New research from IBM shows a lack of support from the C-suite is the biggest obstacle to the development of business analytics and big data management. This is compounded by skepticism about the value of the data and the shortage of big data and analytics talent.
The findings, contained in the recently published Analytics: A Blueprint for Value (registration needed) report, are the result of a survey of 1,000 business and IT executives in 70 countries.
Overall, the findings show analytics and big data initiatives are just gaining ground in enterprises. Most enterprises haven’t really developed strategies around deployment and management of these new technologies, particularly around big data.
None of the obstacles — lack of trust, a talent shortage and lack of C-Suite sponsorship — are new or even surprising. We have found them referenced in other studies numerous times before.
The overall research shows analytics and big data have the potential to help enterprises grow their revenues and client base but is still meeting resistance in most enterprises.
About 75 percent of the highest performing companies cite growth and innovation as the principal advantages of deploying business analytics. Those high performing companies are distinguished by nine differentiators or levers:
Culture: A culture that encourages use of data and analytics within an organization
Data: Structure and formality of the organization’s data governance
Expertise: Development of, and access to, data management and analytic skills
Funding: Financial rigor in the analytics funding process
Measurement: Evaluating the impact on business outcomes
Platform: Integrated capabilities delivered by hardware and software
Source of value: Actions and decisions that generate results
Sponsorship: Executive support and involvement
Trust: Organizational confidence
Needless to say, the vast majority of companies surveyed could not be classified as "Leaders." In fact, only 19 percent could be considered as such. Geographically, leading companies came from the following:
- North America (27 percent)
- Asia Pacific (22 percent)
- Latin America (24 percent)
- Europe, the Middle East and Africa (27 percent).
These companies all have more than 1,000 employees and have been in business for more than 25 years.
The breakdown demonstrates just how widespread use of analytics has become and the types of companies that have deployed these solutions.
However, even these companies report they face political and executive restraints (62 percent) that affect their abilities to optimize the financial value of their deployments.
This percentage is statistically consistent with organizations that are not considered "leading companies." What distinguishes the leaders are their consistent implementation of processes designed to minimize disruptive politics and other corporate constraints.
This is the fifth year IBM has published research on the adoption and use of analytics in the enterprise. Overall, despite problems around in the C-Suite, a growing number of enterprises are using analytics to support revenue generation strategies. To overcome the problems, the report suggests enterprises overcome three principal stumbling blocks:
- Executive Advocates: According to the research only a small number of C-Suite executives are strong advocates of analytics and big data solutions. Only a quarter of Chief Executive Officers (CEOs) and Chief Operating Officers (COOs) are strong advocates of using the insights garnered from analytics. While this is around 10 percent, higher than last year, the report points out this is far from the level of support needed to ensure a change in corporate culture around analytics use. In enterprises where there are low levels of corporate support, deployments are hindered by a lack of funding, human resources issues and follow-through. The report suggests the appointment of a Chief Data Officer or Chief Analytics Officer could build a corporate culture that is more receptive to analytics adoption.
- The Trust Gap: A lack of trust across the enterprise is proving to be one of the biggest problems, the research found. In this respect, trust means the trust across departments in the way analytic insights are gained and interpreted. While 60 percent enjoy strong levels of trust among individuals in their organizations, this percentage drops when it comes to trust between anonymized business units and IT departments. This IT-Business divide is not new, but it is clearly hurting the abilities of enterprises to drive revenue from technology investment
The impact of a lack of trust across different units in the enterprise cannot be underestimated, the report states. A fragmented approach to the way information is being access and interpreted can lead to the unwillingness to share data or rely on insights that have come from different business units. The report cites the example of a major bank that duplicated data collection efforts because executives did not turns the work of another team of executives operating in a different geography. From a data management perspective there is so many things wrong with this it would be hard to count them, but even from an IT investment point of view the impact on the business is going to be very high.
- Growing Skills Gap: The final area that needs to be addressed is one that we have looked at on many occasions. The talent gap. Many technology companies, IBM included, have been investing considerable amounts of money in educational programs that offer analytics and big data education. The extent of the skills gap was quantified in this report. It found one third of all enterprises cited the lack of skills to analyze and interpret data and translate those findings into business actions as the biggest problems they had with analytics.
By far the biggest skills gap is in the ability to combine analytics skills with business knowledge, which prevents enterprises from drawing useful business insights from data. Analysts who understand business and can manage the mathematics behind analytics are the most sought after people in the market (36 percent) while pure analytic (24 percent) and data management skills (21 percent) still outstripped demand for business skills (19 percent).
These are only some of the findings of this report. Apart from the fact that it numerically indemnifies current challenges with analytics, it also points to ways in which the problems might be solved.
However, implementing solutions is one of the functions of C-Suite executives, who have been identified, to a large extent, as being one of the really big problems for enterprises in this respect. Whether they are willing or not to change the C-Suite culture themselves, or whether market forces changes on them, remains to be seen. One way of the other, next year’s report will make for interesting reading.