Data-centric driving

I spend more time in the car than I used to, and whilst petrol prices are down from their scary heights of last year, they are creeping up again. £1 per litre of unleaded is undoubtedly better than £1.20 of last July, but it is enough to think twice. So I am trying to reduce my petrol consumption by driving more economically. In particular:

• Keeping tyres inflated correctly
• Reducing braking
• Keeping my speed down

I guess that rules out my usual driving style which would easily get me employed by one of the emergency services.

I am assured that driving at 60 mph is more economical than 70 mph, and 40 mph is more economical than 50 mph.

The crunch, though, is whether the risk of annoying every 4-wheel drive and bat-out-of-hell driver in the vicinity will get more miles out of my tank. Can I change my driving habits consistently enough to make a difference to the tiger in my tank? I am motivated more by curiosity and a growing concern for environmental issues than cost savings, but saving money is a welcome by-product.

I have to confess I started by forgetting to fill the car with petrol and therefore eking out the remainder of the tank to the local garage. But I found the driving experience unusually quietening. Speed restriction signs were welcome, and as I accelerated away more slowly than usual I reflected on how much money all the drivers behind me were saving. I’m not sure they saw it that way, but I believe everyone made it home without blowing too many fuses.

Next challenge: figuring out how those air pump things at garages work. Tomorrow, maybe …

Data-centric decision-making: an update

I have been attempting to live data-centrically – a challenge in all sorts of ways:

1. Changing my habits is difficult. They are stubbornly ingrained; perhaps the definition of a habit. I am on auto-pilot for much of the day – simply so that I can get through my work. The point of the study was to switch off auto-pilot, but it’s wasn’t so easy.
2. Data doesn’t exist for lots of things – in some trivial and some less trivial areas.
3. Too much data exists in some areas – much of it not joined-up or misleading. But then it was ever thus: lies, damned lies, and statistics. Getting data to be informative involves work – lots of it.
4. I was on holiday for a week. The Highlands of Scotland so completely calmed my soul that I forgot there was any other sort of data apart from how many lambs can run down a grassy slope. Doing that funny kicking thing that lambs do.

Habits which already included data, business financials, for example, were easy. Our internal systems that provide information on projects, financials and data I need on a day to day basis were taken for granted and used by the auto-pilot.

The evidence for and against a tidy desk is no more settled, but my workspace is now clear. Whether a tidy desk improves my work is a controversial idea, but the sense of calm and control is worth the effort. Is this living data-centrically? No – there is just no data on this, just opinions, preferences and tips from those brave enough to offer anything this subject.

Useful data is difficult – no doubt - it needs work and is therefore slow to gather. Successful data is then quickly assimilated and taken for granted. The systems I work on are invariably involved in presenting data in a useful and orderly way to enable better decision making. Maybe its when they are taken for granted that we know we have done a good job.

When I tried to gather data in an unstructured way I found much data to be illusory. It somehow fooled me into feeling that it contributes when in reality it didn’t change my thinking or my actions. There is plenty of data loaded with agendas and bias – and plenty of opinions; neither was much use for this exercise. Cherry-picking here and there is neither scientific nor useful, and is perhaps why so much is ignored. Putting a toe into the turbulent waters of the energy sector seemed to turn out so much contradictory data that it made my head spin.

When weekends and holidays (bank or otherwise) are taken out of the equation, I am only 10 days into the study. I’m unconvinced that any of the above is particularly illuminating, but I promised an update. Take it as work in progress.

Unexpected pleasures

One of the things I never anticipated when I started this blog was the reaction I would get from other people. I am often sent fascinating articles and papers in relation to performance management or business intelligence. It is a real unexpected pleasure.

Last week I was sent an email which I particularly enjoyed after I posted a few words about the 5S’s. It was sent by someone who works in a world-renowned research centre: just the sort of place you would expect to be practising clinical tidiness. Their in joke is that the 5S’s stand for:

• Stash
• Store
• Squirrel
• Save
• Scatter

Of course, I could not possibly comment. Since my last posting about finding evidence that a tidy desk makes for a more effective executive, the reassuring clutter has returned. I will, however, redouble my efforts work on a permanently clear desk and curb my squirreling habits. But it is comforting to know that others face the same battle and find work more interesting than tidying up.

Please keep the feedback coming, it’s always appreciated. And I’ll go back to being serious tomorrow. Probably.

Data, data, everywhere

Water, water, everywhere – but not a drop to drink.

Like the ancient mariner, I was at sea today (well, close to the sea in Aberdeen). The renewable energy sector is not short of data – wind speeds, wind directions, MW of electricity or percentage capacity. Trying to make sense of all this data, and of all the competing technologies that make up the energy sector, however, is something else entirely; a visit to All Energy ’09 today left me with my head spinning.

Wind farms, onshore and offshore, hydro schemes, sub-sea projects – all show enormous potential for helping us reach our 15% EU mandated target for renewable energy, but not all are getting funded for one reason or another. Often the reason is competing stakeholder interests. Quite rightly the environmental lobby is vocal, well organised and effective in the go/no go decision for renewable schemes.

Of course, there is no “right” answer – our energy needs are substantial and ongoing and no one solution appears to have all the answers. So whilst government continue to hold consultation after consultation, the UK is showing little sign of having a coherent renewable energy plan. Meanwhile newly created government departments pop up to add to the rhetoric. Added to which the official line on the climate change debate appears to be an open and shut case, which I’m far from convinced about.

This is a fast growing and dynamic sector with a great deal of activity. The map of the UK appears to have developed a nasty rash when the current wind farms are plotted onto it. Is this the best way of navigating our way out of the fossil fuel and carbon emissions crisis? We will see. Or perhaps the data will.

Dangerous targets

A few days ago I made reference to Locke and Latham’s attack on using anecdotal evidence to “prove” a point. The rigours of research well done and properly carried out should provide information that is more dependable than hearsay.

However, during the course of our working lives we inevitably hear details of managers who have successfully or unsuccessfully used devices such as targets in performance management. One such story, from the 1950’s, demonstrates just how dangerous targets can be when left unchecked.

The North of Scotland Hydro Electricity Board was formed in 1943 after 50 years of successfully generating hydro electricity in the highlands of Scotland. They set out grand and ambitious plans to bring not only electricity to every home in Scotland, but also much needed employment. Their schemes did not go unopposed, but eventually won out and what turned out to be several decades of building hydro electricity plants across Scotland started.

The work involved tunnelling and blasting through mountainous areas to form the infrastructure for the hydro electric plants. It was dangerous work, often done by immigrants who were paid well, and incentivised to work quickly. Overtime was freely available, and eagerly taken up, despite the risks of having tired men working in dangerous conditions.

The overheads on the construction projects were significant and the faster the work could be completed, the better. In the absence of health and safety laws, and high targets for both managers and workers, risk taking was an everyday occurrence.

Many lost their lives and limbs in an atmosphere that valued speed over human life. The final tally for those that perished during the construction of such schemes has been lost – despite the relative recentness of the work. It is a stark reminder of what unchecked corporate targets can achieve.

Yes, the work was completed, but not without significant loss of life and not without construction failures. Since then, of course, different laws have been passed that do not allow such dangerous working conditions.

Walking in the peaceful highlands of Scotland now much of the hydro works are hidden – only the dams and power stations are visible. So it is easy to forget the toil and hardship suffered by those who built them. But it is a reminder that whilst targets might be a powerful weapon, they need to be used responsibly.

Arguments over goal setting

Goal setting is at the heart of performance management. Without a goal or a way of measuring what constitutes success, performance cannot be managed or improved.

This blog is no stranger to comments about what can or cannot be measured; and it is true – some things cannot be. An unexpected sunny day lifts everyone’s spirits and raises performance without anyone even thinking about it. The sincere comment given to a co-worker about a job well done isn’t designed to be measured, but is just part of a good relationship and recognition of good work.

It has been shown, however, that goals and measurement are powerful weapons in improving performance. Yet stories abound about instances where targets and goals have led to problems; the health service is a favourite with reports about inflexible targets lead to poor patient care. A few of these have been sent to me as if to say “see – that’s what happens when you try to set targets!”

A fascinating paper landed on my desk not long ago that in my view made welcome reading. The authors – Locke and Latham - raise some interesting points about the differences between journalism and the rigors of good social science. One is free to be as emotional and anecdotal as it wishes, whilst the other has standards and aims to use dispassionate and accurate language to argue a point. They quote Campbell and Stanley (1963) who pointed out that:

“Any appearance of absolute knowledge or intrinsic [i.e., general] knowledge about singular isolated objects is found to be illusory upon analysis.”

Only this evening I was up against what seemed to be the injustice of those who have targets to meet. A road traffic incident that might once have been arguable was briskly and efficiently chalked up with another ticket and another day in court. It will no doubt end in more bureaucracy than it is worth but targets have been met and at least two people in uniform went away happy.

Of course there is an alternative: that we park where we want to and pedestrians take their chances. It’s annoying, but maybe goals have their value.

Overcoming the law of inertia

I had some difficult stuff to do yesterday – emails and telephone calls that I was by no means sure would have the effect I wanted. So I pondered, puzzled and rearranged the words in my head and on the page. A conversation I had had the previous day came to mind and almost by accident I found Newton’s First Law of Motion.

Newton's 1st Law states that a body in motion tends to stay in motion and a body at rest tends to stay at rest.

I’m not sure Newton had in mind a body sitting at a computer, but nonetheless the lesson sunk home.

This body could put off making the phone call or sending the email and remain at rest. The certain outcome would be that whilst I would not get a rejection, neither would I get the outcome I wanted.

Alternatively, the body could send the email and make the phone call, and set things in motion. If Newton was right, they would stay in motion. I had the evidence I needed, and emails were sent, phone calls were made and meetings duly set up.

Of course, the mere mention of this being the first law implies there are others, and Newton’s 3rd Law is also useful:

Newton's 3rd Law states that every action has an equal but opposite reaction.

Well at least one of my emails did have an opposite reaction – which was not a great surprise to me – even though it was a disappointment. A reaction is better than a body at rest and at least the motion can continue.

So whilst this isn’t the type of evidence I had in mind when I set my 30 day data-centric challenge, it has at least provided additional insight to my decision making process.

To Clear or Not to Clear my Desk?

That is the question. Indeed, it is a question without a clear answer. In my month of living data-centrically (a boring version of a Year Living Dangerously) I am attempting to make my decisions based on data, rather than intuition. Academics have us believe we make better decisions that way, so I’m putting it to the test.

So my first decision after I posted my blog on Tuesday was ”what to do next?” My desk is not the pinnacle of minimalism, so it’s normally a good choice to have a clear up before starting anything new. This time, I thought I would gather some evidence to back up my decision. As it turns out, there isn’t much.

There are estimates that “people spend 30 minutes a day searching for papers” or that great CEOs work on clear desks, both of which I admit to having anecdotal evidence for (although the 30 minutes a day sounds rather high).

Then there is the Clear Desk brigade who reckons that a messy desk is a security hazard. I guess I would agree with that as in my work I am fastidious about shredding client printouts.

My favourite, and I think the most convincing, is the 5 S’s from The Toyota Way. The principle is to Clean It Up, and Make It Visual. The 5 S’s translate neatly into English:

1. Sort – Sort through items and keep only what is needed while disposing of what is not.
2. Straighten (orderliness) – “A place for everything and everything in its place”.
3. Shine (cleanliness) – the cleaning process acts as a form of inspection that exposes abnormal and pre-failure conditions that affect quality.
4. Standardize (create rules) – Develop systems and procedures to maintain and monitor the first three S’s.
5. Sustain (self-discipline) – Maintaining a stabilized workplace is an ongoing process of continuous improvement.

Why am I convinced? Because Toyota came from nowhere to make a global success of their car manufacturing. Just recently they have been knocked off their pedestal by Volkswagen, but these are more than interesting times.

I wonder whether Volkswagen executives have clear desks too – I bet they do …

Data-centric decision making

There is much evidence that data-centric decisions are better than decisions based on intuition. From time to time in the comments section of this blog a little tussle breaks out over whether the head or heart should rule in business. Needless to say I come down on the side of head. However, I’ve not been presenting much evidence.

So I have decided to do my own study. For 30 work-days I will live a data-centric life. I will make as many of my decisions as possible will be based on as much data as I can reasonably gather.

As far as I am able, I will make each and every decision based on data. I will record what those decisions were, what data I used in my decision making process, and how good I felt the decisions turned out.

I fully expect to be slowed down by this way of working – I will by living the Toyota Way – at tortoise rather than hare speed. I will be fascinated to see whether I can actually manage a whole month, and whether I judge my decisions to be better or worse as a result.

Decisions I will include are:

1. What to buy (impulse purchases are out, considered data-centric decisions are in – this one is going to be tough!)
2. What to work on, and for how long (based on plans and past data)
3. Work-based decisions (allocating budget, changing suppliers, etc)
4. Project-based decisions (looking at past projects and outside studies)
5. Whether to accept a call or e-mail interruption in the middle of a task (I’m sure it’s more efficient to work straight through on a task, but don’t have any evidence on this)
6. When to take a break and for how long

I will keep a log and the data or evidence I use to support my decisions. I will also review regularly and post something once a week to let you know how it’s going.

No doubt I will have less data than I would like about some decisions, but maybe I will have too much. I won’t know until I try.

So for all those who have read The Year of Living Biblically – this is The Month of Living Data-Centrically. Not so catchy, but without the scratchy clothing and hopefully better for business…

If you cannot measure it, you cannot improve it

Lord Kelvin is best known for his work in thermodynamics, the temperature scale named after him, and providing brilliant quotations for the Getting to Excellent blog. His studies of heat determined that there is an absolute minimum temperature: zero on the Kelvin scale, equivalent to –273oC.

Although he might have preferred to have been remembered as a physicist rather than a performance management expert, his observation that "If you cannot measure it, you cannot improve it" is worthy of any manager wanting to improve performance – however performance might be defined.

In 1867, together with Peter Tait, he wrote the first ever textbook on Physics – Treatise on Natural Philosophy. To the delight of school boys everywhere, it is still in print today.

Amongst my favourite Lord Kelvin quotes are:

“Large increases in cost with questionable increases in performance can be tolerated only in race horses and women.”

“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.”

And my personal favourite:

"Radio has no future."

Hey – anyone that invents thermodynamics can be forgiven the occasional slip.

By all accounts he was a man of enormous energy, giant intellect, and a tremendous capacity to apply scientific knowledge to practical problems such as laying a telegraph cable across the ocean bed. He was one of the pioneers of electric light and lived in the first house in the world to be completely lit by electricity. He earned himself considerable wealth through his ability to solve practical problems for companies.

He is buried in Westminster Abbey next to Isaac Newton and acknowledged to be the greatest physicist of the 19th Century.