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.
The 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.
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?
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
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.
Who should be accountable for data quality?
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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.
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
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.
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.
Running before you can walk
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.
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):
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.
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.
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:
- 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.
- 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.
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.
Aphorism of the week
“Just because Jeffrey Archer exists, it doesn’t follow that Joseph Conrad can’t have existed”
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| Jeffrey Archer | Joseph Conrad |
Introduction
The context of the above bon mot was – as is often the case – a discussion on LinkedIn.com. I have been rather absent from the LinkedIn.com discussion groups for the same reasons that I have not been blogging and tweeting. In this case, my attention was drawn to the debate by a colleague.
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CIOs.com: Chief Information Officer Network | ||
The particular thread was posted by Andy McKnight and is entitled What’s missing from Business Intelligence? and at the time of writing has attracted nearly 60 responses (you have to be a member of the group to view the discussion). It referred to an article published by EMC2 which has the strap-line How CIOs can Reap the Benefits of BI Technology (note: this is a PDF document). Here is a pertinent quote:
The bad news is that only twenty-seven percent of respondents [to a survey of CIOs carried out by IDG Research] who use a BI solution report being extremely successful or very successful with it. Forty-five percent report being only somewhat successful, while seventeen percent say that they are not very, or not at all successful.
I’m not sure what happened to the other 11% of respondents, maybe they just hung up the ‘phone.
Blaming the users
!["Users are the root of all evil" - anonymous [failed] BI Project Manager](https://peterjamesthomas.com/wp-content/uploads/2010/03/down-with-users.jpg?w=700 "\"Users are the root of all evil\" - anonymous [failed] BI Project Manager")
Having stated that “BI has, too often, not lived up to expectations”, the paper goes on to list some reasons why. First on the list is the following:
- lack of adoption by users
You don’t have to be Einstein to realise that this is the result of a BI project failing, not the cause of it. The equivalent in athletics terms would be to say that you came last in the race because everyone else was faster than you. While obviously true this observation doesn’t help a lot with how to do better next time.
Of course hidden in the comment is the plaintive whine heard emanating from many an unsuccessful project (or indeed product launch), “the problem is the users”. This is arrant nonsense, returning to the start of article if you write a book that is panned by the critics and not bought by the public, then there is at least some chance that the fault lies with you and not them. It is the job of the IT professional to know their users, understand their needs and provide systems that cause delight, not disillusion.
A more interesting observation later on is:
Many BI initiatives falter because the analytics capabilities that are at the core of the system aren’t even used. Many users simply pull data from the warehouse and dump it in a spreadsheet. […] A true BI implementation includes both reporting and analytics. CIOs indicate a much higher success rate with BI when users embrace both.
I think that there is some truth in this. Some of the BI failures I have seen have gone to the bother of building a warehouse only to front it with flat reports that are only marginally better than what they replaced.
In my career I have taken the opposite approach. While many people warn against analysis paralysis, I have deployed OLAP tools to all users, with fixed format reports de-emphasised, or used mostly for external purposes. This does mean that more effort needs to be put into training, but this is necessary anyway if you want your BI system to be an agent of change (and why else would you be building one if this is not the case?). I cover my general approach to driving user adoption in a series of three articles as follows:
This approach was very successful and we achieved user adoption of 92% – i.e. of those people who attended training, 92% remained active users (defined as using the BI system on average for at least two extended periods each week). We actually felt that the OLAP tools we were implementing were pretty intuitive and easy-to-use and so focussed mostly on how to use them in specific business scenarios. Overall we felt that training was 25% technical and 75% business-related.
Aiming for simplicity
Related to the above point, the EMC2 article also mentions the following reason for failure:
- limited functionality/hard to use
This seems a little oxymoronic as normally it is depth of functionality that confuses people. I think I would disagree with both parts of this point. Out of the box, most BI tools have rich functionality and a reasonably intuitive to use. In one response to the LinkedIn.com thread I said the following:
I have been successful in getting users […] weaned […] off ad hoc reports, it wasn’t an easy process and required persistence and selling, but this paid off. […] It is illuminating seeing business managers (some of whom still dictate memos for their secretaries to type) “slicing and dicing”, drilling down/through and generally interacting away merrily and stating that if all IT was this easy to use and informative, they might have taken to it earlier.
My view here is that you can make the tool as complicated or a simple as you choose. Going back to my first warehouse project, in our somewhat naive early attempts at prototype cubes, we had all available dimensions and all available measures included. I think our idea is that the users could help us sift out the ones that were most important. Instead this approach caused the negative reactions that the article refers to.
We subsequently adopted a rule of having as few dimensions and measures as possible in a cube, without compromising the business need that the cube was trying to address. The second part of this rule was that every cube had to be focussed on answering business questions in at least one area and at most two.
Rather than having a small number of monolithic cubes, we went with the option of a slightly larger number of significantly clearer and simpler ones. I think that this was a factor in our success in driving business adoption.
Should the fact that some BI projects fail dissuade you from BI?
I won’t attempt to dissect the rest of the article, the areas that I comment on above are representative. There are some good points and some less good ones – just like any article, including of course my own. Take a look yourself and see whether the findings and recommendations chime with your own experience of success and failure. What I did want to do was to return to the context of the aphorism that starts this post.
The thesis of the original LinkedIn.com post was that because a significant number of organisations had failed to get enormous benefit from BI, BI itself was therefore somehow flawed. I think this is wrong-headed reasoning. If 1,000 people write a book, how many are likely to become acknowledged as great authors? How many are likely to have the lesser accolade of commercial success? The answer in both cases is “not many”. This is because writing well is a very difficult thing to do (I prove this myself with every blog post!). Not everyone who tries it will be successful. BI is also difficult to do well and a major cause of problems is underestimating this difficulty.
Maybe this is too recherché and example, and maybe if the chances of success with BI are as slim as winning the Purlitzer Prize then it is not worth the effort. So I’ll instead I’ll resort to my favourite area of the sporting analogy. Let’s take the same 1,000 people and say that they all take up a new sport – it is mostly immaterial what the sport is, let’s say tennis. How many of them will go on to become proficient in it? By this I don’t mean that they are the next Roger Federer, just that they become competent enough to serve adequately, master the dark arts of the backhand and sustain a few rallies. My feeling is that the stats would look something like those in the EMC2 report.
Is the prize worth it?
Given this, does it mean that some companies are just not cut out for BI and should ignore the area? Well the answer is “it depends”. Going back to tennis, if some one wants to be good, and has the determination to succeed, that is a necessary (though sadly not sufficient) condition. What may drive such a person on is the objective of achieving a goal, or maybe the pleasure of being able to perform at a certain level.
Focussing on business outcomes, I believe that BI can deliver substantial benefits. In fact I have argued elsewhere that BI can have the greatest payback of any IT project. Of course this presupposes that the BI project is done well. If the prize is potentially that great then maybe – like the aspiring tennis player who wants to become better – trying again makes sense. In recent recruitment I have heard frequent mention of organisations that were building their second warehouse as they didn’t get the first one quite right.
However the comparison with tennis breaks down in that business is a team game. If an organisation as a whole has struggled with BI, then this is not a question of simply accepting your genetic limitations. Companies can “evolve” capabilities by hiring people who have been successful in a field. They can also get benefit from targeted consultancy from practitioners who have a track record of success; this can help them to build an internal capability. This is an approach that I took advantage of myself in the initial six months of my first BI project [note: although I often seem to get mistaken for a BI consultant, I am not touting for business here!].
This means that if a company’s BI architecture is currently the equivalent of a Jeffrey Archer novel, it is still possible to transform it into Heart of Darkness. It will not be easy and will take time and effort, but there are people out there who have been successful and can act as guides.
In closing I should also mention that, if you take appropriate precautions, it is far from inevitable that the end of a BI journey will be finding your own version of Kurtz!
Most popular articles over the last eight months
I last published a list of the most popular articles on this site at the beginning of July 2009. As I mentioned a couple of days ago, I had a hiatus in blogging which started at the beginning of August 2009. This means that readership figures since then have not been skewed by when articles were posted (they were all posted before the pertinent period).
The following is a list of the top twenty articles in descending order of hits per day over the last eight months.
Playing the BI Blame Game – Conspectus.com
An abridged and reworked version of my earlier blog post – A bad workman blames his [Business Intelligence] tools – was published on the National Computer Centre’s Evaluation Centre site last October and also appears in print form in February 2010’s Conspectus magazine (pages 18 – 19) and is also available to subscribers on the Conspectus site.
Conspectus is a report, published by The National Computing Centre (NCC) Ltd, which keeps UK decision makers abreast of the key issues in the IT marketplace. It is a regular publication available online as a PDF. Each subject is published annually to ensure its continuing relevance and accuracy. Conspectus has a UK registered readership of 22,500.
Persistence
Persistence can mean a lot of different things, sadly to me it is often the world of databases that comes to mind first. Having linked to my previous article entitled Perseverance earlier today, I won’t bother to do that again, but this is clearly another meaning.
In this case I am going to employ the sense of “continuance of an effect after the cause is removed” and apply it to the stats of this blog. Aside from today’s spurt and a wish of Season’s Greetings and Goodwill to all Readers back in December, I last blogged in anger back on 30th July 2009. Somewhat ironically, the title of this piece was Inspiration as mine subsequently dried up!
The number of monthly readers dropped significantly in August 2009, however, despite this removal of cause, it plateaued at about 3,000; a level it has never dropped below since. Having taken a look at the more detailed statistics (which regulars will be delighted to hear may lead to a revsion of An update of the most read articles on this site to cover the last six months), the readership seems to be pretty evenly spread and not dominated by any one article.
Whether what I am observing is the general persistence inherent in the Internet (where links from one page to another will exist as long as both pages do), or to do with slow-moving algorithms in search engines I do not know. I suppose it could feasibly be related to the enduring appeal of my writing, though this seems a long way removed from the bleeding edge of Occam’s razor.
Some deeper digging may yield further indications (e.g. did I receive more hits from searches, or via other sites as the fallow period of the last six months progressed), but I can’t imagine that these will be statistically significant.
From an experimental perspective, I guess I should have refrained from posting for a bit longer and then calculated the half-life of my writing.
Pressure
The main reason for my lack of blogging since August last year has been starting a new job. I have been very busy and the new role has many challenges that have occupied a lot of my thinking time, however I am not sure that this has been the only factor at work. Having not written – for public consumption at least – for some time, I suppose I felt that it would be good to mark my blogging “comeback” with a signature article on a topic of interest and importance. Perhaps this led to a slight, unconscious build-up of pressure somewhere in my mind. Several people have been very kind about my work on this site and maybe I felt that I should live up to their encouraging comments.
Several months down the line, I have decided that the best way to kill this particular demon is to simply put fingertip to keyboard and write something. Sadly this is not going to be the signature piece that I had hoped for, but my current case of writer’s block is such that if I don’t write something then my concern about not being able to write another engaging and insightful piece will become a self-fulfilling prophecy.
As ever, maybe there is a learning here for the business world and IT in particular. IT people are, by definition, analytical, logical and have a great attention to detail. This can lead to a desire to create the perfect piece of code via endless polishing of the same 5-line “rock”, or to understand every nuance of a business requirement before beginning to scope out a solution. Without wanting to leap on the agile bandwagon, sometimes a good way to get to a solution is to start to write one. Create something, test whether it works and meets user expectations and adapt it if not. Also consider discarding initial attempts that are wide of the mark, so long as you learn something from them.
Back when I wrote Perseverance, I quoted Beckett’s adage about failing better. This is not a bad way of looking at IT work. Jumping in with no real understanding of an area is a major mistake, to be avoided at all costs, but holding back until you form a perfect understanding (or have a perfect article to write in the context of this piece) is almost as serious a problem. As with most things in life, what is required is some balance, a willingness to tolerate some false steps initially and a desire to make sure that these lead to improvement.
With this thought in mind, and in the hope that my creative flow can hereby be unblocked, I’ll close this short piece and trust that the next one follows on fairly shortly from it.
Peter James Thomas 