From Bill Wallsgrove
AI continues to not quite to get what a platypus is – just as many people still don’t understand what Asset Managers do.
I could tell two miserable current stories of Human Resources not getting it. A major power utility with ISO 55000 certification where HR led a structure reorganisation, and failed to include any Asset Management (and the saddest part was how much effort the AM team had put into trying to bring HR along with them). A transit agency where HR insist they know better how to recruit good Asset Managers – again, after years of effort from the AM team on what to look for.
But lamenting HR failures is like shooting fish in barrel: too easy.
And we are all still working it out.
For example, looking at AM teams where they have really done interesting things, I see how much difference ‘professional’ information skills have made. The most impressive Asset Managers I know include a librarian, an ex-military intelligence veteran, and a teacher of data science. I wonder if good Asset Management is even possible without information nous.
And the perennial questions of whether you can learn to ‘embrace uncertainty’, or think strategically. Are good Asset Managers born, not made? I don’t want to believe so.
I certainly don’t have it all and have depended through my career on other people with complementary skills to mine.
As the Institute of Asset Management (IAM) starts its review of its Competency Framework, to update and expand the original work led by Chris Lloyd, I get the feeling more than ever that it isn’t just a matter of hiring people with certain skills, but of encouraging those who think about the world in particular ways.
I’m on the Competences Steering Group for the IAM. This is a plea for input: what is your experience on the most important skills, experience, aptitudes, attitudes for good Infrastructure Asset Management?
What have we learnt about good people in the nearly 40 years of Asset Management?
I work with a variety of organisations in several countries who are attempting to implement good Asset Management. Some are just starting out. A few are quite sophisticated. And one or two are even tackling the question of infrastructure decision making in our communities.
I was struck again this month by how hard this all sometimes seems.
Organizations who are just starting out have interesting challenges, of course, including no-one much understanding what AM is and, usually, a lack of resources. One half time resource without much authority, for example, can’t do much to radically transform their business.
But surely it doesn’t have to be that hard, conceptually, to sort out a basic asset inventory, classic Wave 1? Plenty of organisations have already sorted that – it is, as my old colleague John Lavan put it, a puzzle, for which there is an answer already known, not a problem we haven’t yet solved.
And yet many people just don’t seem to have good sense about asset information. And want to reduce the problem to basic IT, which they also don’t do very well. (I am feeling a bit grumpy about this: can’t someone please donate good-enough asset hierarchies and principles into the public domain, or even write the book so no-one ever has to reinvent those particular wheels? TJ, Dave Ulrich, I am looking at you guys here.)
Wave 2, strategic AM and better all-round asset decision-making also depends on something rather more than technology – and that, I am sure, is why organisations struggle. It involves people! Culture! And politics, small p, and sometimes Big P too!
Where Asset Management is effective, infrastructure Asset Managers can then get caught up in Wave 3. And however smart and well-resourced they are, it’s big.
A great current example is electric buses, something the US Federal government wants to throw money at as part of ‘decarbonization’ of transport. But the questions of how, and why, to invest with all the interconnecting issues of the infrastructure for the buses themselves, performance and customer satisfaction, and whether this will even give the right carbon-reduced answer…
Asset Managers get it. But they are a small drop in a large ocean of greed and love of shiny new things.
I asked a buddy who’s simply caught in too many stupid business decisions in a utility whether he might just bring in some additional resources to tackle more of them… But he said, quite rightly, where from? Who gets it, and all the diplomacy, strategic thinking, experience, intelligent use of what data there is that is that’s required, all at once?
ISO 55000 doesn’t help it all that much.
In a new series of blogs, I want to look with your input at some of the challenges we see in every Wave. Of course we love challenges. But I also see rather too many Asset Managers at every stage drowning in the sheer size of the job.
Series to include: asset information, risk, networking, attitude change, and more.
© 2023 Bill Wallsgrove
Some of my best friends are AI – in literature, at least. Ships Behaving Badly in Iain M Banks’ Culture novels for example, which led a human friend to say they couldn’t make a worse job of running the world than humans.
I am sad to say I expect less in reality, and any technology under the control of the rich few. But should we fear conspiracy or cock-up more, I wonder?
I seem to have become a luddite about ‘smart technology’ in managing infrastructure, delivering less and threatening more than enthusiasts are claiming. Systems too complex to manage, or to understand the potential implications of; and products that don’t offer much except big price tags.
But I had to smile at this image, the first result of my brother using an AI art app to create images for me of duck-billed platypuses.
Most simple definitions of Smart Cities include goals along these lines:
- Improving transportation
- Enhancing sustainability
- Promoting economic development
- Improving public services
- Improving quality of life
There can be more, or fewer goals (I have compiled a non-exhaustive list of 78 that fall under the smart city umbrella) in part because smart cities mean different things to different people:
- For a politician, a smart city address the challenges facing urban areas, improves the quality of life for its citizens, creates new economic opportunities and drives economic growth and development. It also provides an opportunity for politicians to demonstrate leadership and innovation by using technology to improve the lives of citizens.
- The economist sees an integrated approach to urban planning and development that uses technology and data-driven approaches to improve performance and sustainable economic opportunities, growth and development with new business and investment opportunities, and improved competitiveness.
- Civil engineers may see improvement in the performance and sustainability of the city’s infrastructure.
- The planner, a way to identify and address key urban challenges and optimise the functioning of the city’s systems and services.
A dummies definition:
Smart Cities use technology to make cities more livable, efficient and sustainable.
But wait – these goals have been the aim of city administrators form time immemorial. The only difference is the addition of “technology”, and the use of technology in very specific ways:
- Measuring things that matter in a way that allows for timely and rational decision making.
- Providing meaningful access to information for citizens and stakeholders.
The introduction of technology and data analytics in a smart city setting allows for the implementation and achievement of city goals in a more efficient and effective way. It allows for informed policies and programs leading to better infrastructure decision making based on a more accurate understanding of the city and its needs.
Technology and data analytics in smart cities can also allow for better monitoring of progress towards goals, and improved transparency and citizen engagement.
So Smart Cities are simply those that find ways to achieve their goals through the application of technology.
Except it’s not simple.
No single project has the necessary budget to implement enough smart city technology to achieve its own goals. Traditional project funding arrangements do not yield smart cities. They give “projects with cameras”. The city part of Smart City is the key. To achieve a smart city all projects and activities, large and small, need to have a city-wide focus. Where there is opportunity to extend a protect to further the technological goals of a city’s progress to smartness, these opportunities must be seized and exploited. This can generate significant organisational stress, as funding priorities are analysed. A playground that gives 100% fun may need to give 80% fun, and 20% smartness – a difficult pill for some to swallow; and 20% smart might not be enough for the boffins, so they have their own bitter pills. This internal stress requires strong policy and leadership if a smart city state is to be achieved, and “smartwashing” avoided.
Smartwashing, like greenwashing, and other washings, refers to “projects with cameras” being presented as achieving smart goals for political and grant funding reasons.
Leadership, understanding, and communication pave the way to rational decision making through adoption of appropriate technologies, leading us to a smart city.
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