In October, IBM released a report from their Institute for Business Value titled Analytics – A Blueprint for Value. IBM releases these reports on a periodic basis, and this one is focused on the growing importance of analytics to business success. Through their analysis, they came up with nine levers that represent the sets of capabilities that most differentiated leaders exhibit:

1. Culture: Availability and use of data and analytics within an organization
2. Data: Structure and formality of the organization’s data governance process and the security of its data
3. Expertise: Development of and access to data management and analytic skills and capabilities
4. Funding: Financial rigor in the analytics funding process
5. Measurement: Evaluating the impact on business outcomes
6. Platform: Integrated capabilities delivered by hardware and software
7. Source of value: Actions and decisions that generate results
8. Sponsorship: Executive support and involvement
9. Trust: Organizational confidence

These levers make sense. I imagine they collectively represent the analytic maturity of organizations – even if it is not explicitly stated as a lever – more on that later. The report found that the majority of analytics efforts are focused on the first digital enterprise forcing function – Growth and Innovation. Seventy-five percent of Leaders, and 70 percent of all other respondents, attributed the value of analytics solutions to their ability to increase revenues, increase the speed and accuracy of decisions, and generate innovative ideas.

But the report found disconnects in some organizations between value creation and their current analytic focus. The authors conclude that companies derive the most value when they clearly understand the source of value and target activities toward objectives associated with that value. The example provided focuses on revenue-generation objectives, where more than one-third (37 percent) are focused specifically on activities designed to better know, understand, interact with and engage with customers.

Their findings indicate that the top one-fifth of Leaders base all their business decisions – both strategic and operational – on information provided by analytics. I just have not seen a level of analytic maturity in companies to believe this finding. The report covers maturity at some level by examining the analytic capabilities of organizations. They found a majority of all respondents can support query and reporting (73 percent), data visualization (58 percent) and data mining (57 percent). In a recent Blog on transformation, I describe the journey that companies must travel to evolve from Descriptive to Prescriptive on an analytic maturity curve. This journey – otherwise viewed as the shift in focus from hindsight to foresight – is complex. When I ask executives where they are on this journey, it leans towards the descriptive stage – with some believing they are somewhere between descriptive and predictive. That for me is a better barometer of analytic capability than a focus on data mining for instance.

The report determined that leaders have evolved beyond foundational business intelligence platforms to a modern, flexible infrastructure that can intake, process and manage the volume, velocity and variety of today’s data. More than one-third of Leaders, for example, have implemented cloud technology and mobile solutions, while roughly another third are currently developing strategies to implement those technologies. This evolution may make them leaders in the use of technology, but does it make them leaders in the use of insight?

Other findings are also curious – as I am just not seeing the same thing. For instance, sixty percent of Leaders have predictive analytic capabilities, as well as simulation (55 percent) and optimization (67 percent) capabilities. By comparison, just over half (52 percent) of all other respondents have predictive capabilities, while fewer than half have simulation (45 percent) or optimization (49 percent) skills. The effective use of these capabilities is critical to the evolution through predictive and to prescriptive. But simply having these capabilities in place in my mind does not make you a leader. This would say to me that companies are further along the analytic maturity curve than they are – a fact that is then supported in the same report by Gartner: Gartner predicts that through 2015, predictive and prescriptive analytics will be incorporated into less than 25 percent of business analytics projects, but will deliver at least 50 percent of the business value. This is much more in line with what I am seeing.

Some other key findings:

• Top-down executive-driven leadership is required – executive advocates that believe in the power of analytics and are passionate about instilling a data-driven culture

• The gap between the demand for analytics talent globally and the supply of analytics talent locally is one of the key obstacles to analytics implementations across all organizations

• Innovative public-private partnerships are emerging around the globe to create centers of analytics excellence accessible to the broader business community

• Gartner finds that by 2015, the demand for data and analytics resources will reach 4.4 million jobs globally, but only one-third of those jobs will be filled. The largest skills gap is the ability to combine analytic skills with business knowledge

• Leaders have discovered it is more effective and cost-efficient to supplement business knowledge with analytics knowledge by building skills among those already within an organization

• Organizations will likely find it easier to teach critical thinking and analytics software skills to someone knowledgeable about the business than to instill business knowledge in an outside analytics expert

• Training existing employees is also prudent given the current low supply of, and high demand for, strong analytic talent