“Involving users in business intelligence strategy key for success” – Christina Torode on SearchCio-Midmarket.com

Search CIO Midmarket Christina Torode

While browsing the, slightly idiosyncratically named, infoBOOM! Must-know people, ideas and opinions for mid-sized business group on LinkedIn.com today, I came across a link to an artcile about Business Intelligence on SearchCio-Midmarket.com (part of the TechTarget stable). This was by Christina Torode and is entitled, Involving users in business intelligence strategy key for success (please note that registration is required to read the full article, though this is a relatively painless process).

Christina cites the opinions of a number of industry experts and practitioners (as one would expect, the latter are mostly from the mid-market) in making her case, which is one that I pretty much agree with. These include: Boris Evelson at Forrester Research; Rob Fosnaugh, BI lead at Brotherhood Mutual Insurance Co.; and Chris Brady, CIO at Dealer Services Corp. The experiences of Rob and Chris in particular provide some useful pointers to techniques that may be appropriate for you to use in your own BI projects.

Commitment vs Involvement

I do however have one minor quibble. This is to do with the use of the word “involvement” in this context. Some of my concern may be explained by recourse to a dictionary.

  involve /invólv/ v.tr. 1 (often foll. by in) cause (a person or thing) to participate, or share the experience or effect (in a situation, activity, etc.). (O.E.D.)  

The point that I want to make is perhaps more clearly stated in the rather earthy adage about the difference between involvement and commitment relating to breakfast; this being that a chicken was involved with it, but a pig was committed to it.

To me involving business people in a BI project is not enough. It implies that IT is in the driving seat and that the project is essentially a technological one. Instead what I believe is required is a full partnership. I have written about the lengths that I have gone to in trying to achieve this in Scaling-up Performance Management and Developing an international BI strategy.

Aside: It is worth noting that the former of these articles covers a 9-month collaboration with 30 business people to define the overall BI needs of an insurance organisation in 13 European countries. This contrasts with a 2-month process at another (rather different) insurance organisation, Brotherhood Mutual, that Christina cites.

I should mention that the exercise I describe resulted in nine major reporting and analysis areas (chronologically: Profitability, Broker Management, Claims Management, Portfolio Management, Budget Management, Dashboard, Expense Management, Exposure Management and Service & Workflow) as opposed to a single one (Claims) at Brotherhood Mutual; so maybe the durations are comparable.

Either way the main lesson is that it takes time to get good requirements in BI.

The real-life examples that Christina mentions in her article seem to also lean a little more towards partnership / commitment than to involvement. It may seem that I am splitting hairs on this issue (maybe this is a byproduct of the things that I learnt about semantics yesterday), but I have seen BI projects fail to deliver on their promise specifically because the IT team became too internally focussed and lost touch with their business users after an initial (and probably inadequately thorough) requirement-gathering exercise.

Indeed I was once brought in to act as an internal consultant for a failing BI project and my main diagnosis was precisely that the business people were semi-detached from it. They had been “involved”, but this was never to a great degree and had also occurred some time in the past. My recommendation was ongoing and in-depth collaboration, to the degree that the BI team becomes a joint IT / business one with the distinctions between people’s roles blurring somewhat at the edges.

This partnership approach has worked for me (the results may be viewed here) and I have seen the lack of an IT / business partnership lead to failure in BI on a number of occasions. Rather than being the minor point I initially mentioned, I think that the difference between involvement and commitment can be make or break for a BI project.
 


 
Christina Torode has been a high tech journalist for more than a decade. Before joining TechTarget, she was a reporter for technology trade publication CRN covering a variety of beats from security and networking to telcos and the channel. She also spent time as a business reporter and editor with Eagle Tribune Publishing in eastern Massachusetts. For SearchCIO.com and SearchCIO-Midmarket, Christina covers business applications and virtualization technologies.
 

“Does Business Intelligence Require Intelligent Business?” by George M. Tomko

CIO Rant George M Tomko

Introduction

George Tomko’s CIO Rant has been on my list of recommended sites for quite some time. I also follow George on twitter.com (http://twitter.com/gmtomko) and have always found his perspective on business and technology matters to be extremely interesting and informative.

George’s latest blog post is is on a subject that is clearly close to my heart and is entitled Does Business Intelligence Require Intelligent Business? I should also thank him for quoting my earlier artcile, Data – Information – Knowledge – Wisdom, in this. Being mentioned in the same breath as Einstein is always gratifying as well!

George acknowledges that this is something of a “What comes first – the chicken or the egg?” situation. He starts out by building on an article by Gerry Davis at Heidrick & Struggles to state:

  1. collecting [information about customers] is “easy”
  2. analyzing it is hard
  3. disseminating it is very hard

Kudos to the first reader to correctly identify the mountain

Both George and Gerry agreed that the mountains of data that many organisations compile are not always very effectively leveraged to yield information, let alone knowledge or wisdom. Gerry proposes:

identifying and appointing the right executive — someone with superb business acumen combined with a sound technical understanding — and tasking them with delivering real business intelligence

George assesses this approach through the prism of the the three points listed above and touches on the ever present challenges of business silos; agreeing that the type of executive that Gerry recommends appointing could be effective in acting across these. However he introduces a note of caution, suggesting that it may be more difficult than ever to kick-off cross-silo initiatives in today’s turbulent times.

I tend to agree with George on this point. Crises may deliver the spark necessary for corporate revolution and unblock previously sclerotic bureaucracies. However, they can equally yield a fortress mentality where views become more entrenched and any form or risk taking or change is frowned upon. The alternative is incrementalism, but as George points out, this is not likely to lead to a major improvement in the “IQ” of organisations (this is an area that I cover in more detail in Holistic vs Incremental approaches to BI).
 
 
The causality dilemma

Which came first?

Returning to George’s chicken and egg question, do intelligent enterprises build good business intelligence, or does good business intelligence lead to more intelligent enterprises? Any answer here is going to vary according to the organisations involved, their cultures, their appetites for change and the environmental challenges and evolutionary pressures that they face.

Having stated this caveat, my own experience is of an organisation that was smart enough to realise that it needed to take better decisions, but maybe not aware that business intelligence was a way to potentially address this. I spoke about this as one of three sceanrios in my recent artcile, “Why Business Intelligence projects fail”. Part of my role in this organisation (as well as building a BI team from scratch and developing a word-class information architecture) was to act as evangelist the benefits of BI.

The work that my team did in collaboration with a wide range of senior business people, helped an organisation to whole-heartedly embrace business intelligence as a vehicle to increasing its corporate “IQ”. Rather than having this outcome as a sole objective, this cultural transfomation had the significant practical impact of strongly contributing to a major business turn-around from record losses over four years, to record profits sustained over six. This is precisely the sort of result that well-designed, well-managed BI that addresses important business questions can (and indeed should) deliver.
 
 
Another sporting analogy

I suppose that it can be argued that only someone with a strong natural aptitude for a sport can become a true athlete. Regardless of their dedication and the amount of training they undertake, the best that lesser mortals can aspire to is plain proficiency. However, an alternative perspective is that it is easy enough to catalogue sportsmen and women who have failed to live up to their boundless potential, where perhaps less able contemporaries have succeeded through application and sheer bloody-minded determination.

I think the same can be said of the prerequisites for BI success and the benefits of successful BI. Organisations with a functioning structure, excellent people at all levels, good channels of communication and a clear sense of purpose are set up better to succeed in BI than their less exemplary competitors (for the same reason that they are set up better to do most things). However, with sufficient will-power (which may initially be centred in a very small group of people, hopefully expanding over time), I think that it is entirely possible for any organisation to improve what it knows about its business and the quality of the decisions it takes.

Good Business Intelligence is not necessarily the preserve of elite organisations – it is within the reach of all organisations who possess the minimum requirements of the vision to aspire to it and the determination to see things through.
 


 
George M. Tomko is CEO and Executive Consultant for Tomko Tek LLC, a company he founded in 2006. With over 30 years of professional experience in technology and business, at the practitioner and executive levels, Mr. Tomko’s goal is to bring game-changing knowledge and experience to client organizations from medium-size businesses to the multidivisional global enterprise.

Mr. Tomko and his networked associates specialize in transformational analysis and decision-making; planning and execution of enterprise-wide initiatives; outsourcing; strategic cost management; service-oriented business process management; virtualization; cloud computing; asset management; and technology investment assessment.

He can be reached at gtomko@tomkotek.com
 

“Why Business Intelligence projects fail”

Introduction

James Anderson bowls Sachin Tendulkar for 1 - England v India, 3rd Test, The Oval, August 12, 2007

In this blog, I have generally tried to focus on success factors for Business Intelligence programmes. I suppose this reflects my general character as something of an optimist. Of course failure can also be instructive; as the saying goes “we learn more from our mistakes than from our successes.” Given this, and indeed the Internet’s obsession with “x reasons why y fails”, I have also written on the subject of how Business Intelligence projects can go wrong a few times.

My first foray into this area was in response to coverage of the Gartner Business Intelligence Summit in Washington D.C. by Intelligent Enterprise. The article was entitled, “Gartner sees a big discrepancy between BI expectations and realities” – Intelligent Enterprise; I have always had a way with words!

Rather than simply picking holes in other people’s ideas on this topic, I then penned a more general piece, Some reasons why IT projects fail, which did what it said on the can. Incidentally I was clearly in the middle of a purple patch with respect to article headlines back then, I am trying to recapture some of these former titular glories in this piece.

So what has moved me to put fingertip to keyboard this time? Well my inspiration (if it can be so described) was, as has often been the case recently, some comments made on a LinkedIn.com forum. In breech of my customary practice, I am not going to identify the group, the discussion thread or the author of these comments, which were from a seasoned BI professional and were as follows:

Most BI projects fail because:

a) the business didn’t support it properly or
b) the business didn’t actually know what they wanted

I realise that I should be more emotionally mature about such matters, but comments such as these are rather like a red rag to a bull for me. Having allowed a few days for my blood pressure to return to normal, I’ll try to offer a dispassionate deconstruction of these suggestions, which I believe are not just incorrect, but dangerously wrong-headed. If the attitude of a BI professional is accurately reflected by the above quote, then I think that we need look no further for why some BI projects fail. Let’s look at both assertions in a little more detail.
 
 
What does “the business didn’t properly support [BI]” actually mean?

The British and Irish Lions scrum in South Africa - 1997

For a change I am going to put my habitual frustration at unhelpful distinctions between “the business” and “IT” to one side (if you want to read about my thoughts on this matter, then please take a look at the Business / IT Alignment and IT Strategy section of my Keynote Articles page).

To me there are three possible explanations here:

  1. The business did not need or want better information
  2. The business needed or wanted better information, initially supported the concept of BI delivering this, but their enthusiasm for this approach waned over time
  3. The business needed or wanted better information, but didn’t think that BI offered the way to deliver this

maybe there are some other possibilities, but hopefully the above covers all the bases. Here are some thoughts on each scenario:
 
 
1. The business did not need or want better information

So the rationale for starting a BI project was… ?

On a more serious note, there could be some valid reasons why a BI project would still make sense. First of all, it might be that a BI system could deliver the same information that is presently provided more cheaply. This could be the case where there are multiple different reporting systems, each needing IT care and support; where the technology that existing systems are based on is going out of support; or where BI is part of a general technology refresh or retrenchment (for example replacing fat client reporting tools with web-based ones, thereby enabling the retirement of multiple distributed servers and saving on the cost of people to maintain them). Of course it may well be IT that highlights the needs in these circumstances, but there should surely be a business case developed with some form or payback analysis or return on investment calculation. If these stand up, then an IT-centric BI project may be justifiable. While I would argue that such an approach is a wasted opportunity, if such an initiative is done properly (i.e. competently managed), then the the lack of business people driving the project should not be an obstacle to success.

Second, it could be that the business saw no need for better information, but IT (or possibly IT in conjunction with a numerate department such as Finance, Change or Strategy) does see one. While this observation is perhaps tinged with a little arrogance, one of IT’s roles should be to act as an educator, highlighting the potential benefits of technology and where they may add business advantage. Here my advice is not to start a BI project and hope that “if we build it, they will come”, but instead to engage with selected senior business people to explain what is possible and explore whether a technology such as BI can be of assistance. If this approach generates interest, then this can hopefully lead to enthusiasm with appropriate nurturing. Of course if the answer is still that the current information is perfectly adequate, then IT has no business trying to kick off a BI project by itself. If it does so, then accountability for its likely failure will be squarely (and fairly) laid at IT’s door.
 
 
2. The business needed or wanted better information, initially supported the concept of BI delivering this, but their enthusiasm for this approach waned over time

To me this sounds like a great opportunity that the BI team have failed to capitalise on. There is a pressing business need. There is a realisation that BI can meet this. Funding is allocated. A project is initiated. However, some where along the line, the BI team have lost their way.

Why would business enthusiasm wane? Most likely because delivery was delayed, no concrete results were seen for a long time, costs ballooned, the system didn’t live up to expectations, or something else happened that moved executive focus from this area. In the final case, then any responsible manager should be prepared to cut their coat according to their cloth. The BI team may feel that their project is all-important, but it is not inconceivable that another project would take precedence, for example integrating a merger.

Assuming that external events are not the reason for business disenchantment, then all of the other reasons are 100% the responsibility of the BI team themselves. BI projects are difficult to estimate accurately as I described in The importance of feasibility studies in business intelligence, but – as the same article explains – this is not an excuse for drastically inaccurate project plans or major cost overruns. Also the BI team should work hard at the beginning of the project to appropriately set expectations. As with any relationship, business or personal, the key to success is frequent and open communication.

Equally, BI projects often require a substantial amount of time to do well (anyone who tells you the opposite has never been involved with one or is trying to sell you something). This does not mean that the BI team should disappear for months (or years) on end. It is important to have a parallel stream of interim releases to address urgent business needs, provide evidence of progress and burnish the team’s credibility (I explore this area further in Holistic vs Incremental approaches to BI).

If the BI system delivered does not live up to expectations then there are two questions to be answered. In what way does it not meet expectations? and Why did it take until implementation to determine this? It could be that the functionality of the BI tool does not meet what is necessary, but most of these have a wide range of functionality and are at least reasonably intuitive to use. More likely the issue is in the information presented in the tool (which is not judged to be useful) or in an inadequate approach to implementation. The way to address both of these potential problems from the very start of the project is to follow the four-pillared approach that I recommend in many places on this blog; notably in one of the middle sections of Is outsourcing business intelligence a good idea?.

So rather than blaming the business for losing interest in BI, the BI team needs to consider where its own inadequacies have led to this problem. It is sometimes tempting to dwell on how no one really appreciates all of the hard work that us IT types do, but it is much more productive to try to figure out why this is and take steps to address the problem.
 
 
3.The business needed or wanted better information, but didn’t think that BI offered the way to deliver this

While I recognise some aspects of the first scenario above, this one is something that I am more intimately familiar with. Back in 2000, I was charged with improving the management information of a large organisation, in response to profitability issues that they were experiencing. No one mentioned data warehouses, or OLAP, or analytics. A business intelligence implementation was my response to the strategic business challenges that the organisation was facing. However I initially faced some scepticism. It was suggested that maybe I was over-engineering my approach (the phrase “we need a diesel submarine, not a nuclear one” being mentioned) when all that was required was a few tweaks to existing reports and writing some new ones.

First of all, a BI professional should welcome such challenges. Indeed they should continually ask the same questions of themselves and their team. If your proposed approach does not stand up to basic scrutiny with respect to cost effectiveness and timeliness, then you are doing a poor job. However good BI people will be able to answer such questions positively, having devised programmes and architectures that are appropriate for the challenges that they seek to meet. A BI solution should clearly not be more expensive than is needed, but equally it should not be cheaper, lest it fails to deliver anything.

A skill that is required in a situation such as the one I found myself in back in 2000 is to be able to lay out your vision and proposals in a way that is logical, compelling, attractive and succinct enough to engage business enthusiasm and engender the confidence of your potential stakeholders. In short you need to be able to sell. Maybe this is not a skill that all IT people have acquired over the years, but it is invaluable in establishing and maintaining project momentum (I cover the latter aspect of this area in three articles starting with Marketing Change).

Again, if the lead of the BI team is not able to properly explain why BI is the best way to meet the information needs of the organisation, then this is essentially the fault of the BI lead and not the business.
 
 
So far, the main conclusion that I have drawn is the same as in my earlier piece about the failure of BI projects. I closed this by stating:

I firmly believe that BI done well is both the easiest of IT systems to sell to people and has one of the highest paybacks of any IT initiative. BI done badly (at the design, development, implementation or follow-up stages) will fail.

The issue is basically a simple one: just how good is your BI team? If a BI implementation fails to deliver significant business value, then instead of looking for scape-goats, the BI team should purchase a mirror and start using it.

Let’s see if an exploration of the second suggested reason for problems with BI projects changes my stance at all.
 
 
What does “the business didn’t know what they wanted [from BI]” actually mean?

What do I need

Business intelligence, when implemented correctly, helps organisations to be more successful by offering a way to understand the dynamics of their operations and markets and facilitating better business decisions. So, almost by definition, good BI has to be a sort of model of the key things that happen in an company. This is not easy to achieve.

Again I will come back to my four-pillared approach and emphasise the first pillar. There is an imperative to:

Form a deep understanding of the key business questions that need to be answered.

In my opinion, it is the difficulty in managing this process that plays into the assertion that “the business didn’t know what they wanted.” Putting it another way, the BI team were not skilful enough, engaging enough, or business-savvy enough to help the business to articulate what they wanted and to translate this into a formal set of definitions that could then form the basis of IT work. This process can indeed lengthy, tough and difficult to get right because:

  1. Businesses are often complex, with many moving parts and many things that need to be measured
  2. Different business people may have different visions of what is important – each of these may have validity, depending on context
  3. Both IT and business people may be unaccustomed to talking about business phenomena in the required way (one that is self-consistent and exhaustive)
  4. IT may not have a proper understanding of business strategy, business terminology and business transactions
  5. There is often a desire to start with the current state and adapt / add to this, rather than take the more arduous (but more profitable) approach of working out what is necessary and desireable
  6. The process is typically iterative and requires an ongoing commitment to the details, sapping reserves of perseverance

I have written about the level of commitment that can be required in defining BI business requirements in a couple of articles: Scaling-up Performance Management and Developing an international BI strategy. Please take a look at these if you are interested in delving further into this area. For now it is enough to state that you should probably allow a number of months for this work in your BI project plan; more if your objective is to deliver an all-pervasive BI system (as it was in the work I describe in the articles). It is also helpful to realise that you are never “done” with requirements in BI, they will evolve based on actual use of the system and changing business needs. You will end up living this cycle, so it makes sense to get good at it.

Sometimes it may be tempting for either IT or the business people involved to short-cut the process, or to give up on it entirely. This is s sure recipe for disaster. It is difficult to make establishing requirements a fun exercise for all those involved, but it is important the the BI team continually tries to keep energy levels high. This can be done in a number of ways: by reminding everyone about the importance of their work for the organisation as a whole; by trying to use prototypes to make discussions more concrete; and – probably most importantly – by building and maintaining personal relationships with their business counterparts. If you are going to work for a long time with people on something that is hard to do, then it makes sense to at least try to get along. It is on apparently small things such as these essentially human interactions that the success or failure of multi-million dollar projects can hinge.

Helping the business to articulate what they want from BI is extremely important and equally easy to get wrong. Mistakes made at this stage can indeed derail the whole project. However, this is precisely what the BI team should be good at; it should be their core competency. If this work is not done well, then again it is primarily the responsibility of the professionals involved. A statement such as “the business didn’t know what they wanted” simply reflects that the BI team were not very good at running this phase of a BI project.
 
 
Conclusion

The case against the BI team

I find myself back at my previous position. Of course the idea of finding scape-goats for the failure of a BI project can be very tempting for the members of the team that has failed. However, this is an essentially futile process and one that proves that the adage about learning from your mistakes does not always apply.

To make things personal. Suppose that I am responsible for leading project in which it is obvious up-front that extensive buy-in and collaboration will be required from a group of people. If the project fails because neither of these things was obtained, then surely that’s my fault and not theirs, isn’t it?
 


 
For some further thoughts on this issue, take a look at an article by Ferenc Mantfeld entitled: Top 10 reasons why Business Intelligence Projects fail.
 

Jargon

Alice consulting with an industry expert

  `As I was saying, that seems to be done right — though I haven’t time to look it over thoroughly just now — and that shows that there are three hundred and sixty-four days when you might get un-birthday presents –‘

`Certainly,’ said Alice.

`And only one for birthday presents, you know. There’s glory for you!’

`I don’t know what you mean by “glory”,’ Alice said.

Humpty Dumpty smiled contemptuously. `Of course you don’t — till I tell you. I meant “there’s a nice knock-down argument for you!”‘

`But “glory” doesn’t mean “a nice knock-down argument”,’ Alice objected.

`When I use a word,’ Humpty Dumpty said, in rather a scornful tone, `it means just what I choose it to mean — neither more nor less.’

`The question is,’ said Alice, `whether you can make words mean so many different things.’

`The question is,’ said Humpty Dumpty, `which is to be master — that’s all.’

Through the Looking-Glass and what Alice found there, by Lewis Carroll

 

Yesterday I was moved to post the above section from one of my favourite books on the LinkedIn.com Organisational Change Practitioners forum. The precise thread was entitled, Commitment during Change (as ever you need to be a member of LinkedIn.com and thr group to access the preceding links). The context was an increasingly intricate discussion about what constituted a “burning platform”; if this was a good thing to be standing on, or not; and whether such a situation was likely to lead to a positive or negative reaction on behalf of those standing on it.

My first contribution to this section of the discussion was as follows (with some light editing):

A burning platform tends to suggest panic and an imperative to do something (anything) right now. Think about it; the burning bit and… well… being on a platform. I am not sure that this is the best metaphor for instilling commitment.

Commitment may be passionate, but it is more rational, more of an active choice as opposed to, “what do I have to do to get out of here, my toes are getting hot?”

Telling someone that they are on a burning platform will certainly get their attention – they may also be willing to listen to you if you have some suggestion that might help, but this does not sound like instilling commitment in them to me; more like instilling fear.

Commitment tends to suggest a belief on behalf of the committed that what they are being asked to do is right for them and necessary for the broader organisation (despite it potentially being difficult and/or painful).

Commitment is not fleeing a burning platform – that’s just a survival instinct. Instead commitment might be exhibited by a person deciding to return to a burning platform to rescue some one.

The Alice quote came after I had posted the above thoughts, but before the post that I wanted to focus on in this article. This was about professional jargon and was as follows (again lightly edited):

When I was studying Mathematics, the use of words to mean something other than their ordinary meaning became second nature. The uninitiated would never have guessed the recherché meanings we ascribed to everyday words such as “ring”, “field” or “group”.

Early in my IT career I went over to the dark side, quoting impenetrable acronyms with the best of them. However as my role became more part of the business, I had something of an epiphany. I realised that people were not really that impressed by jargon, that they were more likely to assume (sometimes correctly) that the jargon-user was trying to cover something up or sound clever, and that maybe there was a better way.

Nowadays I am sometimes guilty of using complicated English, but I hope that it is mostly just English (as opposed to English 2.0 – now with even more terminology and even less meaning). I will crave your indulgence about the bit of French above of course :-o.

I think that jargon is both useful and inescapable when communicating efficiently with fellow professionals in a field (no not the Maths meaning of “field”); in all other cases it is mostly a hindrance to being understood.

Now I am sure that an assidious reader would have no problem whatsoever in finding counter-examples to my call for plain-speaking about IT; they are probably sprinkled liberally throughout this blog. Maybe this is a case of doing what I say, rather than what I do. However, it is interesting the number of commentators who have suggested that it would help IT professionals to increase their standing with their colleagues if they dropped the technical jargon and learned to speak more like a business person (e.g. see my comments on Ilya Bogorad’s article about Talking Business).

While getting business people to terminate their love affair with their own version of jargon might be wishful thinking, it is pleasing to go beyond Ilya’s recommendation and contemplate a world where a spade is called a spade and not a terrain relocation appliance.

Sadly it is all too often the case that the number of words used in a business context is inversely proportional to the quantum of meaning that they convey. Perhaps it is time for professionals in all walks of life to take a lead from Humpty Dumpty and begin to better assert their mastery of vocabulary.
 

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

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
 

Using multiple business intelligence tools in an implementation – Part I

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
 

Automating the business intelligence process?

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.
 

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

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.
 

Two pictures paint a thousand words…

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.
 

The scope of IT’s responsibility when businesses go bad

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