“Big vs. Small BI” by Ann All at IT Business Edge

19 May 2009

Introduction

  Ann All IT Business Edge  

Back in February, Dorothy Miller wrote a piece at IT Business Edge entitled, Measuring the Return on Investment for Business Intelligence. I wrote a comment on this, which I subsequently expanded to create my article, Measuring the benefits of Business Intelligence.

This particular wheel has now come full circle with Ann All from the same web site recently interviewing me and several BI industry leaders about our thoughts on the best ways to generate returns from business intelligence projects. This new article is called, Big vs. Small BI: Which Set of Returns Is Right for Your Company? In it Ann weaves together an interesting range of (sometimes divergent) opinions about which BI model is most likely to lead to success. I would recommend you read her work.

The other people that Ann quotes are:

• John Colbert Vice president of research and analytics for consulting company BPM Partners.
• Dorothy Miller Founder of consulting company BI Metrics (and author of the article I mention above).
• Michael Corcoran Chief marketing officer for Information Builders, a provider of BI solutions.
• Nigel Pendse Industry analyst and author of the annual BI Survey.

 
Some differences of opinion

As might be deduced from the title of Ann’s piece the opinions of the different interviewees were not 100% harmonious with each other. There was however a degree of alignment between a few people. As Ann says:

Corcoran, Colbert and Thomas believe pervasive use of BI yields the greatest benefits.

On this topic she quoted me as follows (I have slightly rearranged the text in order to shorten the quote):

If BI can trace all the way from the beginning of a sales process to how much money it made the company, and do it in a way that focuses on questions that matter at the different decision points, that’s where I’ve seen it be most effective.

By way of contrast Pendse favours:

smaller and more tactical BI projects, largely due to what his surveys show are a short life for BI applications at many companies. “The median age of all of the apps we looked at is less than 2.5 years. For one reason or another, within five years the typical BI app is no longer in use. The problem’s gone away, or people are unhappy with the vendor, or the users changed their minds, or you got acquired and the new owner wants you to do something different,” he says. “It’s not like an ERP system, where you really would expect to use it for many years. The whole idea here is go for quick, simple wins and quick payback. If you’re lucky, it’ll last for a long time. If you’re not lucky, at least you’ve got your payback.”

I’m sure that Nigel’s observations are accurate and his statistics impeccable. However I wonder whether what he is doing here is lumping bad BI projects with good ones. For a BI project a lifetime of 2.5 years seems extraordinarily short, given the time and effort that needs to be devoted to delivering good BI. For some projects the useful lifetime must be shorter than the development period!

Of course it may be that Nigel’s survey does not discriminate between tiny, tactical BI initiatives, failed larger ones and successful enterprise BI implementations. If this is the case, then I would not surprised if the first two categories drag down the median. Though you do occasionally hear horror stories of bad BI projects running for multiple years, consuming millions of dollars and not delivering, most bad BI projects will be killed off fairly soon. Equally, presumably tactical BI projects are intended to have a short lifetime. If both of these types of projects are included in Pendse’s calculations, then maybe the the 2.5 years statistic is more understandable. However, if my assumptions about the survey are indeed correct, then I think that this figure is rather misleading and I would hesitate to draw any major conclusions from it.

In order that I am not accused of hidden bias, I should state unequivocally that I am a strong proponent of Enterprise BI (or all-pervasive BI, call it what you will), indeed I have won an award for an Enterprise BI implementation. I should also stress that I have been responsible for developing BI tools that have been in continuous use (and continuously adding value) for in excess of six years. My opinions on Enterprise BI are firmly based in my experiences of successfully implementing it and seeing the value generated.

With that bit of disclosure out of the way, let’s return to the basis of Nigel’s recommendations by way of a sporting analogy (I have developed quite a taste for these, having recently penned artciles relating both rock climbing and mountain biking to themes in business, technology and change).
 
 
A case study

Manchester United versus Liverpool

The [English] Premier League is the world’s most watched Association Football (Soccer) league and the most lucrative, attracting the top players from all over the globe. It has become evident in recent seasons that the demands for club success have become greater than ever. The owners of clubs (be those rich individuals or shareholders of publicly quoted companies) have accordingly become far less tolerant of failure by those primarily charged with bringing about such success; the club managers. This observation was supported by a recent study[1] that found that the average tenure of a dismissed Premier League manager had declined from a historical average of over 3 years to 1.38 years in 2008.

As an aside, the demands for business intelligence to deliver have undeniably increased in recent years; maybe BI managers are not quite paid the same as Football managers, but some of the pressures are the same. Both Football managers and BI managers need to weave together a cohesive unit from disparate parts (the Football manager creating a team from players with different skills, the BI manager creating a system from different data sources). So given, these parallels, I suggest that my analogy is not unreasonable.

Returning to the remarkable statistic of the average tenure of a departing Premier League manger being only 1.38 years and applying Pendse’s logic we reach an interesting conclusion. Football clubs should be striving to have their managers in place for less than twelve months as they can then be booted out before they are obsolete. If this seems totally counter-intutitive, then maybe we could look at things the other way round. Maybe unsuccessful Football managers don’t last long and maybe neither do unsuccessful BI projects. By way of corollary, maybe there are a lot of unsuccessful BI projects out there – something that I would not dispute.

By way of an example that perhaps bears out this second way of thinking about things, the longest serving Premier League manager, Alex Ferguson of Manchester United, is also the most successful. Manchester United have just won their third successive Premier League and have a realistic chance of becoming the first team ever to retain the UEFA Champions League.

Similarly, I submit that the median age of successful BI projects is most likely significantly more than 2.5 years.
 
 
Final thoughts

I am not a slavish adherent to an inflexible credo of big BI; for me what counts is what works. Tactical BI initiatives can be very beneficial in their own right, as well as being indispensible to the successful conduct of larger BI projects; something that I refer to in my earlier article, Tactical Meandering. However, as explained in the same article, it is my firm belief that tactical BI works best when it is part of a strategic framework.

In closing, there may be some very valid reasons why a quick and tactical approach to BI is a good idea in some circumstances. Nevertheless, even if we accept that the median useful lifetime of a BI system is only 2.5 years, I do not believe that this is grounds for focusing on the tactical to the exclusion of the strategic. In my opinion, a balanced tactical / strategic approach that can be adapted to changing circumstances is more likely to yield sustained benefits than Nigel Pendse’s tactical recipe for BI success.
 

 
Nigel Pendse and I also found ourselves on different sides of a BI debate in: Short-term “Trouble for Big Business Intelligence Vendors” may lead to longer-term advantage.
 
[1] Dr Susan Bridgewater of Warwick Business School quoted in The Independent 2008
 

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Posted by Peter Thomas

Using multiple business intelligence tools in an implementation – Part I

16 May 2009
linkedin The Data Warehousing Institute The Data Warehousing Institute (TDWI™) 2.0

Introduction

This post follows on from a question that was asked on the LinkedIn.com Data Warehousing Institute (TDWI™) 2.0 group. Unfortunately the original thread is no longer available for whatever reason, but the gist of the question was whether anyone had experience with using a number of BI tools to cover different functions within an implementation. So the scenario might be: Tool A for dashboards, Tool B for OLAP, Tool C for Analytics, Tool D for formatted reports and even Tool E for visualisation.

In my initial response I admitted that I had not faced precisely this situation, but that I had worked with the set-up shown in the following diagram, which I felt was not that dissimilar:

An example of a multi-tier BI architecture with different tools

An example of a multi-tier BI architecture with different tools

Here there is no analytics tool (in the statistical modelling sense – Excel played that role) and no true visualisation (unless you count graphs in PowerPlay that is), but each of dashboards, OLAP cubes, formatted reports and simple list reports are present. The reason that this arrangement might not at first sight appear pertinent to the question asked on LinkedIn.com is that two of the layers (and three of the report technologies) are from one vendor; Cognos at the time, IBM-Cognos now. The reason that I felt that there was some relevance was that the Cognos products were from different major releases. The dashboard tool being from their Version 8 architecture and the OLAP cubes and formatted reports from their Version 7 architecture.
 
 
A little history

London Bridge circa 1600

London Bridge circa 1600

Maybe a note of explanation is necessary as clearly we did not plan to have this slight mismatch of technologies. We initially built out our BI infrastructure without a dashboard layer. Partly this was because dashboards weren’t as much of a hot topic for CEOs when we started. However, I also think it also makes sense to overlay dashboards on an established information architecture (something I cover in my earlier article, “All that glisters is not gold” – some thoughts on dashboards, which is also pertinent to these discussions).

When we started to think about adding icing to our BI cake, ReportStudio in Cognos 8 had just come out and we thought that it made sense to look at this; both to deliver dashboards and to assess its potential future role in our BI implementation. At that point, the initial Cognos 8 version of Analysis Studio wasn’t an attractive upgrade path for existing PowerPlay users and so we wanted to stay on PowerPlay 7.3 for a while longer.

The other thing that I should mention is that we had integrated an in-house developed web-based reporting tool with PowerPlay as the drill down tool. The reasons for this were a) we had already trained 750 users in this tool and it seemed sensible to leverage it and b) employing it meant that we didn’t have to buy an additional Cognos 7 product, such as Impromptu, to support this need. This hopefully explains the mild heterogeneity of our set up. I should probably also say that users could directly access any one of the BI tools to get at information and that they could navigate between them as shown by the arrows in the diagram.

I am sure that things have improved immensely in the Cognos toolset since back then, but at the time there was no truly seamless integration between ReportStudio and PowerPlay as they were on different architectures. This meant that we had to code the passing of parameters between the ReportStudio dashboard and PowerPlay cubes ourselves. Although there were some similarities between the two products, there were also some differences at the time and these, plus the custom integration we had to develop, meant that you could also view the two Cognos products as essentially separate tools. Add in here the additional custom integration of our in-house reporting application with PowerPlay and maybe you can begin to see why I felt that there were some similarities between our implementation and one using different vendors for each tool.

I am going to speak a bit about the benefits and disadvantages of having a single vendor approach later, but for now an obvious question is “did our set-up work?” The answer to this was a resounding yes. Though the IT work behind the scenes was maybe not the most elegant (though everything was eminently supportable), from the users’ perspective things were effectively seamless. To slightly pre-empt a later point, I think that the user experience is what really matters, more than what happens on the IT side of the house. Nevertheless let’s move on from some specifics to some general comments.
 
 
The advantages of a single vendor approach to BI

One-stop shopping

One-stop shopping

I think that it makes sense if I lay my cards on the table up-front. I am a paid up member of the BI standardisation club. I think that you only release the true potential of BI when you take a broad based approach and bring as many areas as you can into your warehouse (see my earlier article, Holistic vs Incremental approaches to BI, for my reasons for believing this).

Within the warehouse itself there should be a standardised approach to dimensions (business entities and the hierarchies they are built into should be the same everywhere – I’m sure this will please all my MDM friends out there) and to measures (what is the point if profitability is defined different ways in different reports?). It is almost clichéd nowadays to speak about “the single version of the truth”, but I have always been a proponent of this approach.

I also think that you should have the minimum number of BI tools. Here however the minimum is not necessarily always one. To misquote one of Württemberg’s most famous sons:

Everything should be made as simple as possible, but no simpler.

What he actually said was:

It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.

but maybe the common rendition is itself paying tribute to the principle that he propounded. Let me pause to cover what are the main reasons quoted for adopting a single vendor approach in BI:

  1. Consistent look-and-feel: The tools will have a common look-and-feel, making it easier for people to use them and simplifying training.
  2. Better interoperability: Interoperability between the tools is out-of-the-box, saving on time and effort in developing and maintaining integration.
  3. Clarity in problem resolution: If something goes wrong with your implementation, you don’t get different vendors blaming each other for the problem.
  4. Simpler upgrades: You future proof your architecture, when one element has a new release, it is the vendor’s job to ensure it works with everything else, not yours.
  5. Less people needed: You don’t need to hire an expert for each different vendor tool, thereby reducing the size and cost of your BI team.
  6. Cheaper licensing: It should be cheaper to buy a bundled solution from one vendor and ongoing maintenance fees should also be less.

This all seems to make perfect sense and each of the above points can be seen to be reducing the complexity and cost of your BI solution. Surely it is a no-brainer to adopt this approach? Well maybe. Let me offer some alternative perspectives on each item – none of these wholly negates the point, but I think it is nevertheless worth considering a different perspective before deciding what is best for your organisation.

  1. Consistent look-and-feel: It is not always 100% true that different tools from the same vendor have the same look-and-feel. This might be down to quality control at the vendor, it might be because the vendor has recently acquired part of their product set and not fully integrated it as yet, or – even more basically – it may be because different tools are intended to do different things. To pick one example from outside of BI that has frustrated me endlessly over the years: PowerPoint and Word seem to have very little in common, even in Office 2007. Hopefully different tools from the same vendor will be able to share the same metadata, but this is not always the case. Some research is probably required here before assuming this point is true. Also, picking up on the Bauhaus ethos of form dictating function, you probably don’t want to have your dashboard looking exactly like your OLAP cubes – it wouldn’t be a dashboard then would it? Additional user training will generally be required for each tier in your BI architecture and a single-vendor approach will at best reduce this somewhat.
  2. Better interoperability: I mention an problem with interoperability of the Cognos toolset above. This is is hopefully now a historical oddity, but I would be amazed if similar issues do not arise at least from time to time with most BI vendors. Cognos itself has now been acquired by IBM and I am sure everyone in the new organisation is doing a fine job of consolidating the product lines, but it would be incredible if there were not some mismatches that occur in the process. Even without acquisitions it is likely that elements of a vendor’s product set get slightly out of alignment from time to time.
  3. Clarity in problem resolution: This is hopefully a valid point, however it probably won’t stop your BI tool vendor from suggesting that it is your web-server software, or network topology, or database version that is causing the issue. Call me cynical if you wish, I prefer to think of myself as a seasoned IT professional!
  4. Simpler upgrades: Again this is also most likely to be a plus point, but problems can occur when only parts of a product set have upgrades. Also you may need to upgrade Tool A to the latest version to address a bug or to deliver desired functionality, but have equally valid reasons for keeping Tool B at the previous release. This can cause problems in a single supplier scenario precisely because the elements are likely to be more tightly coupled with each other, something that you may have a chance of being insulated against if you use tools from different vendors.
  5. Less people needed: While there might be half a point here, I think that this is mostly fallacious. The skills required to build an easy-to-use and impactful dashboard are not the same as building OLAP cubes. It may be that you have flexible and creative people who can do both (I have been thus blessed myself in the past in projects I ran), but this type of person would most likely be equally adept whatever tool they were using. Again there may be some efficiencies in sharing metadata, but it is important not to over-state these. You may well still need a dashboard person and an OLAP person, if you don’t then the person who can do both with probably not care about which vendor provides the tools.
  6. Cheaper licensing: Let’s think about this. How many vendors give you Tool B free when you purchase Tool A? Not many is the answer in my experience, they are commercial entities after all. It may be more economical to purchase bundles of products from a vendor, but also having more than one in the game may be an even better way of ensuring that cost are kept down. This is another area that requires further close examination before deciding what to do.

 
A more important consideration

Overall it is still likely that a single-vendor solution is cheaper than a multi-vendor one, but I hope that I have raised enough points to make you think that this is not guaranteed. Also the cost differential may not be as substantial as might be thought initially. You should certainly explore both approaches and figure out what works best for you. However there is another overriding point to consider here, the one I alluded to earlier; your users. The most important thing is that your users have the best experience and that whatever tools you employ are the ones that will deliver this. If you can do this while sticking to a single vendor then great. However if your users will be better served by different tools in different tiers, then this should be your approach, regardless of whether it makes things a bit more complicated for your team.

Of course there may be some additional costs associated with such an approach, but I doubt that this issue is insuperable. One comparison that it may help to keep in mind is that the per user cost of many BI tools is similar to desktop productivity tools such as Office. The main expense of BI programmes is not the tools that you use to deliver information, but all the work that goes on behind the scenes to ensure that it is the right information, at the right time and with the appropriate degree of accuracy. The big chunks of BI project costs are located in the four pillars that I consistently refer to:

  1. Understand the important business decisions and what figures are necessary to support these.
  2. Understand the data available in the organisation, how it relates to other data and to business decisions.
  3. Transform the data to provide information answering business questions.
  4. Focus on embedding the use of information in the corporate DNA.

The cost of the BI tools themselves are only a minor part of the above (see also, BI implementations are like icebergs). Of course any savings made on tools may make funds available for other parts of the project. It is however important not to cut your nose off to spite your face here. Picking right tools for the job, be they from one vendor or two (or even three at a push) will be much more important to the overall payback of your project than saving a few nickels and dimes by sticking to a one-vendor strategy just for the sake of it.
 

 
Continue reading about this area in: Using multiple business intelligence tools in an implementation – Part II
 

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Posted by Peter Thomas

Automating the business intelligence process?

14 May 2009
Balanced Insight Merv Adrian - IT Market Strategies for Suppliers
Balanced Insight Merv Adrian

 
 
Introduction

I enjoy reading the thoughts of vastly experienced industry analyst Merv Adrian on his blog, Market Strategies for IT Suppliers, and also on twitter via @merv. Merv covers industry trends and a wide variety of emerging and established technologies and companies. I would encourage you to subscribe to his RSS feed.

In a recent artcile, Balanced Insight – Automating BI Design to Deployment, Merv reviews the Consensus tool and approach developed by Ohio-based outfit Balanced Insight. I suggest that you read Merv’s thoughts first as I won’t unnecessarily repeat a lot of what he says here. His article also has links to a couple of presentations featuring the use of Consensus to build both Cognos 8 and Proclarity prototypes, which are interesting viewing.
 
 
An overview of Balanced Insight

Disclaimer: I haven’t been the beneficiary of a briefing from Balanced Insight, and so my thoughts are based solely on watching their demos, some information from their site and – of course – Merv’s helpful article.

The company certainly sets expectations high with the strap line of their web site:

Agile & Aligned Business Intelligence - With Balanced Insight Consensus® deliver in half the time without compromising cross project alignment.

Promising to “deliver in half the time without compromising cross project alignment” is a major claim and something that I will try to pay close attention to later.

The presentations / demonstrations start with a set-up of a fictional company (different ones in different demos) who want to find out more about issues in their business: outstanding receivables, or profit margins [Disclosure: the fact that the second demo included margins on mountain bikes initially endeared me to the company]. In considering these challenges, Balanced Insight offers the following slide contrasting IT’s typical response with the, presumably superior, one taken by them:

IT's approach to information problems vs Balanced Insight's

IT's approach to information problems vs Balanced Insight's

I agree with Balanced Insight’s recommendation, but rather take issue with the assumption that IT always starts by looking exclusively at data when asked to partake in information-based initiatives. I have outlined what I see as the four main pillars of a business intelligence project at many places on this blog, most recently in the middle of my piece on Business Intelligence Competency Centres. While of course it is imperative to understand the available data (what would be the alternative?), the first step in any BI project is to understand the business issues and, in particular, the questions that the business wants an answer to. If you search the web for BI case studies or methodologies, I can’t imagine many of these suggesting anything other than Balanced Insight’s recommended approach.

Moving on, the next stage of both the demos introduces the company’s “information packages”. These are panes holding business entities and have two parts; the upper half contains “Topics and Categories” (things such as date or product), the bottom half contains measurements. The “Topics and Categories” can be organised into hierarchies, for example: day is within week, which is within month, quarter and year. At this point most BI professionals will realise that “Topics and Categories” are what we all call “Dimensions” – but maybe Balanced Insight have a point picking a less technical-sounding name. So what the “information package” consists of is a list of measures and dimensions pertaining to a particular subject area – it is essentially a loose specification for a data mart.

The interesting point is what happens next, the Consensus Integrator uses the “information package” to generate what the vendor claims is an optimised star-schema database (in a variety of databases). It then creates a pre-built prototype that references the schema; this can be in a selection of different BI tools. From what I can tell from the demos, the second stage appears to consist of creating an XML file that is then read by the BI tool. In the first example, the “Topics and Categories” become dimensions in Cognos AnalysisStudio and the measures remain measures. In both demos sample data is initially used, but in the ProClarity one a version with full data is also shown – it is unclear whether this was populated via Consensus or not. The “information package” can also be exported to data modelling tools such as ERwin.

One of the Balanced Insight presentations then mentions that “all that’s left to do is then to develop your ETL”. I appreciate that it is difficult to go into everything in detail in a short presentation, but this does rather seem to be glossing over a major area, indeed one of my four pillars of BI projects referred to above. Such rather off-hand comments do not exactly engender confidence. If there is a better story to tell here, then Balanced Insight’s presentations should try to tell it.
 
 
The main themes

There are a few ideas operating here. First that Balanced Insight’s tools can support a process which will promote best practice in defining and documenting the requirements of a BI project and allow a strong degree of user interaction. Second that the same tools can quickly and easily produce functioning prototypes that can be used to refine these same requirements and also make discussions with business stakeholders more concrete. Finally that the prototypes can employ a variety of database and BI tools – so maybe you prototype on a cheap / free database and BI tool, then implement on a more expensive, and industrial strength, combination later.

Balanced Insight suggest that their product helps to address “the communication gap between IT and the business”. I think it is interesting using the “information package” as a document repository, which may be helpful at other stages of the project. But there are other ways of achieving this as well. How business friendly these are probably depends on how the BI team set them up. I have seen Excel and small Access databases work well without even buying a specific tool. Also I think that if a BI team needs a tool to ensure it sticks to a good process, then there is probably a bigger problem to worry about.

Of course, the production of regular prototypes is a key technique to employ in any BI project and it seems that Balanced Insight may be on to something here, particularly if the way that their “information package” presents subject areas makes it easier for the BI team and business people to discuss things. However, it is not that arduous to develop prototypes directly in most BI tools. To put this in a context drawn from my own experience, building Cognos cubes to illustrate the latest iteration of business requirement gathering was often a matter of minutes, compared to business analysts putting in many days of hard work before this stage.

Having decided to use Consensus to capture information about measures and dimensions, the ability to then transfer these to a range of BI tools in interesting. This may offer the opportunity to change tools during the initial stages of the project and to try out different tools with the same schema and data to assess their effectiveness. This may also be something that is a useful tool when negotiating with BI vendors. However, again I am not sure exactly how big of a deal this is. I would be interested in better understanding how users have taken advantage of this feature.
 
 
A potential fly in the ointment

It would be easy to offer a couple of other criticisms of the approach laid out in the demos; namely that it seems to be targeted at developing point solutions rather than a pervasive BI architecture and that (presumably related to this) the examples shown are very basic. However, I’m willing to given them the benefit of the doubt, a sales pitch is probably not the place for a lengthy exploration of broad and complex issues. So I think my overall response to Balanced Insight’s Consensus product could be summed up as guardedly positive.

Nevertheless, there is one thing that rather worries me and this can best be seen by looking at the picture below. [As per the disclaimer above, the following diagram is based on my own understanding of the product and has not been provided by Balanced Insight.]

My perception of how Balanced Insight addresses needs for information

My perception of how Balanced Insight addresses needs for information

I think I understand the single black arrow on the right of the diagram, I’m struggling to work out what Consensus offers (aside from documentation) for the two black arrows on the left hand side. Despite the fact that Balanced Insight disparaged the approach of looking at available data in their presentation, there is no escaping the fact that some one will have to do this at some point. Connections will then have to be made between the available data and the business questions that need answering.

In both demos Consensus is pre-populated with dimensions, measures and linkages of these to sample data. How this happens is not covered, but this is a key area for any BI project. Unless Balanced Insight have some deus ex machina that helps to cut the length of this stage, then I begin to become a little sceptical about their claim to halve the duration of BI work.

Of course my concerns could be unfounded. It will be interesting to see how things develop for the company and whether their bold claims stand the test of time.
 

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Posted by Peter Thomas

Maureen Clarry stresses the need for change skills in business intelligence on BeyeNetwork

12 May 2009

The article

beyenetwork2

Maureen Clarry begins her latest BeyeNETWORK article, Leading Change in Business Intelligence, by stating:

If there was a standard list of core competencies for leaders of business intelligence (BI) initiatives, the ability to manage complex change should be near the top of the list.

I strongly concur with Maureen’s observation and indeed the confluence of BI and change management is a major theme of this blog; as well as the title of one of my articles on the subject. Maureen clearly makes the case that “business intelligence is central to supporting [...] organizational changes” and then spends some time on Prosci’s ADKAR model for leading change; bringing this deftly back into the BI sphere. Her closing thoughts are that such a framework can help a lot in driving the success of a BI project.
 
 
My reflections

I find it immensely encouraging that an increasing number of BI professionals and consultants are acknowledging the major role that change plays in our industry and in the success of our projects. In fact it is hard to find some one who has run a truly successful BI project without paying a lot of attention to how better information will drive different behaviour – if it fails to do this, then “why bother?” as Maureen succinctly puts it.

Without describing it as anything so grand as a framework, I have put together a trilogy of articles on the subject of driving cultural transformation via BI. These are as follows:

• Marketing Change
• Education and cultural transformation
• Sustaining Cultural Change

However the good news about many BI professionals and consultants embracing change management as a necessary discipline does not seem to have filtered through to all quarters of the IT world. Many people in senior roles still seem to see BI as just another technology area. This observation is born out of the multitude of BI management roles that request an intimate knowledge of specific technology stacks. These tend to make only a passing reference to experience of the industry in question and only very infrequently mention the change management aspects of BI at all.

Of course there are counterexamples, but the main exceptions to this trend seem to be where BI is part of a more business focused area, maybe Strategic Change, or the Change Management Office. Here it would be surprising if change management skills were not stressed. When BI is part of IT it seems that the list of requirements tends to be very technology focussed.

In an earlier article, BI implementations are like icebergs I argued that, in BI projects, the technology – at least in the shape of front-end slice-and-dice tools – is not nearly as important as understanding the key business questions that need to be answered and the data available to answer them with. In “All that glisters is not gold” – some thoughts on dashboards, I made similar points about this aspect of BI technology.

I am not alone in holding these opinions, many of the BI consultants and experienced BI managers that I speak to feel the same way. Given this, why is there the disconnect that I refer to above? It is a reasonable assumption that when a company is looking to set up a new BI department within IT, it is the CIO who sets the tone. Does this lead us inescapably to the the conclusion that many CIOs just don’t get BI?

I hope that this is not the case, but I see increasing evidence that there may be a problem. I suppose the sliver lining to this cloud is that, while such attitudes exist, they will lead to opportunities for more enlightened outfits, such as the one fronted by Maureen Clarry. However it would be even better to see the ideas that Maureen espouses moving into the mainstream thinking of corporate IT.
 

 
Maureen Clarry is the Founder and President/CEO of CONNECT: The Knowledge Network, a consulting firm that specializes in helping IT people and organizations to achieve their strategic potential in business. CONNECT was recognized as the 2000 South Metro Denver Small Business of the Year and has been listed in the Top 25 Women-Owned Businesses and the Top 150 Privately Owned Businesses in Colorado. Maureen also participates on the Data Warehousing Advisory Board for The Daniels College of Business at the University of Denver and was recognized by the Denver Business Journal as one of Denver’s Top Women Business Leaders in 2004. She has been on the faculty of The Data Warehousing Institute since 1997, has spoken at numerous other seminars, and has published several articles and white papers. Maureen regularly consults and teaches on organizational and leadership issues related to information technology, business intelligence and business.
 

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Posted by Peter Thomas

Two pictures paint a thousand words…

29 April 2009
IT / Business Alignment

IT / Business Alignment

versus

IT / Business Integration

IT / Business Integration

Which is more likely to lead to sustained success?
 

 
See also: Business is from Mars and IT is from Venus and The scope of IT’s responsibility when businesses go bad.
 
Note: I have just had it pointed out to me that I missed out HR from the above diagrams. I hope that none of the HR professionals who read this blog will be too offended by my oversight.
 

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Posted by Peter Thomas

The scope of IT’s responsibility when businesses go bad

27 April 2009
linkedin Chief Information Officer (CIO) Network

This article is another relating to a discussion on LinkedIn.com. As with my earlier piece, Short-term “Trouble for Big Business Intelligence Vendors” may lead to longer-term advantage, this was posted on the Chief Information Officer (CIO) Network group

The thread was initiated by Patrick Gray and was entitled: Is IT partially to blame for the financial crisis? (as ever you need to be a member of LinkedIn.com and the group to view this).

Business Failure

Patrick asked:

Information is one of the key components of any IT organization (I would personally argue it’s more important than the technology aspect). Two facts disturb me when one looks at IT’s role in the financial crisis:

1) We in IT have been pushing data warehouse and business intelligence technology for years, saying these technologies should allow for “proactive” decision making at all levels of an organization, and an ability to spot trends and changes in a business’ underlying financial health.

2) The finance industry is usually spends more on IT than any other industry.

This being the case, if BI actually does what we’ve pitched it to do, shouldn’t one of these fancy analytical tools spotted the underlying roots of the financial crisis in at least one major bank? Is IT partially culpable for either not looking at the right data, or selling a bill of goods in terms of the “intelligence” aspect of BI?

I have written elsewhere on LinkedIn.com about business intelligence’s role in the financial crisis. My general take is that if the people who were committing organisations to collateralised debt obligations and other even more esoteric assent-backed securities were unable (or unwilling) to understand precisely the nature of the exposure that they were taking on, then how could this be reflected in BI systems. Good BI systems reflect business realities and risk is one of those realities. However if risk is as ill-understood as it appears to have been in many financial organisations, then it is difficult to see how BI (or indeed it’s sister area of business analytics) could have shed light where the layers of cobwebs were so dense.

So far, so orthodox, but Patrick’s question got me thinking along a different line, one that is more closely related to the ideas that I propounded in Business is from Mars and IT is from Venus last year. I started wondering, ‘is it just too easy for IT to say, “the business people did not understand the risks, so how were we expected to?”?’ (I think I have that punctuation right, but would welcome corrections from any experts reading this). This rather amorphous feeling was given some substance when I read some of the other responses.

However, I don’t want to focus too much on any one comment. My approach will be instead to take a more personal angle and describe some of the thoughts that the comments provoked in me (I am using “provoked” here in a positive sense, maybe “inspired” would have been a better choice of word). If you want to read my comments with the full context, then please click on the link above. What I am going to do here is to present some excerpts from each of my two lengthier contributions. The first of these is as follows (please note that I have also corrected a couple of typos and grammatical infelicities):

Rather than being defensive, and as a BI professional I would probably have every right to be so, I think that Patrick has at least half a point. If some organisations had avoided problems (or mitigated their impact) through the use of good BI (note the adjective) in the current climate, then BI people (me included) would rush to say how much we had contributed. I have certainly done this when the BI systems that I have implemented helped an organisation to swing from record losses to record profits.

Well if we are happy to do this, then we have to take some responsibility when things don’t go so well. It worries me when IT people say that non-IT managers are accountable for the business and IT is just accountable for IT. Surely in a well-functioning organisation, IT is one department that shares responsibility for business success with all the other front-line and service departments.

I have seen it argued with respect to failed financial institutions that IT can only provide information and that other executives take decisions. Well if this is the case, then I question how well the information has been designed to meet business needs and to drive decisions. To me this is evidence of bad BI (note the adjective again).

There are some specific mitigating factors for IT within the current climate, including poor internal (non-IT) governance and the fact that even the people who were writing some financial instruments did not understand the potential liabilities that the we taking on. If this is the case, then how can such risk be rolled up meaningfully? However these factors do not fully exculpate IT in my opinion. I am not suggesting for a second that IT take prime responsibility, but to claim no responsibility whatsoever is invidious.

So yes either poor information, or a lack of information (both of which are IT’s fault – as well as that of non-IT business folk) are a contributory factors to the current problems.

Also, while IT managers see themselves as responsible only for some collateral department, semi-detached from the rest of the business, we will see poor IT and poor information continuing to contribute to business failure.

This is the second passage:

[...]

I just wonder how it is that IT people at such firms can say that any failures are 100% nothing to do with them, as opposed to say 1% responsibility, or something of that nature.

Part of the role of professionals working in BI is to change the organisation so that numerical decision making (backed up of course by many other things, including experience and judgement) becomes part of the DNA. We are to blame for this not being the case in many organisations and can’t simply throw our hands up and say “wasn’t me”.

[...]

I will freely admit that there was a large dose of Devil’s Advocate in my two responses. As I have stated at the beginning of this piece, I am not so masochistic to believe that IT caused the current financial crisis, however I do not think that IT can be fully absolved of all blame.

My concerns about IT’s role relate to the situation that I see in some companies where IT is a department set apart, rather than being a central part of the overall business. In this type of circumstance (which is perhaps more common than anyone would like to think), the success of the IT and the non-IT parts of the business are decoupled.

Under these arrangements, it would be feasible for IT to be successful and the business to suffer major losses, or for the business to post record profits while IT fails to deliver projects. Of couse such decoupling can happen in other areas; for example Product A could have a stellar year, while Product B fails miserably – the same could happen with countries or regions. However there is something else here, a sense that IT can sometimes be an organisation within an organisation, in a way that other service departments generally are not.

Rather than expanding further on this concept here, I recommend you read Jim Anderson’s excellent article Here’s What’s Really Wrong With IT And How To Fix It on his blog, The Business of IT. I think that there is a good deal of alignment between Jim and I on this issue; indeed I was very encouraged to find his blog and see that his views were not a million miles from my own.

I would also like to thank Patrick for posting his initial question. It’s good when on-line forums lead you to take an alternative perspective on things.
 

 
Continue reading about this area in: Two pictures paint a thousand words… and “Why taking a few punches on the financial crisis just might save IT” by Patrick Gray on TechRepublic.

Also check out Jill Dyché’s article: Dear IT: A Letter from Your Business Users
 

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Posted by Peter Thomas

The latest and greatest versus the valuable

20 April 2009

A World of Bytes by Curt Monash

This article expands on some comments I made on Curt Monash‘s latest blog posting: Why the basically good choice of Aneesh Chopra for US CTO scares the bejeesus out of me. In this, Curt argues that:

[the new US government CIO and CTO may be] so focused on shiny new technologies that they won’t address some of the devastatingly critical challenges of government IT.

Curt then goes on to list some of the important areas that he is concerned will not recieve enough attention. Although Curt’s piece was directed at a very specific area, I think that it raises some general questions. Here are the comments that I made on his blog:

“As you allude to, one of the main problems that IT faces is its focus on the new and shiny, sometimes to the exclusion of the older, but more worthy. I’m by no means a technology Luddite, progress is to be desired, but there has to be some reason for it; something beyond just being neat.

This is a double-headed monster in my opinion. First IT types like me are often drawn to the new and sexy – maybe that’s why we got into the business in the first place. Second, the flashy – particularly when it makes it to general business publications, can generate a “me too” attitude in senior executives, sometimes deflecting IT attention from less glamorous, but more necessary work.

As with most things in life, a balance between both elements of IT is probably what is most necessary.”

I have touched on this area already a couple of times. It was one of the issues that I identified in Problems associated with the IT cycle, where I said:

“On top of this we can add some attributes of IT staff which, although generally desirable, can have a downside as well. Many IT people want to be involved in the latest and greatest technology – this is not always what is going to add most value to the business.”

Also, much of my article about dashboards relates to this issue, as may be deduced by the title: “All that glisters is not gold” – some thoughts on dashboards. In this I comment:

“[...] echoing my comments on BI tools in general, I think an attractive looking dashboard is really only the icing on the cake. The cake itself has two main other ingredients:

  1. The actual figures that it presents (and how well they have been chosen) and
  2. The Information Architecture that underpins them”

Making what I realise is something of a bold leap here, I think that this fascination with the new and technically cool is one reason that IT managers sometimes feel left out of the inner circle of executives of an organisation. In some people’s minds (sometimes those of influential people) IT is too readily associated with Sci-Fi conventions, comic books and and pocket protectors (with of course my apologies in advance to devotees of each of these). This may seem a trivial point, but such associations sometimes run deep; everyone loves a good stereotype.

Of course there are many business-focussed IT managers out there striving to deliver value for their organisations, to boost sales, or reach new customers, or reduce costs; I have been one of them myself. But these industrious individuals are sometimes still seen through the “geek” prism I have described above. Maybe it is only by focsuing more established technologies, ones that demonstrably add business value, that the profession will be able to throw off this yoke.

Although I am rather fond of using quotations on this blog, it is not typical for me to cite religious texts. However, maybe St. Paul had IT in mind when he wrote:

“When I was a child, I spake as a child, I understood as a child, I thought as a child: but when I became a man, I put away childish things.”

While the IT leads of the US government can be accused of too great a focus on what many might view as childish things, then it seems that we still have some way to go.
 

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Posted by Peter Thomas

Some thoughts on IT-Business Alignment from the Chase Zander IT Director Forum

27 March 2009

This Chase Zander seminar, which I earlier previewed on this site, took place yesterday evening in Birmingham. There was a full house of 20 plus IT Directors, CIOs and other senior IT managers who all engaged fully in some very stimulating and lively discussions.

As I previously mentioned, our intention in this meeting was to encourage debate and sharing of experiences and best practice between the delegates. My role was to faciliate the first session, focussed on IT-Business alignment. I started by sharing a few slides with that group that explained the research we had conducted to determine the content of the forum.

Click to view the introductory presentation

Click to view the introductory presentation as a PDF

After sharing what in my opinion was a not wholly satisfactory definition of IT-Business alignment, I opened up the floor to a discussion of what IT-Business alignment actually was and why it mattered. We used some of the other slides later in the meeting, but most of the rest of the evening was devoted to interaction between the delegates. Indeed the ensuing conversations were so wide ranging that the theme was also carried over to the second session, hosted by my associate Elliot Limb.

Territory initially covered included the suggestion that IT should be an integral part of the business, rather than a separate entity aligned to it (a theme that I covered in my earlier article Business is from Mars and IT is from Venus, which interestingly I penned after a previous Chase Zander forum, this one focussed on change management). The group also made a strong connection between IT-Business alignment and trust. A count of hands in response to the question “do you feel that you have the 100% unqualified confidence of your CEO?” revealed a mixed response and we tried to learn from the experiences of those who responded positively.

The relationship between IT and change was also debated. Some felt that IT, with its experience of project-based work, was ideally placed to drive change in organisations. Others believed that change should be a business function, with IT sticking to its more traditional role. Different organisations were in different places with respect to this issue – one attendee had indeed seen his current organisation take both approaches in the recent past. It was also agreed that there were different types of change: positive change in reaction to some threat or opportunity and the less positive change for change’s sake that can sometimes affect organisations.

Suggestions for enhancing IT-Business alignment included: being very transparent about IT service level agreements and trends in them; focussing more on relationships with senior managers, the CEO and CFO in particular; better calculating the cost of IT activities (including business resource) and using this to prioritise and even directly charge for IT services; applying marketing techniques to IT; learning to better manage business expectations, taking on more realistic workloads and knowing when to say ‘no’; and paying more attention to business processes, particularly via capability maturity modelling.

It was agreed that it generally took quite some time to establish trust between a CIO and the rest of the senior management team. This might be done by initially sorting out problems on the delivery and support side and, only once confidence had been built up, would the CIO be able to focus more on strategic and high value-added activities. This process was not always aided by the not atypical 3-5 year tenure of CIOs.

Later discussions also touched on whether CIOs would generally expect (or want to) become CEOs and, if not, why was this the case. The perspective of both the delegates and the Chase Zander staff was very interesting on this point. There was a degree of consensus formed around the statement that IT people liked taking on challenging problems, sorting them out and then moving on to the next one. While there was some overlap between this perspective and the role of a CEO in both having their hand on the tiller of an organisation and challenging the management team to meet stretch goals, there was less than a perfect fit. Maybe this factor indicated something of a different mindset in many IT professionals.

In the context of forming better relationships with business managers and IT trying to be less transactional in its dealings with other areas, the question of why there were so few women in senior IT positions also came up. This is a large topic that could spawn an entire forum in its own right.

Overall the meeting was judged to be a success. From my perspective it was also interesting to meet a good cross-section of IT professionals working in different industries and to talk about both what the different challenges that we faced and what we had in common.
 

 
Continue reading about this area in: The scope of IT’s responsibility when businesses go bad
 

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Posted by Peter Thomas

Tactical Meandering

25 March 2009

Meanders
 

  tactics /táktiks/ n.pl. 2 a the plans and means adopted in carrying out a scheme or achieving some end. (O.E.D.)  
 
  meander /miándər/ n. 1 a a curve in a winding river etc. b a crooked or winding path or passage. (O.E.D.)  

 
I was reminded of the expression “tactical meandering”, which I used to use quite a bit, by a thread on the LinkedIn.com Business Intelligence Group forum. The title of this was Is BI recession-proof? (as always, you need to be a member of both LinkedIn.com and the group to view this).

The conversation on the thread turned to the fact that, in the current economic climate, there may be less focus on major, strategic BI initiatives and more on quick, tactical ones that address urgent business needs.

My take on this is that it is a perfectly respectable approach, indeed it is one that works pretty well in my experience regardless of the economic climate. There is however one proviso, that the short-term work is carried out with one eye on a vision of what the future BI landscape will look like. Of course this assumes that you have developed such a vision in the first place, but if you haven’t why are you talking about business intelligence when report writing is probably what you are engaged in (regardless of how fancy the tools may be that you are using to deliver these).

I talked about this specific area extensively in my earlier article, Holistic vs Incremental approaches to BI and also offered some more general thoughts in Vision vs Pragmatism. In keeping with the latter piece, and although the initial discussions referred to above related to BI, I wanted to use this article to expand the scope to some other sorts of IT projects (and maybe to some non-IT projects as well).

Some might argue (as people did on the LinkedIn.com thread) that all tactical work has to be 100% complementary to you strategic efforts. I would not be so absolute. To me you can wander quite some way from your central goals if it makes sense to do so in order to meet pressing business requirements in a timely and cost-effective manner. The issue is not so much how far you diverge from your established medium-term objectives, but that you always bear these in mind in your work. Doing something that is totally incompatible with your strategic work and even detracts from it may not be sensible (though it may sometimes still be necessary), but delivering value by being responsive to current priorities demonstrates your flexibility and business acumen; two characteristics that you probably want people to associate with you and your team.

Tactical meandering sums up the approach pretty well in my opinion. A river can wander a long way from a line drawn from its source to its mouth. Sometimes it can bend a long way back on itself in order to negotiate some obstacle. However, the ultimate destination is set and progress towards it continues, even if this is sometimes tortuous.

Oxbow Lake Formation

Oxbow Lake Formation

Expanding on the geographic analogy, sometimes meanders become so extreme that the river joins back to its main course, cutting off the loop and leaving an oxbow lake on one side. This is something that you will need to countenance in your projects. Sometimes an approach, or a technology, or a system was efficacious at a point in time but now needs to be dropped, allowing the project to move on. These eventualities are probably inevitable and the important thing is to flag up their likelihood in advance and to communicate clearly when they occur.

My experience is that, if you keep you strategic direction in mind, the sum of a number of tactical meanders can advance you quite some way towards your goals; importantly adding value at each step. The quickest path from A to B is not always a straight line.
 

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Posted by Peter Thomas

The specific benefits of business intelligence in Insurance

24 March 2009

Introduction

Insurance

Insurance – specifically Property Casualty Insurance – is the industry that I have worked within for the last twelve years. During this time, I managed teams spanning IT, Finance and Operations. However the successes that I am most proud of have been in the related fields of Business Intelligence and Cultural Transformation that appear in the title of this blog.

I have described various aspects of this work elsewhere, for example in The EMIR Project and my collection of articles on Cultural Transformation. I have also written about the general benefits of good Business Intelligence for any organisation. This article focuses on the business benefits of BI that are specific to the Insurance industry.
 
 
Of pigs and men

  Insure /insho′or/ v.tr. 1 secure the payment of a sum of money in the event of loss or damage to property, life a person etc. (O.E.D.)  

Insurance is all about risk; evaluating risk, transferring risk, reducing risk. The essentials of the industry can be appreciated via a rather colourful fable provided in Success in Insurance (S.R. Diacon and R.L. Carter). This tale was originally told by someone at The Association of British Insurers:

Once upon a time there were 11 men; each of them owned a pig.

Unexpectedly one of the pigs died. The owner could not afford £90 for a new pig and so he had to leave the country and go to work in the town instead. The remaining 10 men went to see a wise man. ‘It could happen to any of us,’ they said. ‘What can we do?’

‘Could you each afford £10 for a new pig if your pig died?’ asked the wise man. They all agreed that they could manage that. ‘Very well,’ said the wise man. ‘If you each give me £10, I’ll buy you a pig if yours dies this year.’ They all agreed.

That year one pig did die. The price of pigs had gone up to £95 by now, but the wise man replaced the pig, so none of the men suffered and the wise man had £5 left for the trouble and risk he had taken.

 
 
Pricing Insurance products

Pricing

Of course in the above example, there were two crucial factors for the wise man. First the outcome that only one pig actually died; if instead there had been two pig-related fatalities, the perhaps less-wise man would have been out-of-pocket by £90. Second, the related issue of him setting the price of the pig Insurance policy at £10; if it had been set at £9 he would again have suffered a loss. It is clear that it takes a wise man to make accurate predictions about future events and charge accordingly. In essence this is one thing that makes Insurance different to many other areas of business.

If you work in manufacturing, your job will of course have many challenges, but determining how much it costs to make one of your products should not be one of them. The constituent costs are mostly known and relatively easy to add up. They might include things such as: raw materials and parts; factory space and machinery; energy; staff salaries and benefits; marketing and advertising; and distribution. Knowing these amounts, it should be possible to price a product in such a way that revenue from sales normally exceeds costs of production.

In Insurance a very large part of the cost of production is, by definition, not known at the point at which prices are set. This is the amount that will eventually be paid out in claims; how many new pigs will need to be bought in the example above. If you consider areas such as asbestosis, it can immediately be seen that the cost of Insurance policies may be spread over many years or even decades. The only way to predict the eventual costs of an Insurance product with any degree of confidence, and thereby set its price, is to rely upon historical information to make informed predictions about future claims activity.

By itself, this aspect of Insurance places enormous emphasis on the availability of quality information to drive decisions, but there are other aspects of Insurance that reinforce this basic need.
 
 
Distribution strategy

Insurance Broker

In most areas of commerce the issue of how you get your product to market is a very important one. In Insurance, there are a range of questions in this area. Do you work with brokers or direct with customers? Do you partner with a third party – e.g. a bank, a supermarket or an association – to reach their customers?

Even for Insurance companies that mostly or exclusively work with brokers, which brokers? The broker community is diverse ranging from the large multinational brokers; to middle-sized organisations, that are nevertheless players in a given country or line of business; and to small independent brokers, with a given specialism or access to a niche market. Which segment should an Insurance company operate with, or should it deal with all sectors, but in different ways?

The way to determine an effective broker strategy is again through information about how these relationships have performed and in which ways they are trending. Sharing elements of this type of high-quality information with brokers (of course just about the business placed with them) is also a good way to deepen business relationships and positions the Insurer as a company that really understands the risks that it is underwriting.
 
 
Changing risks

The changing face of risk

The changing face of risk

At the beginning of this article I stated that Insurance is all about risk. As in the pig fable, it is about policy holders reducing their risk by transferring this to an Insurance company that pools these with other risks. External factors can impinge on this risk transfer. Hurricane season is is always a time of concern for Insurance companies with US property exposures, but over the last few years we have had our share of weather-related problems in Europe as well. The area of climate change is one that directly impinges upon Insurers and better understanding its potential impact is a major challenge for them.

With markets, companies, supply-chains and even labour becoming more global, Insurance programmes increasingly cover multiple countries and Insurance companies need to be present in more places (generally a policy covering risks in a country has to be written by a company – or subsidiary – based in that country). This means that Insurance professionals can depend less on first-hand experience of risks that may be on the other side of the world and instead need reliable and consistent information about trends in books of business.

The increasingly global aspect of Insurance also brings into focus different legal and regulatory regimes, which both directly impinge on Insurers and change the profile of risks faced by their customers. As we are experiencing in the current economic crisis, legal and regulatory regimes can sometimes change rapidly, altering exposures and impacting on pricing.

The present economic situation affects Insurance in the same ways that it does all companies, but there are also some specific Insurance challenges. First of all, with the value of companies declining in most markets, there is likely to be an uptick in litigation, leading to an increase in claims against Directors and Officers policies. Also falling property values mean that less Insurance is required to cover houses and factories, leading to a contraction in the market. Declining returns in equity and fixed income markets mean that one element of Insurance income – the return on premiums invested in the period between them being received and any claims being paid out – has become much less.

So shifts in climate, legal and regulatory regimes and economic conditions all present challenges in how risk is managed; further stressing the importance of excellent business intelligence in Insurnace.
 
 
The Insurance Cycle

If this litany of problems was not enough to convince the reader of the necessity of good information in Insurance, there is one further issue which makes managing all of the above issues even more complex. This is the fact that Insurance is a cyclical industry.

An example of The Insurance Cycle

An example of The Insurance Cycle

The above chart (which I put together based on data from Tillinghast) shows the performance of the London Marine Insurance market as a whole between 1985 to 2002. If you picked any other market in any other location, you would get a similar sinusoidal curve, though there might well be phase differences as the cycles for different types of Insurance are not all in lock-step.

To help readers without a background in Insurance, the ratio displayed is essentially a measure of the amount of money going out of an Insurance Company (mostly its operating expenses plus claims) divided by the amount of money coming in (mostly Insurance premiums). This is called the combined ratio. A combined ratio less than 100% broadly indicates a profit and one above 100% broadly indicates a loss.

It may be seen that the London Marine market as a whole has swung from profit to loss, to profit, to loss and back to profit over these 18 years. This article won’t cover the drivers of this phenomenon in any detail, but one factor is that when profits are being made, more capital is sucked into the market, which increases capacity, drives down costs and eventually erodes profitability. As with many things in life rather than stopping at break-even, this process overshoots resulting in losses and the withdrawal of capital. Prices then rise and profitability returns, starting a new cycle.

Given this environmental background to the Insurance business, it is obvious that it is very important to an Insurance company to work out its whereabouts in the cycle at any time. It is particularly crucial to anticipate turning points because this is when corporate strategies may need to change very rapidly. There may be a great opportunity for defence to change to attack, alternatively a previously expansionary strategy may need to be reined in order to weather a more trying business climate.

In order to make predictions about the future direction of the cycle, there is no substitute for having good information and using this to make sound analyses.
 
 
Summary

I hope that the article has managed to convey some of the special challenges faced by Insurance companies and why many of these dramatically increase the value of good business intelligence.

Essentially Insurance is all about making good decisions. Should I underwrite this newly presented risk? Should I renew an existing policy or not? What price should I set for a policy? When should I walk away from business? When should I aggressively expand? All of these decisions are wholly dependent on having high-quality information and because of this business intelligence can have an even greater leverage in Insurance than in other areas of industry.

Given this it is not unreasonable to state in closing that while good information is essential to any organisation, it is the very lifeblood of an Insurance company. My experience is that Business Intelligence offers the best way to meet these pressing business needs.
 

 
You can read more about my thoughts on Business Intelligence and Insurance in:

  1. Using historical data to justify BI investments – Part I
  2. Using historical data to justify BI investments – Part II
  3. Using historical data to justify BI investments – Part III

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5 Comments | bi and the economic crisis, business, business intelligence, enterprise performance management, it business alignment, management information, technology | Tagged: , , , , , , , | Permalink
Posted by Peter Thomas

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