Comment on ‘EIS revisited’

In a recent post on BeyeNetwork Dan Power made an argument to revisit the concept of an Executive Information System (EIS). This post builds upon that argument and adds to the discussion. For people who don’t know Dan Power, Dan is a professor of IS and one of the few scholars who actively participates in the BI practioners community, trying to bridge the gap between science and practice. As you know, I’m a strong advocate of this kind of interaction, so all the praise to Dan.

Now, let’s get to the article. An argument is made to readdress our attention to executive users and renew the EIS-concept. Next to that, Dan argues that system concepts like EIS, BI, datawarehousing etc. are converging. Here’s my response.

First of all, it’s good to know that EIS’s have been covered widely in scientific research which has resulted in a significant body of knowledge. Next to that, the EIS-concept resembles our current and most common understanding of BI (i.e. management reporting in its broadest sense). BI on the other hand, has hardly been investigated yet; datawarehousing has, but BI has not. So EIS research is our most recent resource of scientific knowledge. Therefore it’s logical to revert to these theories.

I agree with Dan’s final premise that the executive is an important target group and we should focus special attention to them. In order to do so, I’d like to add two refinements. To begin with, we need a clear definition  of who the executive is. Is it limited to the CxO’s, is the 2nd management level included etc.? What characterizes his role and his way of working? I personally experienced a situation were the board of directors insisted on receiving a printed version of the monthly performance review. No strong reporting and drill-down capabilities here… So, to target this user group, we need to define it more precisely.

Secondly, we need to separate te executive user (support) from executive process (support). Executive processes resembles processes like strategic decision making, negotiating and monitoring market trends. These kind of processes require different BI-support than tactical management processes for example. Executive usage defines usability requirements (e.g. no training required, PDA-support) whereas the required process support determines required functionality.

Current BI-platforms provide powerful capabilities to both consolidate the different kind of systems and technologies and at the same time provide the targeted support the executive needs.

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Posted in BI research

The need for rigourness

This post is a comment to Ronald Damhof’s latest blog in which he argues the need for a stronger theoretical foundation in the field. By now, you should know that’s also one of my hobby horses. Let me illustrate the need for this kind of rigourness by two examples.

First, we all know the success stories of successful BI-implementations, especially those that were put on the stand by Davenport’s book “Competing on analytics”. Harrah’s,  a casino and hotel chain is one of those examples; the CEO wrote the foreword of Davenport’s book. However, Harrah’s is also used as an example of a successful implementation of IT Portfolio Management (MIT Sloan Management Review, spring 2004, Vol.45, no.3) with corresponding net effects on Harrah’s performance. I won’t deny a priori the positive effects of both a portfolio management approach and the extensive use of analytics. But available publications gives us to little insight into the real net-effects and the causal relationships (instead of positive correlations).

This leads me to the second example. Even in scientific research we often read about the same succesful companies (sorry, no reference here). Amazon, Google, Dell you name them are always in the spotlights. In the ’80’s it was Sabre, American Hospital Supply (AHS) and Otis Elevator to name some earlier examples.

Why is that, I ask myself…

Posted in BI research

International Journal of Business Intelligence Research

I’ve argued several times that we lack fundamental insights into our own playing field. Fortunately, it seems that change is on the way! Recently, the International Journal of Business Intelligence Research (IJBIR) has been launched. According to the journal’s mission statement, it aims to fill the gap between practioner journals and the ‘hard core’ academic ones. A great initiative! Check out the journal’s home page and a comment by the new editor-in-chief.

Posted in BI research

BI is the same, not different

BI people – and I am one of them! – tend to see the world differently, sometimes very differently from the rest of the IT-world. For long, BI was a neglected area of IT, often seen as byproduct of custom systems development (oops, forgotten, we also need some management reports). First triggered by huge advances in technology and more recently by Davenport’s seminal article ‘Competing on analytics’ in HBR, BI got a business face and a new, much more appealing connotation: the underpinnings were there to view BI as a whole new area of business with programme managers, architects and consultants lobbying for dedicated attention, trying to convince the CEO the company needs to follow an analytics strategy (instead of…?) and transform the organization. As a result, a whole new ecosystem within the IT-world has evolved, with its own vocabulary and the urge to create its own methods, tools etc. For BI people, BI is a whole different ball-game than traditional IT (or transactional IT, or operational IT or….).

I’m increasingly confused and less convinced that this distinct view of the world is justifiable. True, technological developments have created opportunities that didn’t exist before. We’re now able to store tons of data, apply advanced analytics and use the results in operational processess on a real-time, transactional scale. But does this change the way we formulate an IT-strategy, develop solutions, run IT-operations, govern developments? More and more, I tend to answer no, instead of yes. Sure, some things are different but only to a certain extent. It certainly does not justifies a whole separate approach. Why come up with a proprietary architecture / requirements / development method when there are industry standards available? No doubt common standards will lack some specifics that are required for BI-initiatives but isn’t it more effective to provide some kind of add-on to a common standard instead of developing one’s own? Data Vault project management? I don’t know…

More and more, I tend to take a common standard or method as a start, as I’m doing in my current assignment which deals with enterprise architecture, instead of staying with my “BI is unique and the rest of the world should change”-paradigm and trying to convince any other they should adhere to it. In a short time, it has offered me with many valuable insights and allowed to me better (!) govern and architect BI instead of less. It seems to me that this proprietary approach to BI rather impedes success and performance impact than boosts it.

Posted in BI industry, Our profession

Book review: The profit impact of Business Intelligence

In search of relevant literature that adressess the business side of BI, I encountered this book written by Steve Williams and Nancy Williams. Steve and Nancy are instructors at the TDWI and run their own firm, DecisionPath. If there’s one message that remains after reading the book, it’s that BI should be used to impact profits and business performance. This message is repeated so often that it becomes somewhat annoying but I guess that’s a kind of (American) style of writing. Nevertheless, that message is most valuable: all too often the emphasis is on better data, sexier tools or new analytics but less on how this is supposed to impact processes that drive profits and performance (I’m beginning to sound like them…).

Let’s have a brief look at the outline of the book. The first chapter stresses the key message but for me the most important content concerns two other key points: the need for process engineering and the need for change management.  This viewpoint was also brought forward in their 2003 article in Business Intelligence Journal. Especially the process engineering-perspective is important: business processes need to be re-engineered as a result of other (more sophisticated) use of information. It would have been nice if this viewpoint had been elaborated more in the book. Change management deals with changing the business practice and thus human behaviour as a result of changed information provision and business processes. Common change management-practices – like Kotter’s Leading Change approach – apply to this one, but the value is in emphasizing the imperative that BI-initiatives require change management to be succesful.

The next two chapters deal with opportunity analysis and risk- and readiness assessment. Once one has adopted the paradigm set forth in the first chapter, the risk and opportunity-assessment become rather straightforward. The key to do a proper assessment is in understanding the paradigm. Chapter 4 deals with their development methodology, the BI Pathway, and to be honest, this was a somewhat disappointing chapter. To me, the methodology didn’t bring any new fundamental insights and rather than providing some new in-depth knowledge or skills, the reader is encouraged to take a course at the TDWI. Moreover, I would sincerely refrain from presenting an overview of the method (Fig. 4-2 p. 70) to a business audience. For a non-IT person it contains a lot of detail and techno terminology.

BI people tend to see the world differently from the rest (guilty, I used to do that too) and the BI Pathway is just another example. It’s content is good but I see little value in wrapping it into  another methodology. In my opinion, BI professionals should strive to adhere to common standards and frameworks, like TOGAF and RUP. Such an approach does not inhibit or exclude the special treatment of specific BI-aspects.

Chapter 5 is about leading a change progam and here a need for changing the culture of information usage is stressed. Next to that, required core competencies are listed and these provide a valuable checklist for a BI-program. The next chapter deals with the IT that is specific to BI and should have no secrets for any experienced BI professional. In a way, the 7th chapter extends the opportunity analysis of chapter 2 and provides several more specific examples of how BI can impact profits and performance. Basically, chapter 8 is about the don’ts and illustrates common pitfalls, like lack of program management, insufficient information requirements and using an OLTP infrastructure. The final chapter concludes with a view over the horizon.

As explained at the start, the key message is to focus on performance improvements and the primary value of the book is that that message has been written down. However, for a book that intends to convey this thinking, it still contains a lot of BI-technical details, which is a bit odd to me considering that the target audience are managers and executives. Apart from that, as a BI-professional, I’m curious about the HOW. On several occasions, some very BI-specific issues are illustrated. A good example is the observation that end-users tend to define their requirements in terms of reports because that is what they are used to. This observation is a step-stone for describing ways to improve the requirements process but the book provides this kind of deepening too little. A good step-stone to write another book…

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Posted in business value

Fuzzy Gartner

Gartner’s been here and it hasn’t been left unnoticed. The annual BI Summit was used to announce 5 predictions for the future which triggered several discussions  (e.g. in Automatiseringgids and on the Computable blog) both about the predictions themselves and the course Gartner seems to be taking (less focused on technology but more on the management side).

Gartner’s message gave me an awkward feeling. Just a few weeks earlier, a Gartner study was published stating that BI was still on top of mind in 2009 and now they warn us to be careful. What is Gartner trying to tell us?  I can’t help the feeling that for me Gartner’s value to our profession and industry is declining. Some of their research has been very helpful in tracking movements on the (vendor) market, most notably their Magic Quadrants. But more and more, I get disappointed in their message to the market: either they are too obvious (‘BI-governance will shift from IT to the Business’) or way to broad (‘SaaS will gain bigger share’).

I have argued before that to my opinion we lack deep understanding of our own playing field. I’d rather see Gartner provide that in-depth insight we need so desperately. For example, how does the application of BI differ among industries; where, how, when and why does real-time information really makes a difference, what are the fundamental criteria to differentiate the different types of BI, just to name a few. But this kind of research probably doesn’t make a sexy summit…


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Posted in BI industry

Ad hoc reporting, the tools

This post follows up on my previous post in which ad hoc reporting was defined. To wrap things up, the most important features were:

  1. Iterative processing of the entire BI-development cycle
  2. Performed by end-users
  3. On a mix of data sources
  4. With some kind of manual intervention, somewhere in the process

Now that we know what we’re talking about, we can much better define the requirements for supporting technology (finally we get to the tools!). Rephrasing the features into requirements results in the following list:

  1. Support for the entire process (from ETL to reporting building and distribution)
  2. Ease of use: the end-user is the designated user of a BI-solution, not an experience software engineer!
  3. Statistics & usage monitoring: some sort of monitoring by IT-staff / BICC is necessary to keep an eye on what’s going on.
  4. Security and authorization, e.g. to define roles who’s allowed to map new data sources.
  5. Level of integration with the core BI-platform that is used within the enterprise for bulk reporting, pre-defined OLAP-cubes etc.

(Obvious requirements like maintainability etc. are left out-of-scope here).

Probably the most difficult requirement is the last one, level of integration. Let me explain this one. Most mature BI-organizations have consolidated their BI-stack and most of the time chosen for one particular vendor (BO, Cognos, whatever). Current platforms are able to cover a broad range of capabilities, like plain reporting, dashboarding, OLAP etc. The set-up of such an environment is done in the metadata where data sources are mapped to objects that can be used in BI-applications (in SAS these are the information maps, in BO the universe, in MicroStrategy the schema objects to name a few examples). Now here’s the key: this mapping of data sources to (common) objects, is nearly always done based on requirements, design and specifications and done by a BI-developer. Creating accurately defined meta data objects is a key activity to realize a common BI environment with shared definitions.

In the case of ad hoc, ideally the end-user is both able to reuse common metadata that is centrally defined and governed and add new data sources at will which he wants to use for analysis purposes. From a technological point-of-view, the end-user should be equipped with specific functionality designed for his purposes and context and not with the full installation of the client software which is often used by the BICC or BI-developer (apart from license issues). I know this is a difficult one, I hope you can follow me here.

OK, now we get to the vendors! Until recently, to my knowledge SAS’ Enterprise Guide was the only one the market that was able to fulfill this requirement. Fortunately, there’s been a lot of movement lately and some new alternatives seem to be on the horizon. One is MicroSoft’s Gemini solution (see Jorgen’s comment on this one), the other is the announcement this week of MicroStrategy 9 which includes a multi-source option and better self-service capabilities.  Please let me know if any of you have seen these products and whether they are able to fulfill the requirements for ad hoc reporting.

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Posted in Ad hoc query & reporting