Bloomberg on Business Analytics


Interested in slicing, dicing, measuring, and analyzing data for customer and business insights? According to a recent survey by Bloomberg, 97% of companies with revenues of more than $100 million are using some form of business analytics, up from 90% just two years ago.

While businesses have embraced the idea of fact-based decision-making, a steep learning curve remains. Only one in four organizations believes its use of business analytics has been “very effective” in helping to make decisions.

This is a far cry from the current hype around analytics and big data, raising the questions:

  • How can an organization evolve to effectively leveraging analytics?
  • What skillset, mindset, toolset adjustments need to be made to “think outside of the box”? 

These are core questions that managers must ponder. Many companies start their analytics journey by executing one or two projects of small scope. That may be fine at the outset, but in order to address the larger performance improvement issues, companies need to move up the maturity curve from repeatable to defined and then to managed and optimized.

The following are research insights highlighted by the survey sample of 930:

  • Business analytics is still in the “emerging stage.” While analytics has gone mainstream, most organizations still rely on traditional technology. Spreadsheets are the number-one tool used for business analytics.
  • Organizations are proceeding cautiously in their adoption of analytics. Use of business analytics within companies has grown over the past year, but at a moderate rate. Analytics also tend to be used narrowly within departments or business units, not integrated across the organization.
  • Intuition based on business experience is still the driving factor in decision-making. Analytics is used as part of the decision process at varying levels, depending on the organization.
  • Companies are looking to analytics to solve big issues, with the primary focus on money: reducing costs, improving the bottom line, and managing risks.
  • Data is the number-one challenge in the adoption or use of business analytics. Companies continue to struggle with data accuracy, consistency, and even access.
  • Many organizations lack the proper analytical talent. Businesses that struggle with making good use of analytics often don’t know how to apply the results.
  • Culture plays a critical role in the effective use of business analytics. Companies that have built an “analytics culture” are reaping the benefits of their analytics investments.

Nothing earth shattering here….Like all innovation, adoption will take time and require significant organizational changes across toolsets, skillsets and mindsets. But make no mistake, companies that don’t embrace analytics in a fast paced competitive environment will be left behind.


What Is Your “Analytics Maturity ”?

In order to change, you have to baseline first – what is your analytics maturity.  The business analytics maturity curve represents the arc of progression every company moves along. Maturity levels are measured by your level of experience, the implementation and support strategies you use, and your degree of sophistication around data.



Analytics maturity can be assigned to one of the following four groups:

  1. Reactive businesses engage in business analytics only in a reactionary mode, e.g., by complying with a customer request or in response to competitive pressure.
  2. Responsive companies are engaging in business analytics, but mostly as separate, one-off projects.
  3. Proactive organizations have established processes, infrastructure, and resources to support business analytics in a programmatic manner.
  4. Aggressive companies aggressively expand analytics capability as an important growth opportunity and encourage their customers to adopt it.

Which type of organization do you belong to? Where do you want to be?

Notes and References

Source: Bloomberg Businessweek Research Services study, conducted among 930 businesses across the globe in various industries. Focus of the study is to provide insight into the current state of business analytics in today’s organizations. Also examine the challenges companies face when using analytics, and explore tactics favored by companies who have succeeded in using analytics more effectively than their peers.



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Curtis says:

The survey is misleading and contributes to confusion surrounding terminology and definition in this knowledge space.

Business analytics is subset of “Business Intelligence” and is activity based on statistics, prediction, and optimization. Business Intelligence includes querying, reporting, OLAP, signalling/alerts and Business Analytics.

This survey had it flipped around. Survey should have been asking people what categories of activities they thought were Business Intelligence and if their company used that category of Business Intelligence. I suspect that this skews the survey results, as does the categories participants were asked to choose from because categories do not neatly fall under either Business Intelligence or the subset Business Analytics.

The categories in survey that are clearly Business Analytics were:
(#’s are % respondents who “Viewed as Business Analytics Tool” / “Use Tool”)
Forecasting 66/54
Data and Text Mining 58/39
General Statistics 52/40
Optimization 39/28
Simulations and Scenario Development 46/31

The categories in survey that are clearly under the remaining Business Intelligence categories were:
Business Reporting/KPIs/Dashboards 67/56
Spreadsheets 56/62

The remaining categories could be Business Analysis or querying, reporting, OLAP or signalling/alerts, dependent on what activity is being done:
Text, Audio, and Video Analytics 25/13
Web Analytics 44/25
Model Management 43/25
Query and Analysis 46/40
Interactive Data Visualization 35/18
Social Media Analytics 34/21

Looking at survey results from this perspective, it appears 97% of companies are using some form of Business Intelligence (and not Business Analytics).

A much smaller % of companies, perhaps 50%, are using Business Analytics eg statistics, prediction, and optimization.

The categories used in survey present some challenges. Two examples:

* I would doubt that only 25% of $100 million companies use Web Analytics. In fact I would expect 100% of them use Web Analytics. If this category was misunderstood by participants then it calls into question participants’ ability to discern other categories.

* Grouping Query and Analysis together is not helpful. “Queries” can be used to assist in statistics, prediction, and optimization but if that is activity being undertaken then it should be categorized as such rather than as “Query”. Analysis is also quite ambiguous a term without ascribing function or additional description. One can be analytical without conducting Business Analytics.

The 50% result for use of Business Analytics by these larger companies is probably closer to reality. However, if categories were chosen better, it might have reflected the complex and intensive use of statistics, prediction, and optimization is done by a much smaller % of companies. This is high end of Business Analytics for which the qualified workers is in high demand (and short supply).

Finally, while it may be true that 100% of these large companies use Business Intelligence, it is doubtful that 100% are true “data driven organizations” with 100% pervasive integration of BI throughout the organization, used 100% of time. There are very few of these organizations in the world. In fact, I would expect that less than 10% of the companies surveyed are true “data driven organizations”.

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