No-fooling: A new blog-tagging meme – by Curt Monash

30 March 2010

Software Memories - a Curt Monash blog

By way of [very necessary] explanation, this post is a response to an idea started on the blog of Curt Monash (@CurtMonash), doyen of software industry analysts. You can read the full article here. This is intended as an early April Fools celebration.

A summary:

[...] the Rules of the No-Fooling Meme are:

Rule 1: Post on your blog 1 or more surprisingly true things about you,* plus their explanations. I’m starting off with 10, but it’s OK to be a lot less wordy than I’m being. I suggest the following format:

  • A noteworthy capsule sentence. (Example: “I was not of mortal woman born.”)
  • A perfectly reasonable explanation. (Example: “I was untimely ripped from my mother’s womb. In modern parlance, she had a C-section.”)

Rule 2: Link back to this post. That explains what you’re doing.
Rule 3: Drop a link to your post into the comment thread. That will let people who check here know that you’ve contributed too.
Rule 4: Ping 1 or more other people encouraging them to join in the meme with posts of their own.

*If you want to relax the “about you” part, that’s fine too.

I won’t be as dramatic as Curt, nor will I drop any names (they have been changed to protect the guilty). I also think that my list is closer to a “things you didn’t know about me” than Curt’s original intention, but hopefully it is in the spirit of his original post. I have relaxed the “about me” part for one fact as well, but claim extenuating circumstances.

My “no-fooling” facts are, in (broadly) reverse chronological order:

  1. I have recently corrected a Physics paper in Science – and please bear in mind that I was a Mathematician not a Physicist; I’m not linking to the paper as the error was Science’s fault not the scientists’ and the lead author was very nice about it.
  2. My partner is shortly going to be working with one of last year’s Nobel Laureates at one of the world’s premier research institues – I’m proud, so sue me!
  3. My partner, my eldest son and I have all attended (or are attending) the same University – though separated by over 20 years.
  4. The same University awarded me 120% in my MSc. Number Theory exam – the irony of this appeals to me to this day; I was taught Number Theory by a Fields Medalist; by way of contrast, I got a gamma minus in second year Applied Mathematics.
  5. Not only did I used to own a fan-site for a computer game character, I co-administered a universal bulletin board (yes I am that old) dedicated to the same character – even more amazingly, there were female members!
  6. As far as I can tell, my code is still part of the core of software that is used rather widely in the UK and elsewhere – though I suspect that a high percentage of it has succumbed to evolutionary pressures.
  7. I have recorded an eagle playing golf – despite not being very good at it and not playing at all now.
  8. I have played cricket against the national teams of both Zimbabwe (in less traumatic times) and the Netherlands – Under 15s and Under 19s respectively; I have also played both with and against an England cricketer and against a West Indies cricketer (who also got me out), but I said that I wasn’t going to name drop.
  9. [Unlike Curt] I only competed in one chess tournament – I came fourth, but only after being threatened with expulsion over an argument to do with whether I had let go of a bishop for a nanosecond; I think I was 11 at the time.
  10. At least allegedly, one of my antecedents was one of the last hangmen in England – I’m not sure how you would go about substantiating this fact as they were meant to be sworn to secrecy; equally I’m not sure that I would want to substantiate it.
  11. And a bonus fact (which could also be seen as oneupmanship vis à vis Curt):

  12. One of the articles that I wrote for the UK climbing press has had substantially more unique views than any of my business-related articles on here (save for the home page itself) – sad, but true, if you don’t believe me, the proof is here.

 


 
Other Monash-related posts on this site:

 

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Limitations of Business Intelligence

28 March 2010

My predictive analytics model didn't foresee this outcome, therefore it can't be happening. With apologies to the makers of 2012.

Introduction

“So how come Business Intelligence didn’t predict the World Economic Crisis?”

I have seen countless variants of the above question posted all over the Internet. Mostly it is posed on community forums and can often be a case of someone playing Devil’s Advocate, or simply wanting to stir up a conversation. However I came across reference to this question recently in the supposedly more sober columns of The British Computer Society (now very modishly re branded as BCS – The Chartered Institute for IT). According to the font of all human knowledge, the BCS is:

“a professional body and a learned society that represents those working in Information Technology. Established in 1957, it is the largest United Kingdom-based professional body for computing”

The specific article was entitled Data quality issues ‘to blame for financial crises’ (I’m not sure whether the BCS is saying that data quality issues are responsible for more than one financial crisis, or whether there is a typo in the last word). The use of quotation marks is also apt as the BCS seem to be reliant for the content of this article on both the opinions of the owner of a on-line community and a piece of commercial research finding that:

“more than 75 per cent of top financial services firms are to increase the amount of money they allocate to combating data quality and consistency issues”

and

“a further 44 per cent said clarity of data would be their ‘key focus’”

How this adds up to the conclusion appearing in the title is perhaps something of a mystery. The process is not exactly a shining example of how to turn source data into actionable information.
 
 
Lessons from Lehmans

Theirs not to reason why,  Theirs but to do & die,  Into the valley of Death  Rode the six hundred

It is arguable (though maybe not on the evidence presented in the BCS article) that poor data quality may have contributed to the demise of say Lehman Brothers. However the following line of argument is a bit of a reach:

  1. Poor data quality [arguably] contributed to the failure of Lehman Brothers
  2. Lehman Brothers’ failure was a trigger for a broader collapse of the world economy
  3. Therefore Lehman’s collapse was solely to blame for the crisis
  4. Thus (as per the BCS): Data quality issues [are] ‘to blame for financial crises’ [sic.]

There are a number of problems with this logic. To address just one, the failure of Lehmans did not cause the recession, it precipitated problems that were much larger, had been building up for years and which would have been triggered by something sooner or later (all balloons either deflate or pop eventually, even if not pierced by a needle).

By way of analogy, thinking that the assassination of Archduke Ferdinand was the sole reason for the outbreak of The Great War would be an over-simplification of history; greater forces were at work. Does a dropped match [proximate cause] lead to a massive forest fire, or are the preceding months of drought [distal cause] more to blame, with the fire an accident waiting to happen?

To most observers the distal causes of the recession were separate bubbles that had built up in a variety of asset classes (e.g. residential property) that were either going to deflate slowly, or go bang! Leverage created by certain classes of financial instruments made a bang more likely, but these instruments themselves did not create the initial problems either.

Extending our earlier analogy, if the asset bubbles were a lack of rain, then maybe the use of financial instruments – such as collateralised debt obligations – was a drying wind. In this scenario, Lehman Brothers was the dropped match, nothing more. If it wasn’t them, it would have been another event. So for causes of the World Economic crisis, we need to look more broadly.
 
 
Cui culpa?

First published in September 1843 to take part in 'a severe contest between intelligence, which presses forward, and an unworthy, timid ignorance obstructing our progress' [nice use of the Oxford / Harvard comma BTW]

Before I explore whether BI should have performed better in predicting the most severe recession since the 1930s, it is perhaps worth asking a more pertinent question, namely, “so how come macroeconomics didn’t predict the World Economic Crisis?” Again according to the font:

macroeconomics is a branch of economics that deals with the performance, structure, behavior and decision-making of the entire economy, be that a national, regional, or the global economy

so surely it should have had something to say in advance about this subject. However at least according to The Economist (who one would assume should know something about the area):

[Certain leading economists] argue that [other] economists missed the origins of the crisis; failed to appreciate its worst symptoms; and cannot now agree about the cure. In other words, economists misread the economy on the way up, misread it on the way down and now mistake the right way out.

On the way up, macroeconomists were not wholly complacent. Many of them thought the housing bubble would pop or the dollar would fall. But they did not expect the financial system to break. Even after the seizure in interbank markets in August 2007, macroeconomists misread the danger. Most were quite sanguine about the prospect of Lehman Brothers going bust in September 2008.

Source: The Economist – 16th July 2009

[Note: a subscription to the magazine is required to view this article]

In a later article in the same journal, Robert Lucas, Professor of Economics at the University of Chicago, rebutted the above critique, stating:

One thing we are not going to have, now or ever, is a set of models that forecasts sudden falls in the value of financial assets, like the declines that followed the failure of Lehman Brothers in September. This is nothing new. It has been known for more than 40 years and is one of the main implications of Eugene Fama’s “efficient-market hypothesis”, which states that the price of a financial asset reflects all relevant, generally available information. If an economist had a formula that could reliably forecast crises a week in advance, say, then that formula would become part of generally available information and prices would fall a week earlier.

Source: The Economist – 6th August 2009

[Note: a subscription to the magazine is required to view this article]

So if economists had at best a mixed track record in predicting the crisis (and can’t seem to agree amongst themselves about the merits of different ways of analysing economies), then it seems to me that Business Intelligence has its work cut out for it. As I put it in an earlier article, The scope of IT’s responsibility when businesses go bad:

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

As an aside, the above-referenced article argues that IT professionals should not try to distance themselves too much from business problems. My basic thesis being that if IT is shy about taking any responsibility in bad times, it should not be surprised when its contributions are under-valued in good ones. However this way lies a more philosophical discussion.

My opinion on why questions about whether or not business intelligence predicted the recession continue to be asked is that they relate to BI being oversold. Oversold in a way that I believe is unhealthy and actually discredits the many benefits of the field.
 
 
Crystal Ball Gazing

One of these things is not like the others,  One of these things just doesn't belong,  Can you tell which thing is not like the others  By the time I finish my song?

The above slide is taken from my current deck. My challenge to the audience is to pick the odd-one-out from the list. Assuming that you buy into my Rubik’s Cube analogy for business intelligence, hopefully this is not an overly onerous task.

Business Intelligence is not a crystal ball, Predictive Analytics is not a crystal ball either. They are extremely useful tools – indeed I have argued many times before that BI projects can have the largest payback of any IT project – but they are not universal panaceas.

The Old Lady of Threadneedle Street is clearly not a witch

An inflation prediction from The Bank of England
Illustrating the fairly obvious fact that uncertainty increases in proportion to time from now.

Business Intelligence will never warn you of every eventuality – if something is wholly unexpected, how can you design tools to predict it? Statistical models will never give you precise answers to what will happen in the future – a range of outcomes, together with probabilities associated with each is the best you can hope for (see above). Predictive Analytics will not make you prescient, instead it can provide you with useful guidance, so long as you remember it is an prediction, not fact.

It is amazing the things that people find to do in their spare time, isn't it?

However, in most circumstances, the fact that your Swiss Army knife doesn’t have the highly-desirable “tool for removing stones from horses hooves” does not preclude it from fulfilling its more quotidian functions well. The fact that your car can’t do 0-60 mph (0-95 kph, or 0-26 ms-1 if you insist) in less than 4 seconds, does not mean that it is incapable of getting you around town perfectly happily. Tools should be fit-for-purpose, not all-purpose.

Unfortunately, sometimes business intelligence can be presented as capable of achieving the impossible; this is only going to lead to disillusionment with the area and to the real benefits not being seized. Also it is increasingly common for vendors and consultancies to claim that amazing results can be obtained with BI quickly, effortlessly and (most intoxicatingly) with minimum corporate pain. My view is that these claims are essentially bogus. Like most things in life, what you get out of business intelligence is highly connected with what you put it.

If you want some pretty pictures showing some easy to derive figures, then progress in days rather than months is entirely feasible. But if you want useful insights into your organisation’s performance that can lead to informed decision making, then time is required to work out what makes the company tick, how to best measure this to drive action and – a part that is often missed – to provide the necessary business and technical training to allow users to get the best out of tools. Here my experience is that there are few meaningful short-cuts.
 
 
Crystallising BI benefits

Adopting a more positive tone, if done well, then I believe that business intelligence can do a lot of great things for organisations. A brief selection of these includes:

  1. Dissect corporate performance in ways that enable underlying drivers to be made more plain (our drop-off in profitability is due to pricing pressures in Subsidiary A and poor retention of mid-sized accounts in Territory B, compounded by a fall in the rate of new business acquisition in Industry Segment C).
  2. Amalgamate data from disparate sources, allowing connections to be made between different, but related, areas (high turnover of staff in our customer services centre has coincided with both increased lead times for shipments and greater incidence of customer complaints)
  3. Give insights as to how customers are behaving and how they react to corporate initiatives (our smaller customers appear to be favouring bundled services, which include Feature W, however there was increased uptake of unbundled Service Z following on from our recently published video extolling its virtues)
  4. Measure the efficacy of business initiatives (was the launch of Product X successful? did our drive to improve service levels lead to better business retention?)
  5. Transparently monitor business unit achievement (Countries P, Q and R are all meeting their sales and profitability targets, howvever Country Q is achieving this with 2 fewer staff per $1m revenue)
  6. Provide indications (not guarantees) of future trends (sales of Service K are down 10% on this time last year and fell on a seasonally-adjusted basis for four of the last six months)
  7. Isolate hard-to-find relations (the biggest correlation with repeat business is the speed with which reported problems are addressed, not the number of problems that occur)

It is worth pointing out that a lot of the above is internally focussed, about the organisation itself and only tangentially related to the external environment in which it is operating. Some companies are successfully blending their internal BI with external market information, either derived from specialist companies, or sometimes from industry associations. However few companies are incorporating macroeconomic trends into their BI systems. Maybe that’s because of the confusion endemic in Economics that was referenced above.

However there is another reason why BI is not really in the business of predicting overall economic trends. In the preceding paragraphs, I have stressed that it takes lot of effort to get BI working well for a company. To have the same degree of benefit for a nation’s economy, you would have to aggregate across thousands of companies and deal with the same sort of inconsistency in data definitions and calculation methodologies that are hard enough to fight within an organisation; but orders of magnitude worse.

Nationwide (let alone global) BI would be a Herculean (and essentially impossible) task. Instead simplifying assumptions have to be made, and such assumptions do not generally lead to high-quality BI implementations; which are typically highly-tuned to the characteristics of individual organisations.
 
 
Leverage

"Give me a place to stand, and I shall move the earth"

There are of course organisations whose general profitability exceptionally depends on broad economic trends. These include the much maligned banks of varying flavours. The unique problem that many of these face is of leverage. While a 1% fall in economic activity might have a 1% impact on the revenues of a manufacturing company (in fact seldom is the relationship so simple), it might have a catastrophic impact on a bank, depending on how their portfolio is structured.

To look at the simplest form of option, which pays out the differential between the market price and a floor of £50. If conditions in the economy drive the share price from £55 to £50, the regular shareholder has lost 9% of their investment; the option holder has lost 100%. So while both the shareholder and option-holder will have an equal chance of experiencing such a price-fall, the impact on them will be radically different (in this case by 91%). Like BI, derivatives are a very useful tool, however they also need to be used appropriately.
 
 
Closing thoughts

You will notice an absent of fortune-telling from the above list of BI benefits. As indispensable as I believe good BI is to organisations of all shapes and sizes, if fortune-telling is your desire then my advice is to forswear BI and wait until this lady is next in town…

...though of course you may not be able to foretell when this will be
 


 
For readers who are interested in this area, I recommend Neil Raden’s artcile: Wherefore Analytics on Wall Street? An Homage to Hy Minsky.
 

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Feasibility studies continued…

28 March 2010
These make a very disconcerting popping noise when you suffer them

A2 pulley injuries. Partial tear (left) and complete tear (right).
Images © Eric J. Horst, via http://www.nicros.com

Back in May 2009 I wrote about The importance of feasibility studies in business intelligence. More recently I penned a piece entitled Running before you can walk, which compared the circumstances behind me injuring my finger rock climbing to how IT teams can sometimes behave when under pressure.

I started my own feasibility study today, climbing [sadly only indoors] for the first time in the six, or so, weeks since I injured myself. Learning from my previous impetuousness I stuck to lowly V0s, working up only as far as V2 (for anyone interested an explanation of bouldering grades can be found here). My patience in forgoing climbing for a month and a half, together with my caution today seems to have paid off. Aside from a few tweaks, my damaged finger seems to have come through OK. I now need to remember to build things up very slowly and back-off at the first sign of any crunchiness whatsoever.

As per my previous analogy, it similarly takes time to turn round business or IT performance. Change is more of a marathon than a sprint (though often some basic things can be done a lot quicker). Staying with the area of rock climbing / business cross-overs, another previous article – Perseverance – highlighted the importance of this attribute in both areas. My aim is to take my own advice!
 

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The Business Intelligence / Data Quality symbiosis

22 March 2010

The possible product of endosymbiosis of proteobacteria and eukaryots

As well as sounding like the title of an episode of The Big Bang Theory, the above phrase is one I just used when commenting on an article from the Data and Process Advantage Blog.

I rather like it and think it encapsulates the points that I have tried to make in my earlier post, Using BI to drive improvements in data quality.
 


 
I’m not sure whether Google evidence would stand up in court, but I may have coined a new phrase here:

Search google.com for “Business Intelligence Data Quality symbiosis”
 

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Presenting in public

21 March 2010

Not a PowerPoint slide in sight

Introduction

I seem to have acquired the habit of presenting in public. Early in my career, when I worked for a software house, I did a lot of product demonstrations and also ended up regularly presenting new functionality at my company’s user group; so I guess this is where things started.

When thinking about presenting outside of my own corporate environment, I made my debut at a Cognos Europe press summit in Barcelona back in March 2004. Coincidentally this was also the occasion that Cognos supremo Ron Zambonini took his final bow at the company – I trust it was not my talk that pushed him over the edge.

Since then, I have spoken at over 20 seminars and other events, the most notable of which are listed here. Generally I have had very positive feedback, both in person and via the, now ubiquitous, speaker assessment questionnaires that event organisers love.

Despite my scepticism about recipes for success, I thought that it might be worth passing on a few basic tips; approaches that have worked for me over the years. As with many things that we learn, several of these are pointers that I picked up via getting it a bit wrong and trying something slightly different next time round. I’m a great believer in trial and error!

A couple of notes up-front:

  • I am an IT person at heart and in the following I often take this perspective, e.g. this is how you should approach IT matters when speaking to people without a background in the area. I will assume readers are more than capable of transposing this to a more general situation when any specialist presents to people without a background in their area of expertise.
  • A lot of the following assumes that you are using PowerPoint or something similar to present. Many people loathe PowerPoint presentations. My take is the same as with any other tool, it’s not the technology, it’s how people use it. I have sat through deeply boring PowerPoint presentations and highly professional and thoughtfully constructed ones; it’s all down to the presenter. Nevertheless some of the following points would apply to all public speaking, whether accompanied by slides or not.

With these thoughts in mind, let’s leap in.
 
 
1. Be careful what you speak about and to whom

"The ability to use tools has been suggested to indicate advanced physical cognition in animals. Here we show that rooks, a member of the corvid family that do not appear to use tools in the wild are capable of insightful problem solving related to sophisticated tool use, including spontaneously modifying and using a variety of tools, shaping hooks out of wire, and using a series of tools in a sequence to gain a reward. It is remarkable that a species that does not use tools in the wild appears to possess an understanding of tools rivaling habitual tool users such as New Caledonian crows and chimpanzees. Our findings suggest that the ability to represent tools may be a domain-general cognitive capacity rather than an adaptive specialization and questions the relationship between physical intelligence and wild tool use." - Dude?

This might seem a very obvious point to start with, but I have been guilty of getting this one wrong on at least one occasion. On subject matter, it only makes sense to talk about areas of which you have a really good understanding; why else would anyone want to listen to you? Beyond this, the content of your presentation needs to be pertinent to the audience.

It is no good being a renowned expert on insightful tool-use in corvidae and then looking to address a convention of skate-boarders. More prosaically, on the basis of delivering a well-received talk on Business Intelligence, the company that organised this event convinced me to speak at a further conference whose topic was at best tangentially related. This turned out to be a low point for me in public presenting and I learnt to be a bit more careful about which seminars to speak at. It doesn’t matter how informed and engaging your talk is, if it is not relevant to the people you are delivering it to, then things are not going to go well.
 
 
2. Know your audience

An averaged-sized crowd for a Business Intelligence seminar

Expanding on the second part of point 1. assuming that your audience has some general interest in what you are going to talk about, then it is important that you highlight the elements that are going to be most pertinent to them. So when I speak to a general audience about Business Intelligence, I might preface the talk with a brief introduction to the area and provide some definitions. When presenting to BI professionals, this would clearly be superfluous.

Looking at this the other way round, when talking to people with a technical background in BI, I might spend more time covering my ideas about the role of change management. This is because this may be a success factor that they have not focussed on as much as others. It is also important to tailor your vocabulary to the audience. IT people may love (and understand) your jargon, but it is unlikely to help more general audiences to engage with you.
 
 
3. Set the length of your presentation well within the time available

Messe tenus propria vive (Persius)

Given that you are going to deliver an informative, entertaining and insightful presentation, it makes sense to make time for all of the excited questions that this will lead to. Allow sufficient time for this.

In general if you have a 30 minute slot, then aim to speak for no more than 20 minutes of it. If your session is scheduled for a hour, then look to speak for no more than 45 minutes. Ideally you will have a break (or at least a change of pace) somewhere in the middle as well, because 45 minutes is a long time to speak for – and an even longer time to listen for! Use dry runs of your presentation (see 8. below) to make sure that you hit the desired time without either rushing or taking too leisurely a pace.

This approach to timing can also help you if you need to help the organisers to make up time after the inevitable overruns of earlier presentations / coffee breaks; something that both they and delegates tend to be grateful for.
 
 
4. Be punchy

I coulda had class. I coulda been a contender. I coulda been somebody.

This follows on from point 3. above. As regular readers of this column will know (and perhaps as attested to by this article) I am no stranger to verbosity. However I hope that I am quite different when presenting. While loquaciousness and elliptical arguments may have their place in written work, they are the enemy of the public speaker (and their audiences). Think about the main points that you want to cover and aim to achieve this in a crisp manner. If listeners are interested in greater detail, then they can ask questions, or chat to you about their specific queries afterwards.
 
 
5. Have a structure and tell people about it

A blue[stone]print for your presentation

In your presentation you are looking to convey ideas, or provide recommendations, or even just to make provocative suggestions. This is going to go a lot better if you work out in advance what you want to do and how you are going to do it. When actually presenting, it is a good idea to start out by explaining what your talk is going to cover and the broad points that you want to make. This could take the form of an agenda slide, or maybe a brief preamble according to your personal style.

In particular if you are speaking for more than say 15 minutes, it is worth breaking up your subject matter into sections. At the end of section A pause to re-emphasise the main points of what you have just covered. Pause again and introduce the next section. If you can put this into the context of the overall talk, then so much the better.
 
 
6. A picture paints a thousand words

I tend to have a somewhat visual approach to absorbing ideas and over time this has come to influence my presentation style. To illustrate how my approach has shifted, here are two slides from presentations that I have given. The first is from the Cognos Press Summit I reference at the beginning of this article. The second is a more recent presentation, dating from late 2009. I much more frequently take the latter approach nowadays.

Rather wordy, old-style slide

Cognos Press Summit - Barcelona - March 2004

More recent, visually oriented slide

Obis Omni Forum - London - September 2009

A more pictorial approach is likely to stick in people’s minds. Also it has the benefit of allowing you some latitude around what points you actually make while displaying the slide. There are going to be times when text is appropriate, but then it should not be so dense that you need opera glasses to read it. Again brevity is the key.
 
 
7. Don’t simply recite your bullet points

Assume that your audience is at above kindergarten level

If you have some text-based slides, which is generally likely to be the case, never, ever, ever, under any circumstances simply repeat what you have written. By all means use bullet points as reminders to discuss a particular area, but assume that your audience is capable of reading themselves!

Your aim should be to use the bullets as a framework around which to weave the story that you are telling. Incidentally this is another argument for not having text-dense slides as if you have 15 bullet points and take two minutes expanding on each, you are going to spend most of your presentation on a single slide; which might become a little dull.
 
 
8. If you fail to prepare, you prepare to fail

If at first you don't succeed...

I am not a big fan of adages, but this one stuck in my mind from early on in my professional career. Although it is a general point, I think it has particular applicability to presenting in public. This activity is not a million miles away from acting. Would you expect to go and see a stage play where the cast were constantly forgetting their lines or speaking in a dull monotone the entire time?

When you actually present, you need to be entirely comfortable about your material so that you can focus on doing the best job of presenting it. It can be nerve-wracking enough standing up to speak, but feeling that you have not prepared well enough is ten times worse. You need to do more than read through your notes a few times. You need to have run through your presentation a few times as well. Ideally this will have been via presenting to someone else.

I am lucky enough that my partner and I both have to give presentations; mine business-focussed, hers scientifically-focussed. This means that we both act as a tame audience for the other. Nevertheless I have also spent quite a bit of time in hotel rooms presenting out loud to myself or the mirror. This may seem mildly psychotic, but trust me it helps.

As mentioned above, another benefit of practice is that you can time yourself in order to get a sense of pace. If you know that you will finish in say 20 minutes with neither rushing, nor dawdling, you can relax a little more and not be constantly focused on clock-watching.

It is also useful to have a dry-run with someone who is not familiar with the subject you are speaking about. At a seminar you are not going to be presenting to people who are au fait with your day-to-day work, or the details of what your organisation does, or the issues that are important in your industry. These are things that you need to make explicit when you speak. Again my partner is invaluable here. She will point out when I say something that might be clear to me, or my colleagues, but impenetrable to the uninitiated.

One thing that is important with any run-throughs is to listen to the feedback that you get. If someone says that you went too fast or too slow, your probably did. If they say that you didn’t make a point clearly, then you probably were unclear. If you were not animated enough (or too animated) then this is something to think about addressing. This type of feedback is invaluable and should be taken constructively.
 
 
9. Embrace your nerves

Starring Jane Wyman, Marlene Dietrich, Michael Wilding and Richard Todd

Standing up to speak in front of a group of strangers is undeniably a little intimidating. Even with the number of times that I have done this myself, I still get butterflies in my stomach each time my turn to present approaches. However, I have learnt to tell myself that this is simply a build up of adrenaline and that this hormone will simply condition me to perform better.

Nerves are generally a good sign, they indicate that you care about what you are going to do and that your body is gearing up to give it your best shot. Thought of this way, apprehension can be a positive thing. In any case, it is never going to go away, so if you are going to present in public, you had better get used to it.
 
 
10. Check out the venue and your slides

Small arachnids in superfamily Ixodoidea that, along with other mites, constitute the Acarina

I appreciate that this is not always possible, but if you can get access to the auditorium before the seminar starts, or in a break, this is invaluable. Stand on the stage. Accustom yourself to the room. Work out where you are going to stand, or if you are like me, what scope you have for pacing about. If you are going to be mic’ed-up then go through this with the sound engineer and make sure that everything is OK (also remember to turn off the mic when you are not presenting and to turn it on when you are – both easily forgotten).

If there is a pointing device, or a clicker to advance your slides, check that these work and you know how to use them. Finally flip through all of your slides, checking that the text has not been scrambled and that any builds or animations work OK. If you find a problem, there may not be time to fix it, but at least you won’t be surprised later.
 
 
11. Don’t expect to be perfect

Yuvraj Singh of India hits a six (the maximum score in cricket) off each of the six balls of an over - sadly against England

If you have properly prepared (see point 8. above) then you will be fine. If you are OK with your material, even if you only say 75% of what you planned to say, this should not be problematic. It is inevitable that you will forget something, or even stumble over a couple of phrases here or there. The important thing is to not let this faze you, no one will notice your omission, and the occasional glitch in your delivery is to be expected. So long as you simply move on and don’t let minor set backs throw you, all will be well.

The worst thing is to focus on a small issue, which will inevitably distract you, leading you to make more mistakes and creating a spiral of death. Often if you do forget to say something on Slide X, you can say it on Slide Y instead, or mention it in the Q&A session. Telling yourself in advance that it doesn’t matter if you are not 100% perfect is perhaps a good way to set yourself up for success.
 
 
12. Try to maintain a sense of humour

Recommended footwear for presenters

I am not suggesting that you tell a lot of jokes, particularly if this is not your forte. If there is something that has raised a laugh for you previously then consider using it again, but you are not meant to be a stand-up comedian. However a certain lightness of touch never goes amiss and if you can drop in some self-deprecation along the way, this can help to engage better with your audience. No one is going to warm to an overly serious presenter, let alone a pompous one, so try to display a degree of humility as well.
 
 
13. Ask for feedback and actually review any questionnaires that you get back

So how was it for you?

The same as anything else in life the more that you present in public, the better you will get at it. Talk to the people who asked you to present and ask them how they thought things went and whether they had received any comments about your speech; listen to what they tell you. As mentioned above, it is becoming increasingly common to ask delegates to rate speakers. Instead of getting defensive about any adverse comments, think about how you could do things differently next time.
 
 
14. Be yourself

The author being himself

It is an essentially rather contrived thing to stand up in front of an audience and present. Above I have compared it to performing on the stage. There is however one difference. The actors in a play are adopting the personae of their characters; you are playing yourself. That is something important to remember. If you try to be someone else when presenting, you will come across as false. The fact that you have been asked to present is most likely testimony to you having done something right. Your own personality has undoubtedly played a big part in achieving this, so let it shine through.
 
 
Will slavishly following the above recommendations make you into a stellar presenter? Probably not, but there may be some things that you can take from what has worked for me, add to your own experiences, garnish with your personal style and arrive at a formula that is right for you. Good luck with this process. Presenting in public can be a very rewarding thing to do, so if you get the chance plunge right in and then maybe you can pass some tips on to me.
 

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Business logic

20 March 2010

The dot product of the original sketch and my plagiarism of it is 0

With enormous apologies to Randall Munroe of xkcd.com fame; from whose much funnier, and obviously more original, sketch entitled “GOTO” the above was shamelessly adapted.
 


 
Comic strip adapted with the kind permission of the copyright holder.
 

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Correlation?

14 March 2010

Top 50 posts over the last 8 month period. An R squared of 0.0116 is not overly impressive is it? Please note that this post cannot be accused of being self-referential.

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The Big Picture

14 March 2010

Click for a big picture!
 
 
Legitimate labels?

It has become part of the business lexicon, “he’s a big picture guy”, [by contrast] “she’s a details woman”. It is the sort of thing that you hear, file away and which maybe becomes something that colours your view of the person in question going forward.

You often hear the two things said in one breath, “Jane is great at strategy, but isn’t a details person”, “Joe can deal with the nitty gritty, but can’t grasp the big picture”. What could be more sensible to say than that? Doesn’t it chime with the old adage about not seeing the wood for the trees?

I have touched on this area a few times before. In Pigeonholing – A tragedy, I suggested that because someone is good in one area of life, it does not automatically mean that they are bad in another. In Vision vs Pragmatism I argued that both qualities were necessary for success in projects and that they could be embodied in the same person.

Jacques Kallis - Test Matches: 10,843 runs at 54.76, 261 wickets at 31.55. One Day Internationals: 10,613 runs at 45.74, 251 wickets at 32.01.

To employ a metaphor, in my favourite team sport, cricket, while most players tend to specialise in either batting or bowling (cf. pitching for baseball fans), a significant subset are called all-rounders and do both. While some all-rounders are bits and pieces cricketers, others excel at each discipline and would merit selection on either.

There have been many great all-round cricketers over the centuries, but most people would agree that Jacques Kallis of South Africa is probably the finest currently playing. At a much less lofty level, I used to be a wicket keeper (cf. catcher) and opening batsman, so people who are able to do more than one thing to a reasonable level of competence are not that uncommon in sport.
 
 
Foundations of sand?

Analysis is invaluable - particularly when dealing with the Riemann Zeta function

However, in the more business-focussed case of big picture versus details, I would go further than merely asserting that some people can be good at both. In my opinion, it is rather hard to form an accurate big picture without at least some feeling for the details. If you do not have this firm foundation, then what is there to guarantee any legitimacy for the high-level conclusions that you draw. Findings without analysis may be correct sometimes, but it is more likely that they will not be.

Does that mean that in all circumstances minute forensic scrutiny must be paid to every single detail before deciding what to do? Is my claim the enemy of crisp decision-making and an acknowledgement that analysis paralysis is inevitable? I would say no.

Based on experience, new situations may often remind us of old ones and thereby bring ideas to mind on how to best proceed. This however is also based on the understanding of details, just historical ones, coupled with a facility to make connections between current and prior scenarios. My view is that when your gut instinct tells you to do something, it is worth pausing to kick the tyres. A sensible amount of checking of the facts is probably worth while most of the time.

A gifted Mathematician or Theoretical Physicist may develop a feeling for the general shape of a solution to a problem before they attack the details. However this is thought to be based on sub-concious analysis of lower-level factors. Whatever drives this phenomenon, the general shape of a solution is not the same as a solution and the latter will normally require a lot of painstaking work to realise.

Mulling over these analogous observations, maybe some people who claim to focus exclusively on the big picture are simply covering up the fact that they don’t have the inclination to check that their perspective is valid before offering it.
 
 
Look before it leaps

Would you mind holding still while I take a blood sample in order to analyse your DNA? You can never be too careful about evolutionary convergence.

Of course there are exceptions. As a massive feline rears towards your throat, pausing to assess whether it is a leopard or lion may not be overly valuable. But in the situations we normally face, there is generally time for at least a little reflection and to dig a little deeper. To ensure accuracy without compromising speed.

The dazzling images and vibrant colours on your 55″ HD TV are there courtesy of the 2 million plus underlying pixels and the technology that controls them. If ever there was a metaphor for the big picture being based on the details, this is surely it.

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Who should be accountable for data quality?

7 March 2010

The cardinality of a countable set - ex-mathematicians are allowed the occasional pun

linkedin CIO Magazine CIO Magazine forum

Asking the wrong question

Once more this post is inspired by a conversation on LinkedIn.com, this time the CIO Magazine forum and a thread entitled BI tool[s] can not deliver the expected results unless the company focuses on quality of data posted by Caroline Smith (normal caveat: you must be a member of LinkedIn.com and the group to view the actual thread).

The discussion included the predictable references to GIGO, but conversation then moved on to who has responsibility for data quality, IT or the business.

My view on how IT and The Business should be aligned

As regular readers of this column will know, I view this as an unhelpful distinction. My belief is that IT is a type of business department, with specific skills, but engaged in business work and, in this, essentially no different to say the sales department or the strategy department. Looking at the question through this prism, it becomes tautological. However, if we ignore my peccadillo about this issue, we could instead ask whether responsibility for data quality should reside in IT or not-IT (I will manfully resist the temptation to write ~IT or indeed IT’); with such a change, I accept that this is now a reasonable question.
 
 
Answering a modified version of the question

In information technology, telecommunications, and related fields, handshaking is an automated process of negotiation that dynamically sets parameters of a communications channel established between two entities before normal communication over the channel begins. It follows the physical establishment of the channel and precedes normal information transfer.

My basic answer is that both groups will bring specific skills to the party and a partnership approach is the one that is most likely to end in success. There are however some strong arguments for IT playing a pivotal role and my aim is to expand on these in the rest of this article.

The four pillars of improved data quality

Before I enumerate these, one thing that I think is very important is that data quality is seen as a broad issue that requires a broad approach to remedy it. I laid out what I see as the four pillars of improving data quality in an earlier post: Using BI to drive improvements in data quality. This previous article goes into much more detail about the elements of a successful data quality improvement programme and its title provides a big clue as to what I see as the fourth pillar. More on this later.
 
 
1. The change management angle

Again, as with virtually all IT projects, the aim of a data quality initiative is to drive different behaviours. This means that change management skills are just as important in these types projects as in the business intelligence work that they complement. This is a factor to consider when taking decisions about who takes the lead in looking to improve data quality; who amongst the available resources have established and honed change management skills? The best IT departments will have a number of individuals who fit this bill, if not-IT has them as well, then the organisation is spoilt for choice.
 
 
2. The pan-organisational angle

Elsewhere I have argued that BI adds greatest value when it is all-pervasive. The same observations apply to data quality. If we assume that an organisation has a number of divisions, each with their own systems (due to the nature of their business and maybe also history), but also maybe sharing some enterprise applications. While it would undeniably be beneficial for Division A to get their customer files in order, it would be of even greater value if all divisions did this at the same time and with a consistent purpose. This would allow the dealings of Customer X across all parts of the business to be calculated and analysed. It could also drive cross-selling opportunities in particular market segments.

While it is likely that a number of corporate staff of different sorts will have a very good understanding about the high-level operations of each of the divisions, it is at least probable that only IT staff (specifically those engaged in collating detailed data from each division for BI purposes) will have an in-depth understanding of how transactions and master data are stored in different ways across the enterprise. This knowledge is a by-product of running a best practice BI project and the collateral intellectual property built up can be of substantial business value.
 
 
3. The BI angle

It was this area that formed the backbone of the earlier data quality article that I referenced above. My thesis was that you could turn the good data quality => good BI relationship on its head and use the BI tool to drive data quality improvements. The key here was not to sanitise data problems, but instead to expose them, also leveraging standard BI functionality like drill through to allow people to identify what was causing an issue.

One of the most pernicious data quality issues is of the valid, but wrong entry. For example a transaction is allocated a category code of X, which is valid, but the business event demands the value Y. Sometimes it is possible to guard against this eventuality by business rules, e.g. Product A can only be sold by Business Unit W, but this will not be possible for all such data. A variant of this issue is data being entered in the wrong field. Having spent a while in the Insurance industry, it was not atypical for a policy number to be entered as a claim value for example. Sometimes there is no easy systematic way to detect this type of occurrence, but exposing issues in a well-designed BI system is one way of noticing odd figures and then – crucially – being able to determine what is causing them.
 
 
4. The IT character angle

I was searching round for a way to put this nicely and then realised that Jim Harris had done the job for me in naming his excellent Obsessive-Compulsive Data Quality blog (OCDQ Blog). I’m an IT person, I may have general management experience and a reasonable understanding of many parts of business, but I remain essentially an IT person. Before that, I was a Mathematician. People in both of those lines of work tend to have a certain reputation; to put it positively, the ability to focus extremely hard on something for long periods is a common characteristic.

  Aside: for the avoidance of doubt, as I pointed out in Pigeonholing – A tragedy, the fact that someone is good at the details does not necessarily preclude them from also excelling at seeing the big picture – in fact without a grasp on the details the danger of painting a Daliesque big picture is perhaps all too real!  

Improving data quality is one of the areas where this personality trait pays dividends. I’m sure that there are some marketing people out there who have relentless attention to detail and whose middle name is “thoroughness”, however I suspect there are rather less of them than among the ranks of my IT colleagues. While leadership from the pertinent parts of not-IT is very important, a lot of the hard yards are going to be done by IT people; therefore it makes sense if they have a degree of accountability in this area.
 
 
In closing

Much like most business projects, improving data quality is going to require a cross-functional approach to achieve its goals. While you often hear the platitudinous statement that “the business must be responsible for the quality of its own data”, this ostensible truism hides the fact that one of the best ways for not-IT to improve the quality of an organisation’s data is to get IT heavily involved in all aspects of this work.

IT for its part can leverage both its role as one of the supra-business unit departments and its knowledge of how business transactions are recorded and move from one system to another to become an effective champion of data quality.
 

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Running before you can walk

5 March 2010

Prelude…

I have been back blogging for a few days, so it is well past time for a rock climbing-related post. Though this site being what it is, I’ve twisted this thought round to apply to the world of IT.

Case of the Month

Symptoms: 42 year-old with recent long finger injury and resultant deformity.

A2 pulley damage - this is not my finger, but is most likely the injury that I have

Diagnosis Disruption of the A2 (white arrow), A3 (black arrow), and A4 (black arrowhead) pulleys. The primary function of the pulley system is to provide stability to the flexor tendons during flexion by fixing them to the underlying osseous structures. Injuries to the pulley system, commonly seen in rock climbers, lead to bowstringing of the flexor tendons with abnormal separation from the underlying phalanges.

Image and text care of The Institute of Orthopaedic Imaging, with my underlining.

Living in London, real rock is always a reasonably lengthy drive away, but in normal circumstances I would train indoors at least twice, and normally three times, a week and climb outdoors as often as possible. However, for a variety of reasons (including an ankle injury to myself, a chronic shoulder injury to my partner and both having an awful lot of other things on), I have not been climbing very much for several months. About a month ago, my partner and I decided to make a point of once more getting to the wall at least once a week. The problem is that, after a lay-off, your mind can remember climbing at a certain level but your body is way off the pace.

A combination of keenness, a desire to make up for lost time, pride and pig-headedness often sees a climber who is returning from injury quickly try to get back on to the level of routes/problems that they were achieving before. My limit, both indoors and out, used to be around V4 (fairly low down on the overall scale of climbing), with the occasional V5 indoors only. Having a few tentatively successful sessions under my belt, I found an indoor V5 that played to my strengths and was making some progress on it. It was a bit fingery and required use of a technique called crimping (see the image below):

An example of crimping

This is a very effective way of getting purchase on small holds, but puts a lot of pressure on your fingers. Levering my body up from sitting on the ground with both hands crimping like mad I felt a sort of crunching in the ring finger of my left hand. I stopped my attempt and decided that I would warm down on some easier stuff. Sadly even easier stuff can be quite demanding on the fingers and on my next but one climb I ended up pulling quite hard on the same left hand. There was a very audible pop, my left hand exploded off of the hold and I found myself on the floor holding my swollen finger in quite some pain.

After intensive icing at the wall and some therapeutic treatment in the four or so weeks since, I am still able to bend the finger (so hopefully do not have a full rupture of the tendon), but am a long way off of going back to climbing. I also have an unhelpful mental image of the tendon hanging by a thread, it is going to take quite some time for me to get over this; even if the finger itself heals.

Old tendon injury to ring finger of right hand

It doesn’t help that I fully ruptured the same tendon in my right ring finger when playing rugby as a teenager (see above). I can’t bend the top section of that finger and it has been a bit of an issue for me when climbing on occasion.

Tommy Caldwell - "high four"

Professional climber Tommy Caldwell (above) cut off one of his fingers in a DIY accident and still climbs to an astonishingly high level, so I can’t complain too much about this earlier injury. However I am now rather concerned about having matching tendon problems on both hands. I guess time will tell how serious this new injury is and what level of recovery I will experience. I hope to be able to avoid surgery, which is in any case no guarantee of a cure.

One of the most frustrating aspects of all this is that I feel as if I had a warning with the initial crunchiness, I chose to ignore this, which then led to the more serious injury. I guess it rather feels that I could have avoided getting myself in this situation with a little more thought.

The learning here is twofold: specifically how easy it is to injure yourself when returning from a lay-off; and generally that it is also much too tempting to try things that you are not yet ready for – to run before you can walk. The first lesson applies to climbing and sport in general, the second has wider applicability and some pertinence to the work of IT in particular.
 
 
…and Fugue

Running before you can walk seems to be something that particularly afflicts IT departments and IT people when they are in a bit of a hole already. If an IT department has been under-performing, or has become semi-detached from the business (the latter often leading to the former), there can be a desperate desire to get onto firmer ground quickly. I have seen this manifest itself in a couple of ways:

  1. An overwhelming urge to do something that will be appreciated by the business and make a difference – here the desire is for a quick redemption, unfortunately the concomitant rushing and even omission of key steps in the development process are just as likely to lead to more business disappointment and an increasingly tarnished reputation.
  2. The second symptom is virtually antipodal to the first; an unhealthy clinging to formal methodologies, or (much worse) an attempt to introduce new and improved ones – this can have almost a totemic quality, as if by simply adhering to ISO 9000 / Agile / ITIL / RAD (delete as appropriate) things will miraculously turn around.

Unfortunately both of these extremes are essentially displacement activities. I have led the turn-around of a number of IT teams. In my experience, what is generally required is a heavy dose of pragmatism and a focus on doing the basics well and without any elaboration whatsoever. It is nearly always best to try to fix the existing machine, or at most to tinker with it slightly in the first instance, rather than to make drastic modifications or try to build a new machine in entirety.

The main reason that teams under-perform - and the main route to addressing this

When IT is under-performing it is not normally a case of absent or ill-adhered to formal procedures. Rather the malaise is more likely to be a human one, relating to a lack of leadership and direction, a consequent lack of motivation and a group that begins to spiral in on itself. If the problem is essentially with people, then the solution often lies with them as well. It is not easy to motivate demotivated people, it is not easy to provide direction to those who are lost. However both of these things are easier to do than relying on the same lost and demotivated people to either make lighting fast redemptive deliveries, or to cheerfully adopt a new and fool-proof development methodology.

If a formal methodology is important – and it generally is – then my recommendation is to implement this once you have put a lot of effort into creating a happier and better functioning IT team. It is a bit like the old adage about not outsourcing a problem. Best practice instead is to resolve the issues and only then outsource a functioning process.

It is worth also saying that, as well as being more effective, working to make your team happier and more functional is a lot more rewarding and a lot more fun. If you achieve this it is amazing how much more easily the successful system deliveries start to flow.
 
 
Coda

In business, as in rock climbing, if you try to run before you can walk, try to jump to the desired end-state without putting in the necessary hard work, then you are only likely to get hurt. If you don’t believe me, I can tell you all about my finger injury again.
 

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