The specific benefits of Business Intelligence in Insurance

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


 

Short-term “Trouble for Big Business Intelligence Vendors” may lead to longer-term advantage

linkedin Chief Information Officer (CIO) Network

This post is another that highlights responses I have made on various LinkedIn.com forums. In this case, a news article was posted on the Chief Information Officer (CIO) Network group (as ever you need to be a member of LinkedIn.com and the group to view the original thread).

The news article itself linked to a piece / podcast on The IT-Finance Connection entitled: Big BI Vendors Facing Big Challenges. In this Nigel Pendse, author of the anual BI Survey, was interviewed by IT-Finance Connection about his latest publication and his thoughts about the BI market in general.

Nigel speaks about issues that he sees related to the consolidation of BI vendors. In his opinion this has led to the big players paying more attention to integrating acquisitions and rationalising product lines instead of focusing on customer needs. In one passage, he says:

Within product development, the main theme moved from innovation to integration. So, instead of delivering previously promised product enhancements to existing customers, product releases came out late and the highlights were the new connections to other products owned by the vendor, but which were probably not used by the existing customers. In other words, product development was driven by the priorities of the vendor, not the customer.

Whilst there is undoubtedly truth in Nigel’s observations, I have a slightly different slant on them, which I offered in my comments:

It is my very strong opinion that what the users of BI need to derive value is not the BI vendors “delivering previously promised product enhancements” but using the already enormously extensive capabilities of their existing BI tools better. BI should not be a technology-driven area, the biggest benefits come from BI departments getting to know their users’ needs better and focusing on these rather than the latest snazzy tool.

If this does happen, it may mean less than brilliant news for the BI vendors’ sales in the short-term, but successful BI implementations are going to be a better advert for them than some snazzy BI n.0 feature. The former is more likely to drive revenues for them in the medium term as companies build on successes and expand the scope of their existing BI systems.

See also: BI implementations are like icebergs

While some people see large potential downsides in the acquisition of such companies as BusinessObjects, Hyperion and Cognos by large, non-BI companies, you could argue that their new owners are the sort of organisations that will aim to use BI to drive real-world business success. Who knows whether they will be successful, but if they are and this is at the expense of technological innovation, then I think that this is a reasonable sacrifice.

As to whose vision of the future is right, I guess only time will tell.
 

Ilya Bogorad on Talking Business

A very brief post, just to acknowledge that sometimes you come across a gem of an article in the blogosphere. On this occasion, I would also like to thank the author for pointing his work out to me on a LinkedIn.com group!

The piece in question is called Talking business: Three reasons why your opinion is being ignored. It is by Ilya Bogorad and appears on Tech Republic. Well worth a read, no matter where you are in your IT career.
 


 
Read some my thoughts about another Tech Republic piece in: “Why taking a few punches on the financial crisis just might save IT” by Patrick Gray on TechRepublic.
 
 
Ilya Bogorad is the Principal of Bizvortex Consulting Group Inc, a management consulting company located in Toronto, Canada. Ilya specializes in building better IT organizations and can be reached at ibogorad@bizvortex.com or on (905) 278 4753.
 

The Top Business Issues facing CIOs / IT Directors – Results

Back in January, in collaboration with Chase Zander, I started a process of consulting with senior IT managers to develop a list of the top business issues that they faced. This exercise was intended to shape the content of a IT Director Forum that we were planning. This will now be happening on 26th March in Birmingham (for further information see this post).

Questionaire Responses
The Top Business Issues faced by CIOs / IT Directors

Back then, I promised to share some of the findings from this study. These are summarised in the above diagram. The input was based on public comments made by a selection of senior people on the CIO group of LinkedIn.com, plus e-mails sent to me on the topic and feedback received by Chase Zander.

A textual version of the data appeas below (sample size ~60):
 

  Issue % of Votes  

  IT / Business Alignment 27%  
  Cost-saving 13%  
  Managing change 8%  
  Status of the IT Director 8%  
  Legacy Systems 5%  
  Customer focus 5%  
  Enterprise Architecture 5%  
  Business Intelligence 5%  
  Avoiding the latest and greatest 3%  
  Cloud Computing 3%  
  Only one response 17%  

  Total 100%  

 
I would like to thank all of the IT professionals who contributed to this survey.
 

Is outsourcing business intelligence a good idea?

Outsourcing
 
Introduction

The phrase IT outsourcing tends to provoke strong reactions. People either embrace it as a universal panacea capable of addressing any business problem, or recoil in horror at the very sound of it. Just for a change, I am somewhere in the middle; to me it is another tool at the disposal of businesses which can either be used wisely or poorly (much like IT itself you might say). As always the difference between the two extremes comes down to how well the project is led. Regardless of this, there are some benefits and some disbenefits associated with IT outsourcing and this article will explore the case for applying outsourcing to business intelligence.
 
 
Benefits of general IT outsourcing

Before I plunge into the world of BI, it is perhaps worth revisiting the general reasons for IT outsourcing, some of the most regularly quoted are as follows:

1. Reduction in costs

The provider of outsourcing (I’m just going to say “the provider” from now on to save typing) can carry out the same tasks at a cheaper cost to the client organisation (while still presumably turning a profit). There can be a number of bases for this; the one that generally comes to mind is wage arbitrage between different economies. However, it could also be that the provider has economies of scale; for instance, less people being required to run the consolidated data centres of several companies, than is required to run each separately. Also the provider may have staff who are more productive than at the client.

2. Ability to scale-up and scale down resource

The nature of business is such that sometimes all hands are required on the IT deck and at others there is spare capacity (this is something I address in my two articles on Problems associated with the IT cycle and Mitigating problems with the IT cycle). Now IT departments are normally quite good at finding (hopefully) useful things for people to do, but the issue remains. The promise of an outsourcing arrangement is that the tap of resource can be adjusted to meet demand without having to either fire and rehire staff, or rely on bringing in expensive contract resource. It is often hoped that this feature of outsourcing will also help to speed IT products to market.

3. Making IT provision a contractual relationship

An arrangement with a provider, depending on how the contract is drafted, can make the provision of IT services subject to penalties and claw-backs when service levels drop below those that have been agreed. While there are clearly some sanctions that can be applied to underperformance by internal IT departments, the financial benefit to the organisation is likely to be less (unless your CIO is a multi-billionaire of course). Companies are used to these contractual relationships, they are often the lifeblood of business, and it is a more familiar way of dealing with issues for them.

4. Access to skills

The nature of IT is that it does tend to evolve, sometimes quickly, sometimes slowly. For organisations this means keeping their IT people’s skills up to date though courses, or continually looking to bring people with new skills into an organisation (such people generally not being the cheapest). The idea with an outsourcing arrangement is that these issues become the headache of the provider, not the client. This area can be particularly pertinent when there is a technology change or a significant upgrade; these are times at which the prospect of being shot of IT worries may seem very attractive. The effort and cost of, as it were, upgrading your in-house IT staff may seem prohibitive in these circumstances.

5. Focus on core competencies

This has been a business mantra for many years, why should a company engaged in a wholly separate area of human endeavour want to become experts in building and supporting complex IT systems, when they can get a specialist organisation to do this for them? This moves towards the idea of a lean, or even virtual, organisation.

6. Failure of in-house IT

It is sad to have to add this item, but it is often the implicit (and sometimes even the explicit) driver of a desire to outsource. CEOs, COOs or CFOs may be so fed up with the performance of their IT people that they feel that surely someone else could not be worse. There is an adage that you don’t outsource a problem, but this is often honoured more in breech than observance.

I am sure that there are other advantages, claimed or real, for IT outsourcing, but the above list at least covers many of the normal arguments. At this stage a fully-balanced article would probably present arguments against IT outsourcing. However, my objective here is not to provide a critique of IT outsourcing in general, but to see whether the above benefits apply to business intelligence. Because of this, and I should stress purely for the purposes of this article, I am going to accept that all of the above gains are both realisable and desirable for general IT. There will therefore you will find no comments here about arbitrage (of its very nature) resulting in differentials of pricing closing over time.

The only benefit that I am going to rule out is the final one; addressing failed IT departments. Applying outsourcing in these cases is only likely to make things worse, and probably more expensive. Far better in my opinion to work out why IT is failing (most typically due to poor leadership it has to be said, see also my article: Some reasons why IT projects fail) and draw up plans for addressing this. If outsourcing is a strong element of this, then so be it, but thinking that it will resolve this type of issue is probably naive in most circumstances.

So, as always seems to be the case in these types of articles, we have five potential benefits against which to assess outsourcing BI. Before I look at each in turn, I wanted to make some general observations.
 
 
Things that are different about BI

The main fly in the ointment with respect to outsourcing business intelligence is the fact that good BI is reliant upon four things (see also BI implementations are like icebergs):

A. An in-depth understanding of business requirements, developed by close collaboration with a wide range of business managers. In particular, what is necessary is understanding what questions the business wants to ask and why (see Scaling-up Performance Management and Developing an international BI strategy)
B. An extensive appreciation of the data available in different business systems, its accuracy and how data in different places is related to each other.
C. Developing creative ways of transforming the available data into the required information and presenting this in an easy-to-understand and use manner.
D. A focus on change management that includes business-focussed marketing, training and follow-up to ensure that the work carried out in the first three areas results in actual business adoption and thereby the creation of value (see my collection of articles focussed on cultural transformation).

With the possible exception of item C., which is more technical, the above are best carried out in a symbiotic relationship with the business. Ideally what develops is a true IT / business hybrid team, where, though people have clear roles, the differences between these blur into each other. In turn, building thus type of team is predicated on developing strong relationships between the IT and business members and establishing high levels of trust and respect.

Also with item C., this is not precisely a stand-alone activity. It is one best carried out collaboratively by technically-aware business analysts and business-aware data analysts, ETL programmers and OLAP designers. Once again, distinctions blur somewhat during this work and a different type of hybrid team appears.

I have tried to illustrate the way that these tasks and teams should overlap in the following diagram.

bi-venn-w300

Clearly it is not impossible to achieve what I have described above in an outsourced environment, but it seems that it might be rather tougher to do this. One key point is that the type of skills that are necessary for success in BI are cross-over business / IT skills and these are generally less easy to buy off the shelf. Another is that the type of intellectual property that a BI team will build up (basically extensive knowledge of what makes the organisation tick) is precisely the sort that you would want to retain within an organisation.

I would suggest that if an organisation wants to outsource BI, then they should start that way. Once a BI team has gone through tasks A. to D. above then I can’t see how it would be cost-effective to subsequently outsource. The transfer of knowledge would take too long and be too costly.

To provide some context to this let me share some non-confidential details of a study I performed recently comparing the efficiency of a well-established BI team in a developed country with a less mature BI team in a lower-cost location. Rather than considering relative costs, I looked at relative productivity. A simple way to do this is to get quotes for carrying out a certain type of work from both teams (though I also applied some other techniques, which I won’t go into here). My main finding was that the ostensibly high cost team was more than twice as productive as the allegedly low-cost team. Just to be clear, if the “high-cost” team quoted $X for a piece of work, the “low-cost” team quoted over $2X,because they required much more resource and/or time to carry out the same work.

So, in what follows, I will assume that a decision is taken to outsource at the inception of a project. With this assumption and the previous background, let’s go back and look at the five benefits of outsourcing from the beginning.
 
 
Matching the benefits to BI

1. Reduction in costs

It will take external BI resource at least as long as internal BI resource to understand business requirements and available data. In fact internal staff probably have something of an advantage as they should already have an appreciation of what the organisation does and how IT systems support this. The external resource also has the disadvantage of it probably being more difficult for them to build business relationships, this can be exacerbated if there are personnel changes during the project; something that is perhaps more likely to happen with an external provider. If the provider is located in another country, then this raises even more challenges and inefficiencies (and leads to travel expense).

It will take an external BI team at least as long as an internal one to dig into the available data and how the various systems inter-relate. Again, having some familiarity with the existing systems’ landscape would be an advantage for an in-house team.

If an external team can get to the position where they understand the business needs and the available data really well in a reasonable period of time, then they could possibly have an advantage in the arena of transforming data into information. Something that may mitigate this however is that fact that most BI development is iterative and that a rolling set of prototypes needs to be reviewed closely with the business. This element introduces the same challenges as were apparent with defining business requirements above.

Similar arguments as were made about the business requirements phase apply to deployment and follow-up.

2. Ability to scale-up and scale down resource

While it may be possible (subject to contract) to scale-down resource with a provider (though perhaps tougher to get them back when you need them), scaling-up is just as hard as it is in-house at it means more staff at the provider going through the learning curve about the organisations business needs and data.

4. Access to skills

This is the crux of the matter. The skills in question are not Java programming (or even Cobol), they are business knowledge. ETL and OLAP skills are important, but only if they are applied by people who understand what they are doing and to what purpose. These skills are not just lying around in the market place; they are acquired through hard work and dedication.

3. Making IT provision a contractual relationship

Clearly this is a benefit of outsourcing. However, given that the contract is there for when things go awry, it is worth asking the question “are things more or less likely to go wrong with a provider?”

5. Focus on core competencies

While it is quite easy to argue that building e-commerce systems is not necessarily a core competency, good BI is about understanding what is necessary to best run the business. If that is not a core competency of any organisation, then I struggle to think of what would be.
 
 
Summary

My main argument is that BI is different to general IT projects (an assertion to which I will return in a forthcoming article). Having successfully run both, I am confident in this statement. I also think that you need different types of people with different skills in BI projects. These facts, plus the closeness of business / IT relationships which are necessary in the area mean that outsourcing is less likely to be effective. I am sure that an outsourcing arrangement can work well for some organisations in some circumstances, but I would argue strongly against it being best practise for most organisations most of the time.
 


 
After penning this article, a further problem with outsourcing business intelligence came to my mind; security. On part of most BI systems is a facility to analyse the organisation’s results. Ideally the BI system will have these figures in place very soon after the end of a financial closing. Such data is market sensitive and there may be concerns with trusting an external provider with both producing this and ensuring that it remains confidential until market announcements are made. I am not suggesting that providers are unethical, just that companies may not wish to take a chance in this area.
 
I should also credit a thread on the LinkedIn.com EPM – Business Intelligence group, which got me thinking about this area (as ever, you need to be a member of LinkedIn.com and the group to view this)
 

 

Some reasons why IT projects fail

© Alex Messenger - http://www.alexmessenger.co.uk/
© Alex Messenger - http://www.alexmessenger.co.uk/

Having yesterday been somewhat disparaging about the efforts of others to delineate the reasons for BI projects failing, I realised that I had recently put together just such a list myself. By way of context, this was in response to being asked for some feedback in a subject area where I had little expertise and experience. Instead of bailing out of answering, I put together a more general response, a lightly edited and mildly expanded version of which appears below.

Please note that there is no claim on my part that this list is exhaustive; in common with all humans, us IT types can be very creative in finding new ways to fail, I am sure there are some out there that I have not come across yet.
 

  1. The objectives of the project not being clear. By this I mean the business objectives. There are two layers of problems, the actual business issues may not be understood well enough to form an effective response and, if the business knows what it needs to do in general terms, IT may not fully appreciate this for a number of reasons (mostly down to lack of communication) or may be unable to translate this into a suitable programme of work (possibly because of a lack of knowledge of how the business operates). Where IT is not part of the senior management team, or sees itself as a department apart, this issue is more likely to occur.
  2. Strategy formation being skipped. If you don’t understand what a project is meant to be about, it is difficult (to say the least) to form a strategy. However, if the test in point 1. is passed, then it may be tempting (or there may be pressure applied) to get to the end game as soon as possible without either forming a strategy for the project, or fitting this into both over-arching business and IT strategies (which one fervently hopes are complementary). As I know all too well, the strategy formation step can be tough one and people may sometimes be keen to skip it. The current economic climate may lead to this happening more frequently and my opinion is that this will be storing up trouble for the future.
  3. Fragmented systems’ landscapes. Related to the above, it is often very difficult to make progress when there is a patchwork of different systems and approaches throughout an organisation and little desire to address this short-coming. Often some sort of revolution (albeit sometimes a quiet one sustained over many years) is required to move forward. Sometimes this requires some crisis, internal or external, as virtually every organisation is inherently conservative; no matter what their marketing spiel may claim to the contrary.
  4. Lack of Change Management. Projects often also have an organisational change aspect (what else are they for?) and the problems here are: a) people do not like change and resist it; and b) many otherwise able managers are not experienced in change – indeed we tend to educate most managers to be efficient in a steady-state environment. Even when this aspect is recognised, it is often underestimated and work does not start until too late in the game.
  5. People. Aside from these, the main other problem is people. Projects, even small ones, are difficult and not everyone is up to running them. Simple errors in execution can derail projects that otherwise tick all of the boxes.

 
Of course any passing Gartner analyst is more than welcome to rip this to shreds if they see fit.
 

“Gartner sees a big discrepancy between BI expectations and realities” – Intelligent Enterprise

Doug Henschen
 
Doug Henschen at Intelligent Enterprise reports from the Gartner Business Intelligence Summit in Washington D.C., explaining that Gartner analysts John Van Decker and Kurt Schlegel cited five reasons why BI projects do not live up to expectations (article link here):
 

  1. No IT-Business Partnership – “We have to get away from thinking of it as a vendor-customer relationship,” said Schlegel.
  2. No Link to Corporate Strategy – BI team have to listen to the executives and develop metrics and measures that are aligned with their goals.
  3. No connection to the Process – “BI has been overtly disconnected for too long,” Schlegel proclaimed. It’s not enough to deliver the right information to the right users. You have to insert those insights into the processes and interfaces that business users live in every day.”
  4. No Governance or Too Much – It has to be just the right amount of governance. BI grew up departmentally, so it’s all too common to have many silos of BI. At the other extreme, some companies are so uptight about data standards that companies can’t get their data into the warehouse.
  5. No Skills – Business users often lack skills, chimed in Van Decker, citing the one area where the business side was said to be falling short. “Most companies have very sophisticated capabilities available that folks just aren’t taking advantage of,” he said, pointing to corporate performance management (CPM) software as a leading example.

 
I come close to the situation of words failing me when I read a list like this (though not close enough to prevent me penning an article of course). I appreciate that maybe a public seminar is not the easiest place to provide deep insights (I present a lot myself), but the commentary against each of the problem areas seems odd to me. I’m not sure that these are really the five reasons for BI continuing to disappoint in some organisations, while it continues to delight in others, but here are my thoughts on each headline.
 

  1. No IT-Business Partnership – We have to stop talking about IT and Business as if they were two parties trying to negotiate a cease-fire. IT is a business department, it carries out business projects. It would be ridiculous to say that there needs to be a Sales-Business Partnership, it should be equally so with IT. I expand on this theme in the very first article on this blog.
  2. No Link to Corporate Strategy – There should not be a link to Corporate Strategy, BI does not exist as a separate entity that requires linkage. Instead BI work should be an expression of Corporate Strategy (as should any IT project), what else is it an expression of? This is not about listening to executives (though that is important) it is about IT being part of the senior management team of an organisation and not some semi-detached entity, focussed only on the beauty of its own navel. I give some indication of how to go about ensuring that this is the case in two articles, one focussed on a European environment and one spanning four continents.
  3. No connection to the Process – I agree that embedding good BI in a coporoate culture requires effort (indeed I have written a series of articles on the subject, starting with this one), however I struggle to see how any BI team could fail to realise this and pay the area due attention. If this is truly a reason for failure, then it is because of a lack of basic project and change management skills in BI teams.
  4. No Governance or Too Much – I’m not sure that achieving the Goldilocks approach to Governance is the issue here. BI’s impact on an organisation is directly proportional to how pervasive it is. This means that silos of BI reduce value and the walls need to be knocked in. Does this have to be all in one go? of course not, there are always benefits in a balance between incremental progress and paradigm shifts. Any organisation who has gatekeepers who refuse access to the warehouse because of and overly rigid approach to data standards is going to have problems. Equally where systems are developed with little thought to the information that they provide and data is simply thrown over the wall to the BI team, this is going to destroy value. As ever, there needs to be a sensible balance struck, one that yields the greatest business benefit for the lowest cost.
  5. No Skills – “Business users often lack skills”, this seems both incredibly patronising (are only IT people smart enough to get it?) and also a poor excuse for BI teams not paying enough attention to education (see point 3. above). If business people truly lack the skills to use good BI, then they are probably unfit to be in business as the tools are pretty intuitive (if not over-engineered by an approach that is too technology-focussed). More likely, training has been poor, or the BI deliveries have failed to be tailored to answering questions that the business wants to ask.

 
In summary, I don’t have five reasons for BI failing to live up to expectations, I have one. 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.
 


 
Continue reading about this area in: Some reasons why IT projects fail
 
 
Doug Henschen joined Intelligent Enterprise as Editor in 2004 and was named Editor-in-Chief in January 2007. He has specialized in covering the intersection of business intelligence, performance management, business process management and rules management technologies within enterprise applications and architectures. He previously served as Editor-in-Chief of Transform Magazine, which covered content management and business process management challenges.

I comment on another Intelligent Enterprise article, this one by Cindi Howson, here.
 

Trends in Business Intelligence

trends

This year, as in every year since the phrase “Business Intelligence” first came to prominence, there have been a rash of predictions about what will happen with the area in 2009. I have linked to and commented on some of these myself on this blog. This article is my take on the area. I should however explain that there is a twist. These are not the trends that I expect to see in 2009, just my thoughts on what ought to be trends in BI over the next few years. I cannot claim to have any prescience about whether they will come to pass, but I will be encouraged if they do.
 

  1. A more holistic approach to BI in organisations that have already invested
  2. Operational BI
  3. Consolidation of the number of BI platforms with organisations
  4. An increase in the prevalence of BI competency centres
  5. BI teams being jointly owned and managed by business divisions and IT
  6. Data from central warehouses being served to front-end applications
  7. BI data being used to automate some business decisions
  8. Further emphasis on predictive analytics
  9. BI having an increasing role in compliance and risk management
  10. Incorporation of external data into BI platforms
  11. Provision of BI to business partners and/or customers
  12. The most creative users of BI employing it to thrive, even in the current climate

 
1. A more holistic approach to BI in organisations that have already invested

Often BI solutions have started in a single area. Typically – given its direct link to better managing overall performance – this has been around analysing an organisation’s financial results, though implementations starting in the sales and even operational arenas are also not uncommon. BI systems tend to add more value as they bring in more information, particularly where a high-level phenomenon – e.g. a decrease in expenditure – can be attributed to lower level ones – e.g. greater repeat business (business acquisition being more expensive than repeat business in most industries), plus enhanced productivity, plus reduced staff turnover (resulting in lower recruitment and training costs). To do this, BI needs to widen its scope to take on new data sources and combine them in creative ways. Where BI platforms have already added value, there will be pressure from users to expand them to deliver even more utility and provide more sophisticated insights. This in turn will require BI practitioners to take a more holistic view of the area and to develop roadmaps explaining how new data sources will be brought on stream and what business value will result from this.
 
 
2. Operational BI

I think that there is a particular argument for BI to make a greater contribution in the area of operational management, particularly tying this to overall performance. Often BI implementations have focussed on the more stately world of monthly (or weekly) results and steered clear of the daily or hourly demands of operational information. The BI projects that I have seen in the Operational sphere have been more focussed at producing weekly status reports or year-to-date trend analyses. Related to BI platforms expanding to new areas, I see increasing demand for information about the internal effectiveness of an organisation; quickly identifying bottlenecks or areas of inefficiency and tracking efforts to address these. Supporting this type of reporting will often require BI practitioners to rethink their architectures which are often set up to refresh on longer timeframes. This may in turn require the warehouse to support multiple environments with different periodicities.
 
 
3. Consolidation of the number of BI platforms with organisations

It is all too common for organisations to have separate BI implementations. Maybe the ERP system comes with some shrink-wrapped cubes, as does the CRM system. Perhaps Finance have invested in some budget analysis tools and different business units have started dabbling in predictive modelling (see 8. below). Maybe certain power users or numerate departments have their own, much cherished databases. Clearly this approach is sub-optimal. If it was ever acceptable to have such an ad hoc approach to the area, the current economic climate means that there is no longer room for a multitude of platforms, each supported by their own ETL, servers, IT teams and (hopefully) training programmes. While transitional costs may make it impractical for some organisations to move to a single platform in the short term, the reductions in licensing, internal support, data centre and training costs that come from standardising BI tools are compelling. This is to say nothing about reducing the level of confusion in users faced with multiple reporting and analysis systems, each with their own terminology, vagaries of functionality and often un-reconciled to each other. Arguments about certain BI tools being best of breed for particular tasks were never wholly convincing, with the breadth of functionality offered by all of the major players today, any of them will be at least good enough for all but the most exacting of applications.
 
 
4. An increase in the prevalence of BI competency centres

If this is partly as a result of the previous three trends, it also has some drivers all of its own. Even in multinational organisations with highly devolved structures and local accountability, most of the management information that is needed to run businesses will be relatively consistent from country to country and business unit to business unit. Perhaps the sources will vary, but the business transactions that they support are surprisingly consistent. Many organisations are waking up to this fact and pulling BI provision into the centre. There are obvious benefits to this in terms of cost savings, not reinventing the wheel, increasing the consistency of reporting and enabling corporate roll-ups. However, my own feeling is that the best organisations will supplement a strong central resource with a (probably much smaller) virtual component located close to business needs who can better respond to these in a timely manner, but within an overall information architecture. This hybrid approach offers the best of both worlds.
 
 
5. BI teams being jointly owned and managed by business divisions and IT

It is an oft-repeated aphorism that all IT projects are business projects. While clearly true in theory, there are enough counterexamples to suggest that practise is rather different. However, BI projects have often stayed much closer to this maxim than other IT efforts. This is because BI systems serve no purpose unless they are closely entwined with business goals. Natural selection should weed out any non-business-focussed BI projects eventually; even in the sleepiest of organisations. It is likely that this close relationship will deepen. Whilst many aspects of BI are firmly in the IT arena (managing the regular refresh of multiple terabytes of data effectively clearly being one), I see a joint stewardship of the area developing. By this I mean something deeper than business oversight or steering committees. It is also different to business BI liaison managers being appointed – these roles often have the unintended consequence of isolating IT from its customers. What I see emerging in more enlightened organisations is true co-ownership of BI with business and IT management closely collaborating to run the area.
 
 
6. Data from central warehouses being served to front-end applications

Of course it is not uncommon for transaction processing systems to have buttons or links that call up a given report. What I am talking about here is a closer coupling, one that does not require users to leave their current system and where information from the warehouse is presented in a seamless manner to users. While such information will have all the BI benefits of being reconciled, consistent and accurate, its provenance will increasingly become invisible to the user (who shouldn’t really have to worry where figures come from so long as they are accurate). This is an area in which web-services have some real potential to leverage the investments that organisations have made in warehouses.
 
 
7. BI data being used to automate some business decisions

Stepping a little further along the path from the previous point, even before users of front-end systems have a need to review information about a transaction, it may well be that the information itself has been what determines whether a human is involved or not. Already some organisations perform triage on business transactions. Ones that meet all of a number of requirements get processed automatically. Ones that meet some of them, but not all, may get routed to junior staff, whose role is to determine whether they require further review or can proceed. Finally, those with a major variance to requirements may get sent straight to more senior staff. This approach means that a larger volume of business can be handled and that expensive senior resource is only applied where it is necessary. Of course a prerequisite to this type of approach is having reliable information on which to perform the triage.
 
 
8. Further emphasis on predictive analytics

While the best BI implementations encourage users to extrapolate from past figures to estimate future ones, the degree to which the analytical skills of the user plays a part varies from implementation to implementation. Here by analytics I mean the use of larger data sets to identify trends or exceptions, mostly at a portfolio level. Again, having invested in developing data warehouses, it makes sense to utilise the many and sophisticated tools that are available to carry out advanced statistical analysis on these; the aim being to deduce trends that would be beyond even the most skilled of human analysts. A by-product of successful BI implementations is that they often free the more numerate of people in organisations from the burden of repetitive number crunching and allow them to focus on more added-value work such as this.
 
 
9. BI having an increasing role in compliance and risk management

Sometimes BI projects may have had their genesis in these areas. However, even when this is not the case a pleasing result of having consolidated much of the organisation’s data in one place is that this then forms a valuable resource for compliance and risk management. Indeed, taking an external perspective, regulators tend to view the existence of an enterprise data warehouse as a sign that an organisation takes managing its risks seriously. Although business managers and risk managers may have slightly different (though hopefully complementary) perspectives and want to answer different types of questions, the data that they need to do this is not that dissimilar. Producing compliance suites from a well-designed warehouse is probably not one of the more taxing BI problems. Again expansion in this area is a further example of point 1. in action.
 
 
10. Incorporation of external data into BI platforms

I have spoken above about the remit of BI systems expanding internally and becoming more consistent geographically. A further trend in expansion is to meld internal information with that from external providers. The type of external information would range from industry to industry, but might include market data, information about specific companies or individuals (e.g. credit scores, where the use of these is admissible). For example, in insurance, where I have spent the last twelve years of my career, incorporating information from externally produced flood, or windstorm models is often a priority.
 
 
11. Provision of BI to business partners and/or customers

Sometimes one objective of BI implementations is to better understand the relationships with business partners and customers. I have seen this develop to the degree where output from BI systems is mailed to such counterparties. A logical extension of this is to allow such organisations direct access to “their information”. Of course as with any e-commerce initiative, there would have be to strict controls on what is viewed and who can view it, but these are problems that are regularly addressed in other areas of IT and the tools to do this are readily available.
 
 
12. The most creative users of BI employing it to thrive, even in the current climate

There have been many articles (including ones written by me) which have spoken about good BI being a great defence in times of economic stress. I would go beyond this and state that the real BI pioneers will take advantage of these capabilities to capture markets from their less well-informed competitors and to steer a course away from areas of business that may bring other less-foresighted organisations down. I look forward to seeing case studies bearing this out appear over the next few years.
 

“Businesses Are Still Crazy for BI After All These Years” – CIO.com

Thomas Wailgum at CIO.com

Thomas Wailgum has written an article at CIO.com in which he talks about continuing demand for BI, but adds that this, in turn, suggests that in many organisations BI has yet to deliver on its promise. As Thomas puts it:

“I see pent-up enterprise-wide frustration, aimed squarely at IT and CIOs for failing to give the business what it needs and deserves”

He sees the fundamental problem as being fragmented systems and stand-alone BI applications. This sounds like challenges that I have faced before. I agree that BI only realises it potential when a more strategic and wide-ranging approach is taken. Something I refer to in many places on this blog, but possibly most directly in Holistic vs Incremental approaches to BI.

My basic point is that while it is sensible to take a pragmatic, incremental approach to implementing BI (collecting successes as you go and building momentum), this needs to be within the framework of a more encompassing vision for what the eventual BI system will be like and do.

I don’t believe that you can do BI by halves and remain somewhat sceptical about the claims of some of the newer BI products to do away with the necessary hard work.
 

“All that glisters is not gold” – some thoughts on dashboards

Fool's gold

Yesterday I was tweeting quotes from Poe and blogging lines attributed to Heraclitus. Today I’m moving on to Shakespeare. Kudos to anyone posting a comment pointing out the second quote that appears later in the text.
 
 
Introduction

Dashboards are all the rage at present. The basic idea is that they provide a way to quickly see what is happening, without getting lost in a sea of numbers. There are lots of different technologies out there that can help with dashboards. These range from parts of the product suites of all the main BI vendors, through boutique products dedicated to the area, all the way to simply using Java to write your own.

A lot of effort needs to go into how a dashboard is presented. The information really does need to leap off the screen, it is important that it looks professional. People are used to seeing well-designed sites on the web and if your corporate dashboard looks like it is only one step removed from Excel charts, you may have a problem. While engaging a design firm to help craft a dashboard might be overkill, it helps to get some graphic design input. I have been lucky enough over the years to have had people on my teams with experience in this area. They have mostly been hobbyists, but they had enough flair and enough of an aesthetic taste to make a difference.

However, 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

I’ll now consider the importance of these two areas.
 
 
Choosing the KPIs

Filtering out the KPIs

The acronym KPI is bandied about with enormous vigour in the BI community. Sometimes what the ‘K’ stands for can get a bit lost in the cacophony. Stepping back from dashboards for a few minutes, I want to focus on the measures that you have in your general business intelligence applications such as analysis cubes. Things like: sales revenue, units sold, growth, head count, profit and so on.

[Note: If you don’t like BI buzzwords, please feel free to read “figures”, or “numbers” where ever you see “measures”. I may attempt to provide my own definitions of some of these terms in the future as the Wikipedia entries aren’t always that illuminating.]

When you have built a Data Mart for a particular subject area and are looking to develop one or more cubes based on this, you may well have a myriad of measures to select from. In some of the earliest prototype cubes that my teams built, we made the mistake of having too many measures. The same observation equally applied to the number of dimensions (things that you want to slice and dice the measures by, e.g. geography, line of business, product, customer etc.). Having too many measures and dimensions led to a cube that was cumbersome, difficult to navigate and where the business purpose was less that crystal clear. These are all cardinal sins, but the last is the worst as I have referred to elsewhere. The clear objective is to cut down on both the figures and the business attributes that you want to look at them by. We set a rule (which we did break a couple of times for specialist applications) of generally having no more than ten measures and ten dimensions in a cube and ideally having less.

Well this all sounds great, the problem – and the reason for this diversion away from dashboards – is which measures do you keep and which do you drop. Here there is no real alternative to lots of discussions with business partners, building multiple prototypes to test out different combinations and, ultimately, accepting that you might make some mis-steps in your first release and need to revisit the area after it has been “shaken down” by real business use. I won’t delve into this particular process any deeper now. Suffice it to say that choosing which measures to include in a cube it is both an area that is important to get right and one in which it is all to easy to make mistakes.

So, retuning to our main discussion, if picking measures at the level of an analysis cube is hard, just how hard is it to pick KPIs for a dashboard. I recall a conversation with the CEO of a large organisation in which he basically told me to just pick the six most important figure and put them on a dashboard (with the clear implication that sooner would be rather better than later). After I had explained that the view of the CEO in this area was of paramount importance and that his input on which figures to use would be very valuable, we began to talk about what should be in and what should be out. After a period of going round in circles, I at least managed to convey the fact that this was not a trivial decision.

What you want with the KPIs on a dashboard is that they are genuinely key and that you can actually tell something from graphing them. The exercise in determining which figures to use and how to present them was a lengthy one, but very worthwhile. You need to rigorously apply the “so what?” test – what action will people take based on the trends and indicators that are presented to them. In the end we went for simplicity, with a focus on growth.

There was a map showing how each country was doing against plan; colour-coded red, amber and green according to their results. There were graphs comparing revenue to budget by month and the cumulative position and there was a break-down by business unit. The only to elements of interaction were to filter for a region or country and a business unit or line of business. Any further analysis required pulling up an underlying cube (actually we integrated the cube with the dashboard so that context was maintained moving from one to the other – this was not so easy as the dashboard and cube tools, while from the same vendor, were on two different major release numbers).

There were many iterations of the dashboard, but the one we eventually went live with received general acclaim. I’m not sure what we could have done differently to shorten the process.
 
 
Where does the data come from?

A dashboard without an underlying Information Architecture
A dashboard without an underlying Information Architecture

The same range of dashboard tools that I mention in the introduction are of course mostly capable of sourcing their data from pretty much anywhere. If the goal is to build a dashboard, then maybe it is tempting to do this as quickly as possible, based on whatever data sources are to hand (as in the diagram above). This is probably the quickest way to produce a dashboard, but it is unlikely to produce something that is used much, tells people anything useful, or adds any value. Why do I say this?

Well the problem with this approach is that all you are doing is reflecting what is likely to be a somewhat fragmented (and maybe even chaotic) set of information tools. Out of your sources, is there a unique place to go to get a definitive value for measure A? Do the various different sources hold data in the same way and calculate values using the same formulae? Do sources overlap (either duplicating data, or function), if so, which ones do you use? Do different sources get refreshed with the same frequency and do they treat currency the same way? Are customers and products defined consistently everywhere?

A dashboad underpinned by a proper Information Architecture
A dashboad underpinned by a proper Information Architecture

Leaving issues like these unresolved is a sure way to perpetuate a poor state of information. They are best addressed by establishing a wider information architecture (a simplified diagram of which appears above). I am not going to go into all of the benefits of such an approach, if readers would like more information, then please browse through the rest of this blog and the links to other resources that it contains (maybe this post would be a good place to start). What I will state is that a dashboard will only add value if it is part of an overall consistent approach to information, something that best practice indicates requires an Information Architecture. Anything else is simply going to be a pretty picture, signifying nothing.
 
 
Summary

So my advice to those seeking to build their first dashboard has three parts. First of all, keep it simple and identify a small group of measures and dimensions, which are highly pertinent to the core of the business and susceptible to graphical presentation. Second, dashboards are not a short-cut to management information Nirvana, they only really work when they are the final layer in a proper approach to information that spans all areas of the organisation. Finally, and partly driven by the first two observations, if you are in charge of building a dashboard, make sure that the plans you draw up reflect the complexity of the task and that you manage expectations accordingly.