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Measurement should never be a process

Working on the future of the finance function with Prophix recently, we defined a transition that every organisation needs to make. I realised this weekend that this principle can be generalised to all areas of business — indeed operations in any type of organisation.

Put simply, stop wasting time on measurement.

How much time do you spend on pretty charts?

20 seconds to comply

This idea started in the world of company finance. Here, compliance, which we loosely defined as the preparation of all financial reporting required by regulatory authorities, shareholders and internal stakeholders, is too often a process. Even though the same, standard reports have to be completed on a known schedule, each new report consumes huge amounts of time to produce, since the numbers have to be gathered, processed and presented.

This is a perfect opportunity for automation: digital inputs, digital outputs, definable, repeatable processes. With automation, compliance becomes a state not a process.

You are always ready, always compliant.

Don’t do, measure

This weekend I was chatting to a friend in academia about the insane process of responding to the Research Excellence Framework or REF. Not only do some Universities complete their required response every six years, they try to monitor their progress each year. A valid approach, you might think — you want to know how you are progressing and six years is a long window between scores. But, the administrative overhead in responding to the REF, and the interim scoring exercises, is enormous. Not just in administrative posts to support it, but in time spent by the academics when they could be doing more research to improve their REF scores.

If this were the only factor, there might be a good argument to keep on with the measurement process: you don’t want to be flying blind for six years. But there’s something else. The research academics produce is published in peer-reviewed journals. The REF is essentially a peer-review process. Not surprisingly, there is a strong correlation between scores you can extrapolate from a department’s track record publishing in the journals, and the results of the REF.

Measurement is inherent in the core activity of the academic. A measurement process put on top of it is redundant. Worse, it takes people away from adding value that could improve the very thing you’re trying to measure.

Same problem, different day

This situation is not unique to universities. Or finance departments. Almost every organisation I interact with devotes time to measuring what has been done, both quantitatively and qualitatively. And often this measurement is a waste of time. Not because the metric itself is not useful, but because measurement should be embedded in the process.

Consider measurement in three parts: capture, analysis, presentation. Ask yourself these questions:

— Is the information we need to capture already captured elsewhere, or could we change our processes so that it is captured as a natural consequence of day-to-day activity?

A good example of this is moving from emails & documents to a proper workflow system that captures interactions. Not only will you save a lot of time hunting down documents, you will be able to extract data on performance.

— How much analysis do we really need to do in order to extract value from the data?

Too often ‘analysis’ hides a degree of arse-covering that disguises real results. Keep processing to a minimum.

Is the time spent on presentation well spent?

Pretty charts and graphs are all well and good if they contribute to understanding. But is all that time you spend formatting in Excel and PowerPoint really adding value? Or would the person receiving the report prefer that you spent the time upping the results? Be ruthless about what is useful and automate presentation wherever possible.

Ask yourself those three questions and see what you find. The key rule is that measurement should never, ever be a process. It should be intrinsic in your activity.

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Wipeout: the risk of flying solo

This week has been a wipeout. From the wedding I had to leave early on Saturday, to the uncomfortable journey home on Sunday, to the four days spent largely incapacitated since. I won’t go into too much detail but it involves a root canal, a ‘phoenix abscess’, a probable migraine, and a pretty negative reaction to some of the medication involved.

In five days, I’ve lost five pounds in weight and my face has gained a few years worth of wrinkles, screwed-up in a grimace when my painkillers were exhausted.

It has not been pleasant.

I share this in part as an explanation and apology (‘Explapology’? ‘Explology’?) for my lack of presence and the emails piling up in my inbox.


But I share it more as a cautionary tale for the future gig economy.

Short term security

Much is made of the loss of security that freelancers face: no sick pay, no paid holiday, no company pension. But there’s little discussion of what happens to everything else when someone flying solo crashes for a week. What happens to the work? The business of marketing? The administration?

Maintaining a successful freelance practice involves constant self-promotion. It can’t stop or the work stops — or at the least, stops growing. You become reliant on ‘word of mouth’, also known as good will and luck. This is fine until it’s not, because it is so unpredictable.

It also involves large amounts of administration: dealing with clients, contracts, invoices, accounts, tax, rent, broadband, software. All the things you can hand off to someone else when you’re employed.

It’s not just the work that doesn’t get done when you’re sick, it’s the business of being in business.

Clients first

The reality is that when you’re back on your feet, the priority is always servicing your clients. Often even beforehand.

Three times this week I’ve timed the painkillers right and steeled myself to get through a webinar, a presentation, and a batch of calls and emails. Only then did I find the time to squeeze out some confirmations of new work and a couple of invoices.

That’s why, right now, I don’t feel too bad about knocking out this blog post rather than chasing my next deadline (I have a few hours).

It will ever be thus: good freelancers will be committed to meeting their clients’ needs first. And it looks like there will be a lot more freelancers in the next few years, as companies automate what they can and turn to on-demand resource for the things they can’t. That seems to be the current pattern.

So who is going to catch the freelancers when they fall (ill)?

Not tomorrow but today

This isn’t so much about the long term: the pensions, benefits, holiday entitlements etc on which an increasingly freelance workforce might miss out. This is about keeping the wheels turning from day to day — automation, which presents benefits to the freelancer, as well as risks, can only do so much.

I see two approaches. One is the collaborative collective, sharing rather than competing, and supporting each other. These are the types of initiatives that some co-working spaces seem to be trying to develop, though if you’re going to trust your business to someone in your absence, you’d want to have some pretty robust agreements in place or a very strong sense of trust.

The other is outsourcing. We already have umbrella companies, who handle all the financial affairs of contractors in health, IT and elsewhere. Imagine a super-umbrella, like a combined PA, book-keeper, accountant and marketing firm. If such a thing existed, I’d be tempted to shift a chunk of my expenditure to them. With a few clients they might be able to exert some fairly significant buying power over additional services that might be attractive: office space, connectivity, travel etc.

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Smart Cities vs Living Cities

I talk a lot about the idea of a ‘living city’. But what’s the difference between that and a ‘smart city’?

Well, that’s hard to say, since the term ‘smart city’ means different things to different people. There is something close to a standard definition, from the BSI’s PAS180 Smart City Vocabulary document:

“‘Smart cities’ is a term denoting the effective integration of physical, digital and human systems in the built environment to deliver a sustainable, prosperous and inclusive future for its citizens.”

Who could argue with that? It’s a good definition. But the term carries a lot of baggage with it.

Push and pull

Smart cities have been the subject of aggressive marketing from the major tech companies for some years. Their development has come to be seen by some as a success of technology marketing over citizen need. Something of a corporate takeover.

People have issues with the command-and-control format of many smart city programs, with their ‘control centres’ featuring giant screens and dashboards for some mastermind at the middle to monitor the city.

There’s an issue with the focus on cities — something my Republic of Thingscolleague Andrew Beechener points out in the next episode of my podcast. While the global challenge is focused on the resource consumption and prosperity of cities, there’s a good argument in the UK for putting a greater focus on towns, villages, and rural areas, which perhaps need much more support to deliver services and drive economic regeneration.

This last point I can’t really address: I’m afraid I too have been largely focused on cities. I’m pleased that Republic of Things is working on programmes outside of cities to apply technology to bring public service benefits.

But the other issues, I hope I can.

Defining the living city

My vision of a living city is of one where the application of technology — sensing, AI, 3D printing and more — allows us to bring static, ‘dead’ infrastructure like buildings, streets and bridges to life.

By ‘life’ I mean that they exhibit three key attributes of ‘life’: they can sense their environment, they can process those inputs and make decisions, and they can act on them, not just over a short time frame but over a long one.

In other words, they can evolve.

How would this work?

Imagine a town hall: it has public spaces and offices, service desks and function rooms. There are lots of different and perhaps competing demands on all of the resources: power, light, space, heat. The chances of it being designed completely optimally from day one are minimal. Even if it were, needs change.

Now imagine the building can sense the patterns of consumption for all these resources. Imagine over time it can reshape itself: relocating walls and doors, heaters and lamps, entrances and exits, power sockets, batteries and solar cells, in order to optimise itself to the uses required.

Everything the building did would be inside a set of constraints, both functional and aesthetic, defined by the original architect. You could even include some more joyful constraints: a perfectly optimised building may be incredibly dull.

Of course the building may go off-track a little, so there would be a lifetime (of the building) role for the architect as ‘gardener’, tending his living creation and taming its wilder traits.

Smart city or future city?

This idea positions the living city somewhere in the future: we don’t have the technology to make this happen today. But it has other explicitly distinguishing features that stand it apart from the smart city.

Firstly, the living city is, by its nature, evolved from an existing city. Because they are evolutionary, the living characteristics don’t have to be built rigidly into a new structure. It’s easy to see how a relatively low cost package of sensors and a cloud-based AI could fairly rapidly start to optimise an existing building and, lacking any robotic construction capabilities, start to make recommendations to the owners/managers about adaptations that would add value: changes in lighting, connectivity, power provision, heating.

Secondly, the living city is a collaborative ecosystem rather than a command-and-control system. In a living city every building and vehicle is recognised as part of the community, with expectations on it in terms of behaviour and interaction. Being a good member of the community means managing your resource consumption and sharing it with others: venting waste stored heat to keep the queue at a bus-stop warm, illuminating offices at night to light a dark street, or releasing energy/restricting consumption to help balance the local grid.

A living city is less about central control and more about maintaining these standards of behaviour, interaction and collaboration.

Building the living city

If these ideas appeal, then there is an obvious question: how do we build a living city?

The answer is about focusing on the interfaces. So many smart city projects to date have been about defining a whole stack: every technology component from the sensor to the display systems. This comes in part from the companies who have been driving the projects. For me, what is important is to define how every layer in the stack interacts: what data is passed, and how. Leave the specifications beyond this to individual applications.

If these are the ‘vertical’ interfaces, through the technology stack, then there is a second dimension to consider. The ‘horizontal’ interfaces between the members of this new ecosystem. What will be the standards of behaviour? How will we ensure that every citizen can enjoy the benefits of the living city?

These are the bigger challenges.


I’ll be speaking about ‘Life and Work in the Living City’ at next week’s Digital Disruption and the Smart City conference next week. Details at

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Failure undermines our faith, slows progress

Predicting what will happen in the future is easier than predicting when it will happen. Our economic system — unless and until it changes — makes some transitions so attractive as to be inevitable. But the human factors slowing or speeding that transition are much harder to predict.

Faith in technology, and our inevitable fallibility in its application are two such factors. Two stories in today’s papers illustrate the potential of these factors.

Smart, but inaccurate

The first story in today’s Sun and Telegraph, browsed while preparing the newspaper review on BBC Radio Manchester this morning, highlight the poor performance of many smart meters. Smart meters are supposed to replace all of our utility meters by 2020, but the programme has seemed to stumble from inception onward. Security issues, budget over-runs, delays, and now this: some meters over-read consumption by a factor of six. They struggle to cope with low-energy bulbs, LED lights and dimmers. Some of the meters included in the study, though not necessarily the worst offenders, have been installed in the UK.

This will undoubtedly undermine people’s faith in what should be a highly positive programme, with the potential to cut people’s bills, increase their smart consumption of energy, and tackle our collective carbon footprint — as well as releasing pressure on an over-stressed energy grid. The result? 2020 not looks even more optimistic as a deadline.

Call centre criminals

In The Times this morning is the story of a scam being perpetrated against TalkTalk customers. This is a more targeted version of the Windows Support scam, where you receive a call claiming to be from tech support having discovered a problem with your machine. They walk you through a few steps designed to convince you that your machine is afflicted, then convince you to open up your machine to remote control. You are then locked out until you make a payment to restore access — or worse, your banking, payment and identity information can be stolen from your machine.

There’s only anecdotal evidence of a link to the 2015 TalkTalk hack that captured the data of 157,000 users, but it seems plausible that this is the source of the targeting data. The result? More stories scaring people off the internet and making online banking and shopping less appealing for the remaining percentage yet to take advantage. And it is an advantage: prices are often lower online.

Tech isn’t the threat

Technology carries both opportunity and threat. Sometimes the threat is intentional. Sometimes it is accidental. If we are to realise the opportunities technology presents then technologists need to demonstrate great responsibility in its application — something that is not always in evidence. That’s problematic at best when handling people’s personal data or energy bills. It could be catastrophic as we start to deploy more wide-reaching and powerful technologies like AI.

Tom Cheesewright