who indicated that the use of analytics has provided a competitive advantage to a great extent and strongly agreed that analytics has helped them innovate. The Analytics Practitioners have not achieved this high level of competitive advantage and innovation from analytics. But they have matured well beyond the Analytically Challenged on their path to being data-driven. (See Figure 10: Analytics Practitioners Use Analytics more to Compete than Innovate.)

Figure 10: Analytics Practitioners Use Analytics More to Compete Than Innovate

View Exhibit

Analytics Practitioners have matured beyond the Analytically Challenged but are not yet close to Analytical Innovators.

Underpinning the differences between this large group and Analytical Innovators are three characteristics:

  1. Just-good-enough data
  2. Operational focus on analytics
  3. Fragmented analytics ecosystem

Just-Good-Enough Data

Unlike the Analytically Challenged, Analytics Practitioners have made significant advances in the area of access to useful data this past year, with a corresponding increase in their confidence about the data, likely stemming from improved accuracy and timeliness. As survey respondents noted:

Analytics are only as the good as the data. Best practices for data management, integration and governance are necessary for analytics to succeed. Otherwise, the adage “garbage in, garbage out” applies. Then analytics gets a bad name and decision making is done via management intuition rather than based on facts originating in the data.

We operate in extremely complex markets that are very difficult to model, so the reliability of the data, analysis or insights is often challenged by the decision makers. We still have a way to go.

Let’s be clear: This group still has room for improvement in terms of data proficiency. But Analytics Practitioners have achieved a level at which they are able to make use of their information to help run their businesses. In their own words:

Today, accessing data is not an issue, but the challenge lies in structuring the data, managing the data and making the data more usable, which will enable quicker decision making.

We have the data in pockets and currently manually piece a lot of it together, but have been making great progress in first aligning data so we speak the same language across the global operations, then connecting data, and finally creating dashboards and tools to provide the right data to the right people.

Operational Focus on Analytics

Analytics are mired in “automating the existing” rather than innovating a brighter performance future. It is a culture problem that will not be mitigated until a real leadership change occurs.

As this survey respondent points out, Analytics Practitioners tend to be focused more on day-to-day operational use of analytics, as opposed to using it to drive innovation and change the business. This is clearly supported by the survey results, which show that the top two uses of analytics among this group, similar to the Analytically Challenged, are reduction of enterprise costs and improvement in resource allocations. Compare these to the priority uses of the Analytical Innovators: making real-time decisions and increasing customer understanding. One Analytics Practitioner respondent noted:

We have to teach the enterprise to “behave” differently with data and move from a transactional to an insight mindset.

The balance of using analytics and intuition in key decisions is another example of the operational focus of Analytical Practitioners. In decisions in the areas of budget allocation, financial forecasts, supply chain management and allocating employees’ time, Analytics Practitioners and Analytical Innovators use a similar balance of intuition and analytics. However, for more strategic insights such as identifying target customers, enhancing customer experience and establishing strategy for the organization, Analytical Innovators are much more reliant on analytics than the Practitioners.

Fragmented Analytics Ecosystem

Analytics are HUGE in my company. … Until recently, though, it was held in the hands of very few people. To the point where we worried about the proverbial “what if they get hit by a bus” scenario. The past 12 months have been focused on integrating and trying to give data access to more people.

As seen in this comment, the third key differentiator of the Analytics Practitioner and their more analytics-savvy counterpart is their fragmented approach to the execution and use of analytics in the organization. Additional fragmentation is evidenced by differences in where companies are in their integration of information management and business analytics. While fully 85% of the Analytical Innovators indicate that an integrated approach is a core part of their business strategy, only 59% of the Analytics Practitioners report the same. One respondent’s view of the future of analytics emphasizes this point:

In the future, analytics will transition from simple information gatherers and maintainers to influential thought-leaders that are integrated parts of teams across the organization.

In the meantime, a pervasive issue still exists: ineffective dissemination of key insights to employees. We found that companies generally seem to struggle most with the dissemination of some components of the information value chain. This is quite definitely the weakest link for the Analytics Practitioners. One survey respondent from this group said:

The need internally is to have access to actionable insight with data at the right level of granularity — when it is needed.

What’s more, only 14% of Analytics Practitioners report increasing by “a great deal” their delivery of actionable insights to frontline employees over the past year, as compared to 35% of Analytical Innovators. That, coupled with the 16% of Analytical Practitioner organizations that “strongly agree” that their customer-facing employees have access to insights, gives rise to a sort of insight fragmentation — analytics is being conducted to drive decisions, but the results are not being shared among those who might be in the best positions to drive change. In the words of one respondent:

A data-driven decision culture is at its beginning of being developed across the organization. It will be effective only if it is being embraced at all levels and everyone is empowered to access it.

Moving Forward with Analytics

The current operational and tactical use of analytics by Analytics Practitioners is not unexpected for companies getting their feet wet in the use of analytics technology. Many companies have only recently made the foray into data-driven decisions and are still experiencing growing pains. It’s clear that, unlike some in the Analytically Challenged segment, these organizations do see value in information, and they are earnest in trying to use it to their advantage.

One Analytics Practitioner respondent noted:

Analytics are the essential tool in the toolbox. The analytics are not THE answer, but the analytics should inform us to reach or formulate the answer. A growing trend for our company is the ability to capture information from a wide range of sources, use standard metrics and analytics to glean some knowledge and then ensure that this knowledge is appropriately disseminated. This is a trend and a need within our company ... it is a work in progress.

This optimism about the use of analytics was strong among the Analytical Practitioner group. Unlike the general feeling of “we can’t” among the Analytically Challenged, this group showed a definite sentiment of “we’ll try.” The mission for analytics evangelists who want to step up their organization’s use of analytics: Expand analytics reliance by demonstrating strategic possibilities.

In order to develop the ability to “reimagine the possible” with game-changing insights, at least three issues must be addressed: due data diligence, dashboard dependence and denial of access.

Due Data Diligence.

A key differentiator between these organizations and those taking analytics to the next level is the data itself. It’s a matter of data quality, access and management. Analytical Innovators are leading the charge in tapping new sources of data. Analytics Practitioners should take note and learn from them.

Action items for the analytics evangelist: Conduct a data audit. Do a quality check on the data you are using to drive decisions. How long have you been using the same data sources? Identify gaps in what you have and what you need, and consider how data from unconventional sources (e.g., social media) might provide a new perspective on your business.

Dashboard Dependence.

Business intelligence technologies brought the ability to watch day-to-day operations on bright and shiny dashboards and monitor actual results against KPIs. But what’s hot now is the ability to predict what’s going to happen and to find patterns in data that lead to not-so-obvious conclusions. Analytics Practitioners who want to step beyond the tactical and operational uses of their data need to sharpen their analytical skills and cast a net for analytics talent. If you are going to make the move to Innovator, be prepared to invest.

Action items for the analytics evangelist: Take stock of your own analytical prowess. Do you or your staff have the right skills to employ sophisticated analytical techniques? Search for talent that combines an understanding of your business with a passion for data exploration and technical skills.

Denial of Access.

To help drive innovation, Analytics Practitioners must do a better job at disseminating key insights to the right people at the right time. Analytics should be approachable — easy to access, simple and intuitive – in order to spur innovation from all levels in the organization. As one respondent said, “Analytics must be in the DNA of every empowered employee.”

Action items for the analytics evangelist: Take stock of your organization’s information access and distribution. Are employees stifled in their jobs because they don’t have the appropriate information to make decisions? Connect with peers about information dissemination, and developing strategies that help empower workers with insight.

References

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.