Profile Data does not have to be difficult! From George Clooney to carpenters and dirty washing, Julian Schwarzenbach, data and asset management consultant, author and trainer, chats to Louise Parfitt on why data is all about people and keeping out of mischief The data about me could say I am a George Clooney lookalike, although, clearly, I am no Mr Clooney doppelganger even if the data looks good and is plausible. But no AI tool is going to know that the data is not accurate, so, when it comes to data, we need to realise that technology cannot solve all our problems. Talking to Julian Schwarzenbach is not what I expected. Despite the strapline on his LinkedIn profile that data does not have to be difficult, I am a little apprehensive about the interview. To me, data is a slightly intangible, seemingly complex subject that I would normally shy away from. But if George Clooney is involved, maybe I could get on board. Back to Schwarzenbach: There is a very close symbiotic relationship between the technology that IAM involvement Work satisfaction I like to help bring people on the journey, and Im very much a pragmatist at heart. For me, its far better to come up with a solution that the organisation can work with to get from where they are to being a step better, rather than aim for a perfect solution, which may be so far ahead of what people can conceive of or deliver that it is just completely meaningless. Whats very rewarding is when people say, oh, weve developed that and see the results for themselves. stores and exploits the data, and the data that goes into the decision-making, which often comes from people. The two have to work together, he says. Schwarzenbachs whole approach is very peoplefocused. Inspired by his dad, who taught mechanical engineering and after discovering he had a flair for technical drawing at school he went on to study engineering at Sheffield University. His first job was working for a heavy engineering company, making bridges, cranes and large machinery. I moved into automotive for a short while, then I spent a couple of years in quarrying, which involved setting up the maintenance management system for a large new quarry. Then followed 15 years in the water industry, where he started off managing a maintenance workshop in the Midlands. By the end of my time there, I was running the companys maintenance systems, including the asset inventory, investment management, and programme management systems, and looking after the operation and maintenance manuals, as well as the teams running the systems. So, in a way I came full circle. At the end of 2006, Schwarzenbach made the move into the big bad world of consultancy. I spent a couple of years in a pure asset management consultancy, with a focus on asset information, because, by that time, it was the data and the asset information that was driving me forward. Then my wife, Ann, and I decided to set up our own consultancy, Data and Process Advantage weve been doing that for 13 years now. Data and asset management Data at rest is a cost to an organisation: it has potential value, but it hasnt actually delivered any value. When the data is used to inform decision-making, thats when it delivers value. Whether that is I need to go to maintain this asset thats failed or how can I find my least reliable assets out of the million that we own, the data is whats going to drive that decision-making and it enables you to make the right decisions to deliver value to the organisation. This effective decision making is especially important in asset management situations. If you dont understand the quality of the data you are provided in the updates from the field staff, you are compromising future decisionmaking. You are also increasing your future risks Hammer time Schwarzenbach deliberately took the decision not to develop or sell software because, he says, technology is no silver bullet for the data issues that companies have. Avoiding software sales means our advice to clients is truly independent. Typically, most of their recommendations for companies are all about processes and procedures, and having clear standards, ownership and governance in place. Its almost never you need to buy this software product. It all comes back to that relationship between people and data. I try to get people to have a carpenters mindset when thinking about data, he says. A carpenter takes a piece of wood out of the stockpile and assesses the grain to see if there are any knots in it or any areas of rot or weakness. Rather than assuming the wood is perfect, they are looking at the imperfections so they can get the best value out of each piece of wood. People working with data need a similar mindset; they need to recognise the data usually isnt perfect and it never will be. So, we encourage people to understand the nature of the imperfections in the data to make sure they are using it in the best way for decision-making, then to look at ways to improve the data gathering in the first place, which is often done by people. The people factor When the data is used to inform decision-making, thats when it delivers value. Data enables you to make the right decisions to deliver value to the organisation What intrigues Schwarzenbach about his work is not so much the data, but the culture and relationships in the organisations with which he works. What is interesting is the people, the behaviours, the organisational aspects behind the data. Very often, there are a lot of things that can be done quickly and easily, without spending a lot of money, to improve how you look after your data such as changing processes and standards to look after and retain the quality of the stored data. The problem you get is that data can become a bit of a difficult thing to manage if you dont look after it. One utility company he worked with had no document management system, so their planners spent a lot of time trying to work out which was the most upto-date schematic diagram for a site. Often, somebody will spend a lot of time trying to find the right bit of information or trying to merge three or four datasets. This reduces organisational efficiency and product/ service quality, but, sadly, is accepted as normal by many organisations. If you use outdated information, there are potential health and safety risks. A number of years ago, there was a gas explosion where the utility company had assumed an old pipe had been replaced with a modern plastic one. In fact, it was an old cast iron pipe that started leaking, yet the data implied it had been replaced. Because the company didnt know, it got fined. If you dont understand the quality of the data you are provided with in the updates from the field staff, you are compromising future decision-making... and future risks. Joining the IAM I joined the IAM in 2007, when I moved into the consultancy world. I was working for AMCL at the time, which was, and is, a patron of the IAM the team there really encouraged me to become active in the institute. I got involved in the development of the Asset Information Guidelines, as they were initially titled, which then became the Asset Information SSG. I have been involved in a variety of other things with the IAM subsequently. Im on the UK Chapter committee and the Climate Emergency Programme, helping from an asset information perspective. I also represent the IAM on a number of standards bodies, including the committee thats developing the ISO 55000 series of asset management standards and the BSI B/555 committee, which looks at building information modelling. It definitely keeps me out of mischief! Psychology at work This highlights another issue: its not those who provide poor data, or dont bother providing any data, that suffer the consequences. The pain is felt further down the process by those trying to use the data to make decisions about maintenance and asset management, who are faced with inconsistent or incomplete data. You need to be very clear what information you expect people to provide from a job, explains Schwarzenbach. The analogy he uses is the teenagers dirty laundry syndrome. Your teenage children may develop a habit where they leave piles of dirty washing around the house, with the expectation that a parent or carer will pick it up and wash it: thats the learned behaviour of your teenage offspring. If you start haranguing them every time they leave dirty clothes lying around, eventually theyll realise that, for a quiet life, they had better put it in the laundry basket themselves. We need to try to get that kind of mindset for our field staff. If somebody whos just done a job on site hasnt filled in the details about what they did correctly, theres no comeback. Therefore, theres no incentive for them to improve what theyre doing, which is why you need an artificial feedback loop, explains Schwarzenbach. This could be a case of running a report for all the jobs done yesterday, to see if the data is complete for them all. Perhaps you could do a league table comparing the reports of different teams. As soon as you put something comparative like that in place, people have motivation, because no-one wants to be at the bottom. We always like to be at the top. If people are part of the solution, then they can keep it going; they can build on it. Then the approach to data and quality management is a lot more organic and evolutionary, and people keep on building on those foundations. On downtime I love gardening: we just had the garden redone, so I am enjoying taking the time to help bed that in. I like hiking, cycling, and usually Ill play badminton on a Friday night. I like being outdoors and being active even when I am on holiday, Im on the go. A cruise or beach holiday just isnt for me. I have two grown-up children: my son is making his way in the world of retail and my daughter is a project manager for an engineering consultancy. Theres a running joke in the family that, at the age of three, she asked for her first clipboard: shes always been good at organising! I have dual nationality: Swiss and British. Although I have lived in the UK all my life, I love going to visit Switzerland: the mountain scenery is just spectacular.
