In a recent webinar, editors from MIT SMR and SAS’s Chief Research Officer outlined three stages of analytical effectiveness, and offered concrete steps on how to improve a company’s analytical capabilities.
In mid-March my colleagues David Kiron, Executive Editor at MIT Sloan Management Review, Pamela Kirk Prentice, Research Director at SAS Institute, and I conducted a webinar discussing the findings of our recent research report, From Value to Vision: Reimagining the Possible with Data Analytics
In the webinar we outlined three distinct levels of analytical sophistication that emerged in the course of our research — Analytically Challenged, Analytical Practitioners and Analytical Innovators — and outlined a path to how your organization can move from one stage to the next. A quick recap of the stages:
- The Analytically Challenged, 29% of our survey respondents, are the least mature in their use of analytics. Few have achieved a competitive advantage with analytics, and even fewer have benefited in the area of innovation.
- Analytical Practitioners, which represent 60% of our respondents, have made significant progress in their analytics journey. However, this group has not achieved a high level of competitive advantage and innovation from the use of analytics.
- Analytical Innovators, 11% of our survey respondents, use analytics to gain a competitive advantage and to innovate.
As the hour-long webinar came to a close, we found that there were far more questions than we had time to answer, and far too many intriguing questions to leave unaddressed. Here are a few responses to some of the many terrific questions posted during the March 14 webinar (we’ll start with the basics first).
What is the working definition for “analytics”?
In our report, the term “analytics” refers to the use of data and related business insights developed through applied analytical disciplines (e.g., statistical, contextual, quantitative, predictive, cognitive and other models) to drive fact-based planning, decisions, execution, management, measurement and learning.
Which industries participated in the survey?
More than 2,500 business executives, managers and analysts responded to our survey conducted last summer. They hailed from organizations located around the world, with individuals located in 122 countries and more than 30 industries. We also conducted 29 qualitative interviews with leading industry executives, technology developers and academics representing a variety of industries.
The top ten industries with the most survey respondents included: IT & technology, professional services, manufacturing, energy and natural resources, financial services, government/public sector, retail, consumer goods, aerospace & defense, and healthcare services.
Are the analytics “champions” primarily CIOs, or did you find champions across functional groups at the C-suite level?
CIOs are not the only analytics champions. If there is a top-down mandate, it generally starts with the CEO (and needs to, to successfully change the culture of the organization). In our report and elsewhere, we discuss how the CEOs of Oberweis Dairy, LinkedIn and Match.com have played a pivotal role in championing analytics. We have also noted that chief marketing officers and a relatively new group of chief digital officers are becoming analytics evangelists within many organizations.
During your research, what did you find to be the bottlenecks most companies face in the use of analytics?
There seem to be two main bottlenecks that companies face in their use of analytics: technological and cultural. On the technology side, issues can range from the need to ramp up infrastructure to meet “big data” demands, with hard choices often having to be made between making data available (including even the allocation of processing power to facilitate analytics computation) versus managing data storage costs. There are also data governance and data readiness issues to deal with.
On the cultural front, there can be a number of bottlenecks to contend with, from data that is trapped in departmental silos, to an executive team that does not see the value in data.
What are the key business areas where analytics is delivering value?
We asked organizations: “To what extent has analytics helped improve your organization’s ability to innovate?” in regard to a number of departments. Their answers shed some light on this question.
- Asked about its impact on Marketing, 57% of Analytical Innovators responded “a great extent,” versus 20% of Analytical Practitioners and 4% of Analytically Challenged.
- Asked about its impact on Operations, 36% of Analytical Innovators responded “a great extent,” versus 18% of Analytical Practitioners and 4% of Analytically Challenged.
- Asked about its impact on Finance, 36% of Analytical Innovators responded “a great extent,” versus 18% of Analytical Practitioners and 4% of Analytically Challenged.
- Asked about its impact on Human Resources, 22% of Analytical Innovators responded “a great extent,” versus 18% of Analytical Practitioners and 1% of Analytically Challenged.
- Asked about its impact on Product Development, 56% of Analytical Innovators responded “a great extent,” versus 17% of Analytical Practitioners and 4% of Analytically Challenged.
Which companies disagreed that analytics helps their companies innovate and why?
The nature of our survey requires that respondents remain anonymous, so we cannot say specifically which organizations disagreed that analytics helped their companies to innovate. Broadly speaking, Analytically Challenged organizations have the most difficulty with innovation. In our survey, 45% of Analytically Challenged “strongly disagreed” or “somewhat disagreed” with the statement, “Analytics helps my organization to innovate.” In contrast, not a single Analytical Practitioner or Analytical Innovator “disagreed” that analytics enabled their organization to innovate.
To get a sense of which departments are not able to innovate with analytics, it’s useful to look at who disagreed that analytics enables their organization to innovate, by department:
- In Marketing departments, 46% of Analytically Challenged responded “not at all” or “a small extent,” versus 14% of Analytically Challenged and 8% of Analytical Practitioners.
- In Operations, 35% of Analytically Challenged responded “not at all” or “a small extent,” versus 9% of Analytical Practitioners, and 3% of Analytical Practitioners.
- In Finance, 38% of Analytically Challenged responded “not at all” or “a small extent,” versus 14% of Analytical Practitioners and 8% of Analytical Innovators.
- In Human Resources, 58% of Analytically Challenged responded “not at all” or “a small extent,” versus 30% of Analytical Practitioners and 20% of Analytical Innovators.
- In Product Development, 47% of Analytically Challenged responded “not at all” or “a small extent,” versus 14% of Analytical Practitioners and 6% of Analytical Innovators.
If upper management is not well versed in analytics, which department should lead the charge in moving from analytically challenged to analytical innovators?
We don’t recommend one department over another to lead the charge in moving from one stage of analytical sophistication to the next. Rather, it’s best to find those departments — or individuals — that have an interest in, and/or are utilizing or excelling in the use analytics, and align with them in an effort to share data and create analytics wins. Small wins, we’ve found, add up quickly in an organization.
Interestingly, when we asked the question, “Where do analytics projects typically start in your organization,” four areas consistently bubbled to the top across all respondents: Line of business that is not marketing or IT (30%); C-suite (21%); Marketing (19%); and IT (14%).
How do you suggest starting with analytics?
In our report — and in our webcast — we’ve identified several ways to overcome key hurdles common to Analytically Challenged and Analytical Practitioner organizations.
We’ve found that Analytically Challenged organizations have four distinct characteristics that separate them from their more analytically advanced peers: a data deficiency, weak information value chain, lack of collaboration, and no burning platform to move an analytics agenda forward.
To address these issues, start small. The information value chain — the capture, quality, integration and access of data on one and, and the analysis and dissemination of data on the other end — is an important first step. To move forward, it is essential to invest in improved infrastructure, processes and technology skills. That said, a wholesale change of these competencies across the organization is virtually impossible without an executive commitment to data. Without that, improvement can and should start at the localized level.
To get there: identify a small but important issue that will benefit from the use of analytics and focus on identifying solutions to your issue that have a clear and measurable impact.
The same is true if you want to foster collaboration. We recommend you find others in the organization that have data that is important to addressing your issue. Enlist their help as partners to increase the value of their data decision-making. Share information, build relationships and facilitate discussions among peers in different departments on bringing data together to address specific challenges.
If there is essentially no “burning platform” for analytics in your organization, its value must be proved one small win at a time — with analytics results that are translated into business insights and recommended actions. Show ROI with clear business value: cost reduction, improved operations, increased revenue, and focus discussions on improving business issues, rather than on methodology.
Good luck on your analytics journey! Please feel free to weigh in with some of the answers you’ve found to your organization’s questions. We’d love to hear your insights.