Independent Analysts and Social Media – a marriage made in heaven

13 April 2010
Oracle EPM and BI Merv Adrian - IT Market Strategies for Suppliers

I have been a regular visitor to Merv Adrian’s excellent blog since just after its inception and have got to know Merv virtually via twitter (@merv) and other channels. I recently read his article : Oracle Ups EPM Ante, which covered Oracle’s latest progress in integrating its various in-house and acquired technologies in the Enterprise Performance Management and Business Intelligence arenas.

The article is clearly written and helpful, I recommend you take a look if these areas impinge upon you. One section caught my attention (my emphasis):

Finally, Oracle has long had a sizable base in government, and its new Hyperion Public Sector Planning and Budgeting app suite continues the integration theme, tapping its ERP apps (both Oracle E-Business Suite [EBS] and PeopleSoft ERP) for bidirectional feeds.

My current responsibilities include EPM, BI and the third Oracle ERP product, JD Edwards. I don’t work in the public sector, but was nevertheless interested in the concept of how and whether JDE fitted into the above scenario. I posted a comment and within a few hours Merv replied, having spoken to his senior Oracle contacts. The reply was from a vendor-neutral source, but based on information “straight from the horse’s mouth”. It is illuminating to ponder how I could have got a credible answer to this type of question any quicker.

To recap, my interactions with Merv are via the professional social media Holy Trinity of blogs, twitter.com and LinkedIn.com. The above is just one small example of how industry experts can leverage social media to get their message across, increase their network of influence and deliver very rapid value. I can only see these types of interactions increasing in the future. Sometimes social media can be over-hyped, but in the world of industry analysis it seems to be a marriage made in heaven.
 


 
Analyst and consultant Merv Adrian founded IT Market Strategy after three decades in the IT industry. During his tenure as Senior Vice President at Forrester Research, he was responsible for all of Forrester’s technology research, covered the software industry and launched Forrester’s well-regarded practice in Analyst Relations. Earlier, as Vice President at Giga Information Group, Merv focused on facilitating collaborative research and served as executive editor of the monthly Research Digest and weekly GigaFlash.

Prior to becoming an analyst, Merv was Senior Director, Strategic Marketing at Sybase, where he also held director positions in data warehouse marketing and analyst relations. Prior to Sybase, Merv served as a marketing manager at Information Builders, where he founded and edited a technical journal and a marketing quarterly, subsequently becoming involved in corporate and product marketing and launching a formal AR role.
 

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BI and Competition – Bruno Aziza at Microsoft

13 April 2010

Bruno Aziza Worldwide Strategy Lead, Business Intelligence at Microsoft

Introduction

Bruno Aziza, Worldwide Strategy Lead for Business Intelligence at Microsoft recently drew my attention to his article on The Official Microsoft Blog entitled Use Business Intelligence To Compete More Effectively.

My blog attempts to stay vendor-neutral, but much of Bruno’s article is also in the same vein; aside from the banner appearing at the top of course. It is noteworthy how many of the big players are realising that engaging with the on-line community in a sotto voce manner is probably worth much more than a fortissimo sales pitch. This approach was also notable in another output from the BI stable at Microsoft; Nic Smith’s “History of Business Intelligence” , which I reviewed in March 2009. However, aside from these comments I’ll focus more on what Bruno says than on who he works for; and what he says is interesting.

His main thesis is that good BI can “sharpen competitive skills [...] turning competitive insights into new ways to do business”. I think that it is intriguing how some organisations, ideally having already got their internal BI working well, are now looking to squeeze even further value out of their BI platform by incorporating more outward-looking information; information relating to their markets, their customers and their competitors. This was the tenth BI trend I predicted in another article from March 2009. However, I can’t really claim to be all that prescient as this development seems pretty common-sensical to me.
 
 
Setting the bar higher

Competition between companies is generally seen as a positive thing – one reason that there is so much focus on anti-trust laws at present. Competition makes the companies involved in it (or at least those that survive) healthier, their products more attuned to customer needs, their services more apt. It also tends to deliver better value and choice to customers and thus in aggregate drives overall economic well-being (though of course it can also generate losers).

Setting the bar higher

In one of my my earliest blog articles, Business Intelligence and Transparency, I argued that good BI could also drive healthy internal competition by making the performance of different teams and individuals more accessible and comparable (not least to the teams and individuals themselves). My suggestion was that this would in turn drive a focus on relative performance, rather than settling for absolute performance. The latter can lead to complacency, the former ensures that the bar is always reset a little higher. Although this might seem potentially divisive at first, my experience of it in operation was that it led to a very positive corporate culture.

Although organisations in competition with each other are unlikely to share benchmarks in the same way as sub-sections of a single organisation, it is often possible to glean information from customers, industry associations, market research companies, or even the published accounts of other firms. Blended with internal data, this type of information can form a powerful combination; though accuracy is something that needs to be born in mind even more than with data that is subject to internal governance.
 
 
A new source of competitive advantage

"Lightning" striking twice in Bejing

Bruno’s suggestion is that the way that companies leverage commonly available information (say Governmental statistics) and combine this with their own numbers is in itself a source of competitive advantage. I think that there is something important here. One of the plaudits laid at the feet of retail behemonth Wal Mart is that it is great at leveraging the masses of data collected in its stores and using this in creative ways; ways that some of its competition cannot master to the same degree.

In recent decades a lot of organisations have attempted to define their core competencies and then stick to these. Maybe a competency in generating meaningful information from both internal and external sources and then – crucially – using this to drive different behaviours, is something that no self-respecting company should be without in the 2010s.
 


 
You can follow Bruno on twitter.com at @brunoaziza
 

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Google Fools Day

1 April 2010

Happy April Fools Day from Google

A nice touch – pointed out by @CurtMonash (who seems to be cropping up on my blog quite a bit at the moment):

  • Results 1 – 10 of about 63,300,000 for peter thomas. (2.00 shakes of a lamb’s tail)
  • Results 1 – 10 of about 63,300,000 for peter thomas. (0.10 microfortnights)
  • Results 1 – 10 of about 63,300,000 for peter thomas. (1.21 gigawatts)

and so on…

Try it yourself here .

Though I suspect you have only a few hours left.
 


 
Also worth checking out:

  1. The burgeoning NoData movement, led by revolutionary in chief @merv.
  2. The cutting-edge concept of Subterranean Computing, championed by @ocdqblog – so much more substantive than The Cloud.

 

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Inspiration

30 July 2009

From one of those rather annoying "motivational" pictures that seem to adorn a lot of HR department's walls nowadays
 
Introduction

Inspiration can come from many places. For me it is often via making a connection between two separate areas. I wrote about this phenomenon in my earlier artcile, Synthesis.

A couple of inspiration-related events have led me to pen this piece today and, as a great man once said:

A deductive technique

When two separate events occur simultaneously pertaining to the same object of inquiry we must always pay strict attention.

 
Thing One

The first occurrence was an article on Jeff Shuey’s blog entitled Surely, you must be joking. This borrows from the title of Nobel Laureate Richard P. Feynman‘s book Surely You’re Joking Mr. Feynman (as edited by his friend and co-drummer Ralph Leighton). I have found Feynman to be an inspirational character since I first saw him interviewed in depth on the BBC’s science magazine programme, Horizon. Some footage of this interview appears in the BBC’s archives, and may be viewed here. It is well worth a look.

I happen to have recently referenced Feynman, albeit rather obliquely, in a review of my bogging experiences, New Adventures in Wi-Fi – Track 1: Blogging. I have been delighted to receive some messages from people saying that this article had prompted them to take up blogging themselves. There can surely be no greater compliment paid in social media and I am honoured to receive it.

twitter.com

The idea for Jeff’s article came both from Microsoft featuring Feynman’s work on its Project Tuva site (this doesn’t seem to work for me in Chrome, though it’s fine in IE8 – maybe I’ll keep quiet about this in case the European Commission is listening in) and a subsequent exchange of tweets and links that we shared on twitter.com. Jeff’s handle is @jshuey if you would like to follow him. Also check out Jeff’s article to learn more about how a remarkable human being has influenced both him and Project Tuva.
 
 
and Thing Two

The second event relates to the traditional American diner that is round the corner from where I live. I appreciate that I live in London, but nevertheless I do have a traditional American diner round the corner. It is even owned by a Packers fan from Wisconsin. Lauren is one of the people who regularly works there and she has a talent for drawing in chocolate – no you haven’t misread that, she draws in chocolate, specifically on the plate that holds the diner’s very pleasant flourless chocolate cake.

Mermaids have been a favourite theme for Lauren, but more recently she has moved on to more ambitious works. The first was Michael Jackson for obvious reasons. This was followed by Barak Obama. The other day I suggested that, if she was working her way through American icons, then the next obvious person would be Marilyn Monroe. Lauren liked this idea and when I visited this morning to get my customary cup of coffee (skinny cappuccino rather than black and hot sadly) her lastest work greeted me:

Chocolate Marilyn

I’m really happy that my input has played a small part in two creative acts. This is particularly the case as I am normally acknowledging the inspiration that I have drawn from other people.

This sort of give and take of ideas has of course been happening during the entire course of human history. Clearly, even if I live to be 100, I could never hope to be as inspirational or influential as Richard Feynman. However it is both gratifying and humbling to be able to take part in the cycle of human interaction, no matter how minor my role. Maybe these two small recent examples are further evidence that the pace is increasing.
 

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A bad workman blames his [Business Intelligence] tools

29 July 2009

Tools
 
Introduction

This is a proverb with quite some history to it. Indeed its lineage has been traced to 13th Century France in: mauvés ovriers ne trovera ja bon hostill (les mauvais ouvriers ne trouveront jamais un bon outil being a rendition in more contemporary French). To me this timeless observation is applicable to present-day Business Intelligence projects. Browsing through on-line forums, it is all too typical to see discussions that start “What is the best BI software available on the market?”, “Who are the leaders in SaaS BI?” and (rather poignantly in my opinion) “Please help me to pick the best technology for a dashboard.” I feel that these are all rather missing the point. Before I explain why, I am going to offer another of my sporting analogies, which I believe is pertinent. Indeed sporting performace is an area to which the aphorism appearing in the title is frequently applied.

If you would like to skip the sporting analogy and cut to the chase, please click here.
 
 
The importance of having the right shoes

Rock climbing is a sport that certainly has its share of machismo; any climbing magazine or web-site will feature images of testosterone-infused youths whose improbable physiques (often displayed to full advantage by the de rigueur absence of any torso-encumbering clothing) propel them to the top of equally improbable climbs.

Given this, many commentators have noted the irony of climbing being conducted by people wearing the equivalent of rubber-covered ballet slippers. The fact that one of the most iconic rock climbing shoes of all time was a fetching shade of pink merely adds piquancy to this observation. Examples of these, the classic FiveTen Anasazi Lace-ups, are featured in the following photo of top British climber, Steve McClure (yes it is the right way up).

The UK's finest sport climer - Steve McClure - sports the Pink'uns

When I started rock climbing, my first pair of shoes were Zephyrs from Spanish climbing firm Boreal. They looked something like this:

The Zephyr by Boreal - $87 - £67

The Zephyr by Boreal - $87 - £67

Although it might not be apparent from the above image, these are intended to be comfortable shoes. Ones to be worn by more experienced climbers on long mountain days, or suitable for beginners, like myself at the time, on shorter climbs. Although not exactly cheap, they are not prohibitively expensive and the rubber on the soles is quite hard-wearing as well.

The Zephyrs worked well for me, but inevitably over time you begin to notice the shoes worn by better climbers at the crag or at the wall. You also cannot fail to miss the much sexier shoes worn by professional climbers in films, climbing magazine articles and (no coincidence here) advertisements. These other shoes also cost more (again no coincidence) and promise better performance. When you are looking to get better at something, it is tempting to take any advantage that you can get. Also, perhaps especially when you are looking to break into a new area, there is some pressure to conform, to look like the “in-crowd”, maybe even simply to distance yourself from the beginner that you were only a few months previously.

This is very shallow behaviour of course, but it is also the rock on which the advertising industry is founded. I wanted to get better as a climber, but would have to admit that other, less noble, motives also drove me to wanting to purchase new rock shoes.

The Galileo by FiveTen - $130 - £85

The Galileo by FiveTen - $130 - £85

The Galileos shown above are made by US company FiveTen and are representative of the type of shoes that I have worn for most my climbing career. FiveTen shoes have been worn by many top climbers over the years (though there have recently been some quite high-profile defections to start-up brand Evolv, who can never seem to decide whether to append a final ‘e’ to their name or not).

Amongst other things, FiveTens are noted for the stickiness of their rubber, which is provided by an organisation called Stealth Rubber and appears on no other rock climbing shoes. Generally the greater the adhesion between your foot and the rock, the greater the force that you can bring to bear on it to drive yourself upwards. Also it helps to have confidence that your foot has a good chance of staying in place, no matter how glassy the rock may be (and no matter how long the fall may be should this not happen). I have worn FiveTen shoes on all of my hardest climbs (none of which have actually been very hard in the grand scheme of things sad to say).

The Solution by La Sportiva - $155 - £120 (link goes to the Sportiva site)

The Solution by La Sportiva - $155 - £120
(the link loads a Flash page on the Sportiva site)

Nevertheless, with what I admit was rather a sense of guilt, I have recently embarked on a dalliance with another rock shoe manufacturer, La Sportiva of Italy. The Sportiva Solutions which are shown above are both the most expensive rock shoes I have ever owned and the most technical. If NASA made a rock shoe, they would probably not be a million miles away from the Solutions. The radical nature of their design can perhaps best be appreciated in three dimensions and you can do this by clicking on the above image.

The Solutions are very, very good rock shoes. I recently had the opportunity to carry out a before and after comparison on the following climb, A Miller’s Tale:

A Miller's Tale (V4/Font 6b+) - Rubicon Wall, Derbyshire, England

A Miller's Tale (V4/Font 6b+)
Rubicon Wall, Derbyshire, England
© http://77jenn.blogspot.com

My partner, who appears in the photo (incidentally sporting FiveTen shoes), climbed this on her second go. By contrast, I had many fruitless attempts wearing my own pair of FiveTens (that, to be fair to FiveTen, were much less technical than the Galileo’s above and were also probably past the end of their useful life). I frequently found my feet skittering off of the highly polished limestone, which resulted in me rapidly returning to terra firma.

A couple of weeks later, equipped with my shiny new Sportivas, my feet did not slip once. Of course the perfect end to this story would have been to say that I then climbed the problem (for an explanation of why some types of climbs are called problems see my earlier article Perseverance). Sadly, though I made much more progress during my second session, I need to go back to finally tick it off of my list.

So here surely is an example of the tool making a difference, or is it? My partner had climbed A Miller’s Tale quite happily without having the advantage of my new footwear. She is 5’3″ (160cm) compared to my 5’11″ (180cm) and the taller you are the easier it is to reach the next hold. Strength is a factor in climbing and I am also stronger in absolute terms than she is. The reason that she succeeded where I failed is simply that she is a better climber than I am. It is an oft-repeated truism in the climbing world that many females have better techniques than men. This, together with the “unfair” advantage of smaller fingers, is the excuse often offered by muscle-bound men who fail to complete a climb that a female then dances her way up. However in my partner’s case, she is also very strong, with her power-to-weight ratio being the key factor. You don’t need to lift massive weights in climbing, just your own body.

So I didn’t really need better rock shoes to prevent my feet from slipping. If I got my body into a better balanced position, then this would have had the same impact. Equally, if my abdominal muscles were stronger, I could have squeezed my feet harder onto the rock, increasing their adhesion (this type of strength, known as core strength for obvious reasons, is crucial to progressing in many types of climbing). What the Solutions did was not to make me a better climber, but to make up for some of my inadequacies. In this way, by allowing me the luxury of not focussing on increasing my strength or improving my technique, you could even argue that they might be bad for my climbing in the long run. I probably protest too much in this last comment, but hopefully the reader can appreciate the point that I am trying to make.

Campus board training

In order to become a better climber I need to do lots of things. I need to strengthen the tendons in my fingers (or at least in nine of them as I ruptured the tendon in my right ring finger playing rugby years ago) so that I can hold on to smaller edges and grasp larger ones for longer. I need to develop my abdominal muscles to hold me onto the rock face better and put more pressure on my feet; particularly when the climb is overhanging. I need to build up muscles in my back, shoulders and arms to be able to move more assuredly between holds that are widely spaced. I must work on my endurance, so that I do not fail climbs because I am worn out by a long series of lower moves. Finally I need to improve my technique: making my footwork more precise; paying more attention to the shape of my body and how this affects my centre of gravity and the purchase I have on holds; getting more comfortable with the tricks of the trade such as heel- and toe-hooks; learning when to be aggressive in my climbing and when to be slow and deliberate; and finally better visualising how my body fits against the rock and the best way to flow economically from one position to the next.

If I can get better in all of these areas, then maybe I will have earned my new technical rock shoes and I will be able to take advantage of the benefits that they offer. Having the right shoes can undoubtedly improve your climbing, but it is no substitute for focussing on the long list in the previous paragraph. There is no real short-cut to becoming a better climber, it just takes an awful lot of work.

A final thing to add in this section is that the Solutions offer advantages to the climber on certain types of climbs. On any overhanging, pocketed rock, they are brilliant. But the way that they shape your foot into a down-turned claw would be a positive disadvantage when trying to pad up a slab. In this second scenario, something like my worn out FiveTens (now sadly consigned to the rubbish tip) would be the tool of choice. It is important to realise that the right tool is often dictated by the task in hand and one that excels in area A may be an also-ran in area B.

Notes:

  1. Lest it be thought that the above manufacturers play only in narrow niches, I should explain that each of Boreal, FiveTen and La Sportiva produce a wide range of rock shoes catering to virtuially every type of climber from the neophyte to the world’s best.
  2. If you think that the pound dollar rates are rather strange in the above exhibits, then a few things are at play. Some are genuine differences, but others are because they are historical rates. for example, I struggled to find a US web-site that still sells Boreal Zephyrs.
  3. If you are interested in finding out more about my adventures in rock climbing, then take a look at my partner’s blog.

 
 
The role of technology in Business Intelligence

I hope that I have established that at least in the world of rock climbing, the technology that you have at your disposal is only one of many factors necessary for success; indeed it is some way from being the most important factor.

Having really poor, or worn out, rock shoes can dent your confidence and even get you into bad habits (such as not using your feet enough). Having really good rock shoes can bring some incremental benefits, but these are not as great as those to be gained by training and experience. Most of the technologically-related benefits will be realised by having reasonably good and reasonably new shoes.

While the level of a professional rock climber’s performance will be undoubtedly be improved by using the best equipment available, a bad climber with $150 rock shoes will still be a bad climber (note this is not intended to be a self-referential comment).

Requirements - Data Analysis - Information - Manage Change

Requirements - Data Analysis - Information - Manage Change

Returning to another of my passions, Business Intelligence, I see some pertinent parallels. In a series of previous articles (including BI implementations are like icebergs, “All that glisters is not gold” – some thoughts on dashboards and Short-term “Trouble for Big Business Intelligence Vendors” may lead to longer-term advantage) , I have laid out my framework for BI success and explained why I feel that technology is not the most important part of a BI programme.

My recommended approach is based on four pillars:

  1. Determine what information is necessary to drive key business decisions.
  2. Understand the various data sources that are available and how they relate to each other.
  3. Transform the data to meet the information needs.
  4. Manage the embedding of BI in the corporate culture.

Obviously good BI technology has a role to play across all of these areas, but it is not the primary concern in any of them. Let us consider what is often one of the most difficult areas to get right, embedding BI in an organisation’s DNA. What is the role of the BI tool here?

Well if you want people to actually use the BI system, it helps if the way that the BI technology operates is not a hindrance to this. Ideally the ease-of-use and intuitiveness of the BI technology deployed should be a plus point for you. However, if you have the ultimate in BI technology, but your BI system does not highlight areas that business people are interested in, does not provide information that influences actual decision-making, or contains numbers that are inaccurate, out-of-date, or unreconciled, then it will not be used. I put this a little more succinctly in a recent article: Using multiple business intelligence tools in an implementation – Part II (an inspired title I realise), which I finished by saying:

If your systems do not have credibility with your users, then all is already lost and no amount of flashy functionality will save you.

Similar points can be made about all of the other pillars. Great BI technology should be the icing on your BI cake, not one of the main ingredients.
 
 
The historical perspective

What Car?

Ajay Ohri from the DecisionStats web-site recently interviewed me in some depth about a range of issues. He specifically asked me about what differentiated the various BI tools and I reproduce my reply here:

The really important question in BI is not which tool is best, but how to make BI projects successful. While many an unsuccessful BI manager may blame the tool or its vendor, this is not where the real issues lie. I firmly believe that successful BI rests on four mutually reinforcing pillars: understand the questions the business needs to answer, understand the data available, transform the data to meet the business needs and embed the use of BI in the organisation’s culture. If you get these things right then you can be successful with almost any of the excellent BI tools available in the marketplace. If you get any one of them wrong, then using the paragon of BI tools is not going to offer you salvation.

I think about BI tools in the same way as I do the car market. Not so many years ago there were major differences between manufacturers. The Japanese offered ultimate reliability, but maybe didn’t often engage the spirit. The Germans prided themselves on engineering excellence, slanted either in the direction of performance or luxury, but were not quite as dependable as the Japanese. The Italians offered out-and-out romance and theatre, with mechanical integrity an afterthought. The French seemed to think that bizarrely shaped cars with wheels as thin as dinner plates were the way forward, but at least they were distinctive. The Swedes majored on a mixture of safety and aerospace cachet, but sometimes struggled to shift their image of being boring. The Americans were still in the middle of their love affair with the large and the rugged, at the expense of convenience and value-for-money. Stereotypically, my fellow-countrymen majored on agricultural charm, or wooden-panelled nostalgia, but struggled with the demands of electronics.

Nowadays, the quality and reliability of cars are much closer to each other. Most manufacturers have products with similar features and performance and economy ratings. If we take financial issues to one side, differences are more likely to related to design, or how people perceive a brand. Today the quality of a Ford is not far behind that of a Toyota. The styling of a Honda can be as dramatic as an Alfa Romeo. Lexus and Audi are playing in areas previously the preserve of BMW and Mercedes and so on. To me this is also where the market for BI tools is at present. It is relatively mature and the differences between product sets are less than before.

Of course this doesn’t mean that the BI field will not be shaken up by some new technology or approach (in-memory BI or SaaS come to mind). This would be the equivalent of the impact that the first hybrid cars had on the auto market. However, from the point of view of implementations, most BI tools will do at least an adequate job and picking one should not be your primary concern in a BI project.

If you are interested, you can read the full interview here.
 
 
The current reality

IBM to acquire SPSS

As my comments to Ajay suggest, maybe in past times there were greater differences between BI vendors and the tools that they supplied. One benefit of the massive consolidation that has occurred in recent years is that the five biggest players: IBM/Cognos, Oracle/Hyperion, SAP/BusinessObjects, Microsoft and (the as yet still independent) SAS all have product portfolios that are both wide and deep. If there is something that you want your BI tool to do, it is likely that any of these organisations can provide you with the software; assuming that your wallet allows it. Both the functionality and scope of offerings from smaller vendors operating in the BI arena have also increased greatly in recent times. Finding a technology that fits your specific needs for functionality, ease-of-use, scalability and reliability should not be a problem.

This general landscape is one against which it is interesting to view the recent acquisition of business analytics firm SPSS by IBM. According to Reuters, IBM’s motivations are as follows:

IBM plans to buy business analytics company SPSS Inc for $1.2 billion in cash to better compete with Oracle Corp and SAP AG in the growing field of business intelligence

Full story here.

As an aside, should both Microsoft and SAS be worried that they are omitted from this list?

Whatever the corporate logic for IBM, to me this is simply more evidence that BI technology is becoming a utility (it should however be noted that this is not the same as BI itself becoming a utility). I believe that this trend will lead to a greater focus on the use of BI technology as part of broad-based BI programmes that drive business value. Though BI has the potential of releasing massive benefits for organisations, the track record has been somewhat patchy. Hopefully as people start to worry less about BI technology and more about the factors that really drive success in BI programmes, this will begin to change.

A precursor to Business Intelligence

As with any technical innovation over the centuries, it is only when the technology itself becomes invisible that the real benefits flow.
 

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Accuracy

20 July 2009

Micropipette

As might be inferred from my last post, certain sporting matters have been on my mind of late. However, as is becoming rather a theme on this blog, these have also generated some business-related thoughts.
 
 
Introduction

On Friday evening, the Australian cricket team finished the second day of the second Test Match on a score of 152 runs for the loss of 8 (out of 10) first innings wickets. This was still 269 runs behind the England team‘s total of 425.

In scanning what I realise must have been a hastily assembled end-of-day report on the web-site of one of the UK’s leading quality newspapers, a couple are glaring errors stood out. First, the Australian number 4 batsman Michael Hussey was described as having “played-on” to a delivery from England’s shy-and-retiring Andrew Flintoff. Second, the journalist wrote that Australia’s number six batsman, Marcus North, had been “clean-bowled” by James Anderson.

I appreciate that not all readers of this blog will be cricket aficionados and also that the mysteries of this most complex of games are unlikely to be made plain by a few brief words from me. However, “played on” means that the ball has hit the batsman’s bat and deflected to break his wicket (or her wicket – as I feel I should mention as a staunch supporter of the all-conquering England Women’s team, a group that I ended up meeting at a motorway service station just recently).

By contrast, “clean-bowled” means that the ball broke the batsman’s wicket without hitting anything else. If you are interested in learning more about the arcane rules of cricket (and let’s face it, how could you not be interested) then I suggest taking a quick look here. The reason for me bothering to go into this level of detail is that, having watched the two dismissals live myself, I immediately thought that the journalist was wrong in both cases.

It may be argued that the camera sometimes lies, but the cricinfo.com caption (whence these images are drawn) hardly ever does. The following two photographs show what actually happened:

Michael Hussey leaves one and is bowled, England v Australia, 2nd Test, Lord's, 2nd day, July 17, 2009

Michael Hussey leaves one and is bowled, England v Australia, 2nd Test, Lord's, 2nd day, July 17, 2009

Marcus North drags James Anderson into his stumps, England v Australia, 2nd Test, Lord's, 2nd day, July 17, 2009

Marcus North drags James Anderson into his stumps, England v Australia, 2nd Test, Lord's, 2nd day, July 17, 2009

As hopefully many readers will be able to ascertain, Hussey raised his bat aloft, a defensive technique employed to avoid edging the ball to surrounding fielders, but misjudged its direction. It would be hard to “play on” from a position such as he adopted. The ball arced in towards him and clipped the top of his wicket. So, in fact he was the one who was “clean-bowled”; a dismissal that was qualified by him having not attempted to play a stroke.

North on the other hand had been at the wicket for some time and had already faced 13 balls without scoring. Perhaps in frustration at this, he played an overly-ambitious attacking shot (one not a million miles from a baseball swing), the ball hit the under-edge of his horizontal bat and deflected down into his wicket. So it was North, not Hussey, who “played on” on this occasion.

So, aside from saying that Hussey had been adjudged out “handled the ball” and North dismissed “obstructed the field” (two of the ten ways in which a batsman’s innings can end – see here for a full explanation), the journalist in question could not have been more wrong.

As I said, the piece was no doubt composed quickly in order to “go to press” shortly after play had stopped for the day. Maybe these are minor slips, but surely the core competency of a sports journalist is to record what happened accurately. If they can bring insights and colour to their writing, so much the better, but at a minimum they should be able to provide a correct description of events.

Everyone makes mistakes. Most of my blog articles contain at least one typographical or grammatical error. Some of them may include errors of fact, though I do my best to avoid these. Where I offer my opinions, it is possible that some of these may be erroneous, or that they may not apply in different situations. However, we tend to expect professionals in certain fields to be held to a higher standard.

Auditors

For a molecular biologist, the difference between a 0.20 micro-molar solution and a 0.19 one may be massive. For a team of experimental physicists, unbelievably small quantities may mean the difference between confirming the existence of the Higgs Boson and just some background noise.

In business, it would be unfortunate (to say the least) if auditors overlooked major assets or liabilities. One would expect that law-enforcement agents did not perjure themselves in court. Equally politicians should never dissemble, prevaricate or mislead. OK, maybe I am a little off track with the last one. But surely it is not unreasonable to expect that a cricket journalist should accurately record how a batsman got out.
 
 
Twitter and Truth

twitter.com

I made something of a leap from these sporting events to the more tragic news of Michael Jackson’s recent demise. I recall first “hearing” rumours of this on twitter.com. At this point, no news sites had much to say about the matter. As the evening progressed, the self-styled celebrity gossip site TMZ was the first to announce Jackson’s death. Other news outlets either said “Jackson taken to hospital” or (perhaps hedging their bets) “US web-site reports Jackson dead”.

By this time the twitterverse was experiencing a cosmic storm of tweets about the “fact” of Jackson’s passing. A comparably large number of comments lamented how slow “old media” was to acknowledge this “fact”. Eventually of course the dinosaurs of traditional news and reporting lumbered to the same conclusion as the more agile mammals of Twitter.

In this case social media was proved to be both quick and accurate, so why am I now going to offer a defence of the world’s news organisations? Well I’ll start with a passage from one of my all-time favourite satires, Yes Minister, together with its sequel Yes Prime Minister.

In the following brief excerpt Sir Geoffrey Hastings (the head of MI5, the British domestic intelligence service) is speaking to The Right Honourable James Hacker (the British Prime Minister). Their topic of conversation is the recently revealed news that a senior British Civil Servant had in fact been a Russian spy:

Yes Prime Minister

Hastings: Things might get out. We don’t want any more irresponsible ill-informed press speculation.
Hacker: Even if it’s accurate?
Hastings: Especially if it’s accurate. There is nothing worse than accurate irresponsible ill-informed press speculation.

Yes Prime Minister, Vol. I by J. Lynn and A. Jay

Was the twitter noise about Jackson’s death simply accurate ill-informed speculation? It is difficult to ask this question as, sadly, the tweets (and TMZ) proved to be correct. However, before we garland new media with too many wreaths, it is perhaps salutary to recall that there was a second rumour of a celebrity death circulating in the febrile atmosphere of Twitter on that day. As far as I am aware, Pittsburgh’s finest – Jeff Goldblum – is alive and well as we speak. Rumours of his death (in an accident on a New Zealand movie set) proved to be greatly exaggerated.

The difference between a reputable news outlet and hordes of twitterers is that the former has a reputation to defend. While the average tweep will simply shrug their shoulders at RTing what they later learn is inaccurate information, misrepresenting the facts is a cardinal sin for the best news organisations. Indeed reputation is the main thing that news outlets have going for them. This inevitably includes annoying and time-consuming things such as checking facts and validating sources before you publish.

With due respect to Mr Jackson, an even more tragic set of events also sparked some similar discussions; the aftermath of the Iranian election. The Economist published an interesting artilce comparing old and new media responses to this entitiled: Twitter 1, CNN 0. Their final comments on this area were:

[...]the much-ballyhooed Twitter swiftly degraded into pointlessness. By deluging threads like Iranelection with cries of support for the protesters, Americans and Britons rendered the site almost useless as a source of information—something that Iran’s government had tried and failed to do. Even at its best the site gave a partial, one-sided view of events. Both Twitter and YouTube are hobbled as sources of news by their clumsy search engines.

Much more impressive were the desk-bound bloggers. Nico Pitney of the Huffington Post, Andrew Sullivan of the Atlantic and Robert Mackey of the New York Times waded into a morass of information and pulled out the most useful bits. Their websites turned into a mish-mash of tweets, psephological studies, videos and links to newspaper and television reports. It was not pretty, and some of it turned out to be inaccurate. But it was by far the most comprehensive coverage available in English. The winner of the Iranian protests was neither old media nor new media, but a hybrid of the two.

Aside from the IT person in me noticing the opportunity to increase the value of Twitter via improved text analytics (see my earlier article, Literary calculus?), these types of issues raise concerns in my mind. To balance this slightly negative perspective it is worth noting that both accurate and informed tweets have preceded several business events, notably the recent closure of BI start-up LucidEra.

Also main stream media seem to have swallowed the line that Google has developed its own operating system in Chrome OS (rather than lashing the pre-existing Linux kernel on to its browser); maybe it just makes a better story. Blogs and Twitter were far more incisive in their commentary about this development.

Considering the pros and cons, on balance the author remains something of a doubting Thomas (by name as well as nature) about placing too much reliance on Twitter for news; at least as yet.
 
 
Accuracy an Business Intelligence

A balancing act

Some business thoughts leaked into the final paragraph of the Introduction above, but I am interested more in the concept of accuracy as it pertains to one of my core areas of competence – business intelligence. Here there are different views expressed. Some authorities feel that the most important thing in BI is to be quick with information that is good-enough; the time taken to achieve undue precision being the enemy of crisp decision-making. Others insist that small changes can tip finely-balanced decisions one way or another and so precision is paramount. In a way that is undoubtedly familiar to regular readers, I straddle these two opinions. With my dislike for hard-and-fast recipes for success, I feel that circumstances should generally dictate the approach.

There are of course different types of accuracy. There is that which insists that business information reflects actual business events (often more a case for work in front-end business systems rather than BI). There is also that which dictates that BI systems reconcile to the penny to perhaps less functional, but pre-existing scorecards (e.g. the financial results of an organisation).

A number of things can impact accuracy, including, but not limited to: how data has been entered into systems; how that data is transformed by interfaces; differences between terminology and calculation methods in different data sources; misunderstandings by IT people about the meaning of business data; errors in the extract transform and load logic that builds BI solutions; and sometimes even the decisions about how information is portrayed in BI tools themselves. I cover some of these in my previous piece Using BI to drive improvements in data quality.

However, one thing that I think differentiates enterprise BI from departmental BI (or indeed predictive models or other types of analytics), is a greater emphasis on accuracy. If enterprise BI is to aspire to becoming the single version of the truth for an organisation, then much more emphasis needs to be placed on accuracy. For information that is intended to be the yardstick by which a business is measured, good enough may fall short of the mark. This is particularly the case where a series of good enough solutions are merged together; the whole may be even less than the sum of its parts.

A focus on accuracy in BI also achieves something else. It stresses an aspiration to excellence in the BI team. Such aspirations tend to be positive for groups of people in business, just as they are for sporting teams. Not everyone who dreams of winning an Olympic gold medal will do so, but trying to make such dreams a reality generally leads to improved performance. If the central goal of BI is to improve corporate performance, then raising the bar for the BI team’s own performance is a great place to start and aiming for accuracy is a great way to move forward.
 


 
A final thought: England went on to beat Australia by precisely 115 runs in the second Test at Lord’s; the final result coming today at precisely 12:42 pm British Summer Time. The accuracy of England’s bowling was a major factor. Maybe there is something to learn here.
 

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A blast from the past…

25 June 2009

Gutenberg Printing Press

I recently came across a record of my first ever foray into the world of Business Intelligence, which dates back to 1997. This was when I was still predominantly an ERP person and was considering options for getting information out of such systems. The piece in question is a brief memo to my boss (the CFO of the organisation I was working at then) about what I described as the OLAP market.

This was a time of innocence, when Google had not even been incorporated, when no one yet owned an iPod and when, if you tried to talk to someone about social media, they would have assumed that you meant friendly journalists. All this is attested to by the fact that this was a paper memo that was printed and circulated in the internal mail – remember that sort of thing?

Given that the document has just had its twelfth birthday, I don’t think I am breeching any confidences in publishing it, though I have removed the names of the recipients for obvious reasons.
 

INTERNAL MEMORANDUM

To: European CFO
cc: Various interested parties
From: Peter Thomas
Date: 16th June 1997
Subject: What is OLAP?

 
On-Line Analytical Processing (OLAP) is a category of software technology that enables analysts, managers and executives to gain insight into data. This is achieved by providing fast, consistent, interactive access to a wide variety of possible views of information. This has generally been transformed from raw data to reflect the real dimensionality of the enterprise.

There are around 30 vendors claiming to offer OLAP products. A helpful report by Business Intelligence[1] (an independent research company) estimates the market share of these . As many of these companies sell other products, the following cannot be viewed as 100% accurate. However the figures do provide some interesting reading.
 

Vendor

1996

1995

Market Position

Share (%)

Market Position

Share (%)

Oracle

1

19.0%

1

20.0%

Hyperion Software

2

18.0%

2

19.0%

Comshare

3

12.0%

3

16.0%

Cognos

4

9.0%

4

5.0%

Arbor Software

5

4.8%

7

2.9%

Holistic Systems

6

4.3%

6

4.7%

Pilot Software

7

4.0%

5

4.8%

MircoStrategy

8

3.5%

9

2.1%

Planning Sciences

9

2.6%

8

2.3%

Information Advantage

10

1.8%

10

1.4%

 
In this group, some companies (Hyperion, Comshare, Holistic, Pilot Software and Planning Services) provide either complete products or extensive toolkits. In contrast some vendors (such as Arbor and – outside the top ten – Applix) only sell specialist multi-dimensional databases. Others (e.g. Cognos and – outside the top ten – BusinessObjects and Brio Technology), offer client based OLAP tools which are basically sophisticated report writers. The final group (including MicroStrategy and Information Advantage) offer a mixed relational / dimensional approach called Relational OLAP or ROLAP.

If we restrict ourselves to the “one-stop solution” vendors in the above list, it is helpful to consider the relative financial position of the top three.
 

Vendor

Market Cap.[2]

($m)

Turnover

($m)

Profit

($m)

Oracle

32,405

4,223[3]

603

Hyperion Software

335

173[4]

9

Comshare

132

119[5]

(9)

 

[1] The OLAP Report by Nigel Pendse and Richard Creeth © Business Intelligence 1997
[2] As at June 1997
[3] 12 months to March 1997
[4] 12 months to June 1996
[5] 12 months to June 1996

 


 
It is of course also worth pointing out that I used to disagree with what Nigel Pendse wrote a lot less back then!
 

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Neil Raden on sporting analogies and IBM System S – Intelligent Enterprise

22 May 2009

neil-raden

I have featured Neil Raden’s thoughts quite a few times on this blog. It is always valuable to learn from the perspectives and insights of people like Neil who have been in the industry a long time and to whom there is little new under the sun.

In his latest post, IBM System S: Not for Everyone (which appears on his Intelligent Enterprise blog), Neil raises concerns about some commentators’ expectations of this technology. If business intelligence is seen as having democratised information, then some people appear to feel that System S will do the same for real-time analysis of massive data sets.

While intrigued by the technology and particular opportunities that System S may open up, Neil is sceptical about some of the more eye-catching claims. One of these, quoted in The New York Times, relates to real-time analysis in a hospital context, with IBM’s wizardry potentially alerting medical staff to problems before they get out of hand and maybe even playing a role in diagnosis. On the prospects for this universal panacea becoming reality, Neil adroitly observes:

How many organizations have both the skill and organizational alignment to implement something so complex and controversial?

Neil says that he is less fond of sporting analogies than many bloggers (having recently posted articles relating to cricket, football [soccer], mountain biking and rock climbing, I find myself blushing somewhat at this point), but nevertheless goes on to make a very apposite comparison between professional sportsmen and women and carrying out real-time analysis professionally. Every day sports fans can appreciate the skill, commitment and talent of the professionals, but these people operate on a different plane from mere mortals. With System S Neil suggests that:

The vendor projects the image of Tiger Woods to a bunch of duffers.

I think once again we arrive at the verity that there is no silver bullet in any element of information generation (see my earlier article, Automating the business intelligence process?). Many aspects of the technology used in business intelligence are improving every year and I am sure that there are many wonderful aspects to System S. However, this doubting Thomas is as sceptical as Neil about certain of the suggested benefits of this technology. Hopefully some concrete and useful examples of its benefits will soon replace the current hype and provide bloggers with some more tangible fare to write about.
 


 
You can read an alternative perspective on System S in
Merv Adrian’s blog post about InfoSphere Streams, the commercialised part of System S.
 


 
Other articles featuring Neil Raden’s work include: Neil Raden’s thoughts on Business Analytics vs Business Intelligence and “Can You Really Manage What You Measure?” by Neil Raden.

Other articles featuring Intelligent Enterprise blog posts include: “Gartner sees a big discrepancy between BI expectations and realities” – Intelligent Enterprise and Cindi Howson at Intelligent Enterprise on using BI to beat the downturn.
 


 
Neil Raden is founder of Hired Brains, a consulting firm specializing in analytics, business Intelligence and decision management. He is also the co-author of the book “a consulting firm specializing in analytics, business Intelligence and decision management. He is also the co-author of the book Smart (Enough) Systems.
 

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

19 May 2009

Introduction

  Ann All IT Business Edge  

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

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

The other people that Ann quotes are:

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

 
Some differences of opinion

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

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

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

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

By way of contrast Pendse favours:

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

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

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

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

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

Manchester United versus Liverpool

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

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

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

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

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

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

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


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

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Using multiple business intelligence tools in an implementation – Part I

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

Introduction

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

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

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

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

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

London Bridge circa 1600

London Bridge circa 1600

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

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

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

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

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

One-stop shopping

One-stop shopping

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

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

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

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

What he actually said was:

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

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

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

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

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

 
A more important consideration

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

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

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

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


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

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