Top 10 Business Intelligence Predictions For 2012

Demands by users of business intelligence (BI) applications to "just get it done" are turning typical BI relationships, such as business/IT alignment and the roles that traditional and next-generation BI technologies play, upside down. As business users demand more control over BI applications, IT is losing its once-exclusive control over BI platforms, tools, and applications. It's no longer business as usual: For example, organizations are supplementing previously unshakable pillars of BI, such as tightly controlled relational databases, with alternative platforms. Forrester recommends that business and IT professionals responsible for BI understand and start embracing some of the latest BI trends — or risk falling behind.

Traditional BI approaches often fall short for the two following reasons (among many others):

  • BI hasn't fully empowered information workers, who still largely depend on IT
  • BI platforms, tools and applications aren't agile enough

2012 will bring a new set of trends that BI and business process professionals will need to stay on top of. Despite the recession of 2007 to 2009 and continued economic uncertainty in 2010 and 2011, Forrester has not seen any decline in BI efforts among its clients. Actually, businesses have no choice but to act and react quickly in the face of financial volatility and rapidly changing business and regulatory conditions. Therefore, "getting things done quickly" often takes priority over "getting things done in an approved way." These changes force IT to give up some control over BI in favor of working more closely with business users. This forms the basis of most of the trends Forrester sees in how organizations will use BI and what new technologies will go mainstream

  1. Individualized fit for purpose BI tools trump standards.
  2. A "multiple BI tool" strategy is here to stay for the foreseeable future.
  3. Ready or not, information workers will demand more BI control.
  4. BI tools that support the right amount of managed end user self-service will become popular.
  5. Mobility is no longer a "nice to have" — it will become the new BI mantra.
  6. Cloud BI will slowly and steadily chip away at on-premises implementations.
  7. BI-specific DBMSes will gain popularity.
  8. Big data will move out of silos and into enterprise IT.
  9. Exploration will become the new bread and butter of BI suites.
  10. BI will integrate with the Information Workplace (IW).

For more information please take a look at the detailed research report behind these predictions


Multiple BI tools vs platform consolidation


Thanks for the effort here. Individually I don't find much to disagree with, but when reading it through I did find some difficulty in not seeing some conflicts between:

"BI users start demanding and vendors start delivering BI tools integrated with email and collaboration platforms."

No problem here until going back to:

"It’s all about getting things done. >>BI tools functionality to get things done trumps standards."

I see standards as a data quality issue primarily, but also one of access

"Big data starts to move out of silos and into enterprise IT."

"More BI moves into the hands of end users. IT learns not fight it or risk becoming irrelevant."

My point is that tool functionality depends to a large degree on data quality, which depends to a substantial degree on data standards, and end user access to include undefined queries depend not on asking IT for access, but for architecture that provides it. While it can be done with integration without standards, data standards are obviously far less costly.

"Forrester client inquiries about how to live with multiple BI tools far exceed inquiries about platform consolidations."

I take this as the clients understand that one size fits all and enterprise commoditization is the path to failure (or as Bob Herbold says in What's Holding You Back -- "avoid commodity hell"), but just wanted to make the point that platforms that employ data standards and are designed for adaptability need not prohibit other tools. It's a choice that is very much influenced by customer behavior, which all too often has incentivized and rewarded behavior by vendors that is directly (and in some cases increasingly) conflicting with the mission of the client organization.

Mark Montgomery
Founder & CEO

Mark, as always thank you for

Mark, as always thank you for insightful comments. A few points. 1) Re: data quality. All our research points to a fact/realization that data quality is relative and contextual, not absolute. 2) Re: multiple BI tools. In our recent research on BI self service (see link above), not a single vendor provided all of the key self service features. Until they do - i don't see this happening in the near future - multiple BI tools will be a pragmatic reality. Happy to continue the dialogue!

1 and 2

1) Yes indeed, albeit broad-- quality is itself a function of analytics in my view and design, on a sliding scale and to some extent in the eye of the beholder-- at least relative to tailored for individual mission.

2) Well, here we go again on standards-- if maintenance fees are 20+% to keep the lights on, and integration is dependent on either internal or external gatekeepers--or expensive consultants, then self-service is far more problematic. Layers of stakeholders is a challenge in both organizational design and enterprise system design, but agree that's the direction-- it's all we've ever pursued-- self managed systems. I'd do something else with my life otherwise.

I personally think multiple BI tools will be desirable even with holistic, adaptable, largely self-managed systems like our Kyield-- in our case we intentionally provide for plug-ins in no small part due to the need for competitive advantage, third party algorithms, patented technology, OS, etc. etc. -- endless possibilities to forge new territory for the creative mind, but the system design must of course embrace that reality.

Interesting post by Chris, IT@IntelSME below -- with so much interaction with Intel over the years, I am surprised that this is a new internal venture, but not surprised at the low hanging fruit in semiconductor manufacturing. As we've attempted to convince with old Intel friends up to the board level -- there is enormous potential for both sides of the balance sheet, even in a healthy one that is well managed and lean. I think in their corp culture it may be easier to analyze material science and physics than human performance systems, so their strengths tend towards cost side--understandable, but one need not track long even externally to see massive opportunity on the revenue side as well. Good work-- thanks, MM

Intel IT embraces BI for 2012

Boris, At Intel IT, we are accelerating our efforts around BI in 2012 - as we have found that harnessing big data means big value for our business. We just published a new IT@Intel paper discusses the virtual explosion of business intelligence and advanced analytics projects we are working on.

One of the more interesting aspects of our BI investment roadmap is what we are calling a 5-6-10 BI innovation model. This IT best practice model deploys small (~5 person) BI teams for 6 months with the goal of delivering up to $10M of value. Intel IT has successfully deployed advanced analytics across silicon design, manufacturing, and security teams increasing business velocity and improving decision making.

Learn more about our “Roadmap for Transforming Intel’s Business with Advanced Analytics" -

Great model. What has your

Great model. What has your real experience been? What % of these projects actually achieved $10M value in 6 months?

Boris, We are just beginning


We are just beginning to deploy the model I mentioned now so don't have a % metric yet - however we do have a few advanced analytic successes ID'd in the paper under our belt are are using these successes to build momentum with our business partners.

One of the examples is use of a BI engine that predicts likelihood of job failures and run times during silicon design. With this information, IT can rebalance compute capacity across a grid computing environment (similar to a private cloud) maximizing useful utilization of existing assets and avoiding unecessary capital spending. This 1 project is expected to save up to $7M annually.


Predictive Analytics

Boris, insightful information. Are you preparing your Top 10 Analytics predictions For 2012?



The line between BI & Predictive has blurred...

I find it hard to believe that any discussion for Predictive Analytics won't be in the context of BI & vice-versa. Part of Boris's first statement that it's about getting things done.

analytics is just one BI component

George and Jacinto. It's very simple. Advanced analytics is nothing new. I built my first SAS data mining for fraud detection app in the late '90s. It's a popular market segment but i don't see anything new happening in 2012 specifically related to advanced analytics. In my definition analytics (of which advanced analytics is a part) is part of BI. So everything I say about BI is 100% attributable to advanced analytics.

Boris, great insights I

Boris, great insights I think you are spot on.

Packaged Analytics/BI

Where do you see packaged analytics fitting in the BI. I'm especially thinking of mid market firms with needs but not the people and skill sets to build their own.

Good question, but it's a

Good question, but it's a whole different world. My predictions are mostly about BI platforms, not specific apps or solutions, used by enterprises. IMO prebuilt apps/solutions become more attractive mostly at the lower end of midmarket and in small businesses. Businesses in the upper end of mid market, say $500M+ tend to customize. But, just like everything else in BI, the only right answer is "it depends". I just finished an advisory project for a $500M co which is looking for a highly customizable platform, and starting a project for a multi billion $ co which is looking for buy vs build analysis, thinking that they failed at building and may need to consider buying.

Spreadsheet silos = part of Big Data


Very much agree with your comments and wanted to highlight another link between your points.

For many complex institutions a key part of their 'Big Data' (your Point #8) issue is spreadsheets and other 'semi-structured' financial data. So acceptance of your Point #3 will then encourage IT departments to think about how to analyze/exploit these data silos at an enterprise level - rather than fruitlessy chase extermination.