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The programming world is full of mathematicians, logical people, engineers. But they might not be the best people to make software.

Making software which really suits an expert work is more like architecture, designing buildings people really want to live in – who have a detailed internal model of how people behave in buildings.

Or consider the people who create high street retail businesses, who need to create a sense of welcome for customers, and also maintain security – quite analogous to what software ought to do.

Interior designers can create rooms which people want to be in.

Ergonomic experts can create tools which fit the way people’s bodies work so they feel intuitive to use.

Writers and editors can deliver information to an expert the way they want it.

Advertising people can make someone excited about an opportunity.

The police know how to make sure people are aware of a problem.

These are all people who know, in their own way, how to develop a good environment for expert work, and there are plenty more designers.

What if software was designed in depth by these people – and then once it had been comprehensively designed, the mathematicians, engineers and logical people step in to build it?

Experts in all organisations need to be good at spotting problems, spotting opportunities, and figuring out solutions to the problems and ways to go after the opportunities. They also need to be good at pursuing goals set by others.

What happens if we try to imagine software developed from the start to meet that objective.

The software needs to have a very sophisticated ‘model’ of the expert’s landscape. By sophisticated we don’t mean technically complex, we mean accurate – in the way a model of a building can be accurate.

I don’t know what the most important information someone in an organisation I don’t understand needs when they sit down at their desk in the morning. A school headmistress might be most interested in exam scores, absentee levels, temperature in the building, the mood of the parents, the status of a specific problem, a visit from an inspector, a problem with the building, a staffing issue, I don’t know. What I’m saying is, most of the above factors could be made available digitally if they aren’t already, and someone could build software to deliver it.

So she sits at a computer, the computer says “here’s the information you are most interested in right now”, and “here’s something happening you might want to know about”.

Continuing the idea – every small company has business development and sales staff. What information do they want most at the beginning of the day? E-mail can deliver them reactive stuff (complaints from customers for example) but their job is fundamentally to grow the business not reply to e-mail. Perhaps there could be some relevant news about something happening in their town or their industry, or something a competitor is doing, or an opportunity to meet a key client in a conference. There could be relevant internal news about a manufacturing problem or advance. I don’t know.

But with a detailed insight into this expert’s landscape, it would be possible to build sophisticated software to provide the expert landscape.

Note that we’re not talking about analytics, BI or decision making tools here. This can be part of an expert’s data landscape, yes. But the core part of it might not be particularly sophisticated – go back to the headmistress example – just information about the temperature in the school hall.

 

Here’s an idea (well I’m not the first to think of it, but bear with me)

Shouldn’t enterprise software stimulate its users?

Let’s say, the role of an expert is usually to spot and understand problems, spot and understand opportunities, and develop solutions.

Historically software has been very good at (let’s say) anti stimulating people – the software version of the smoke alarm which goes off by itself – it gives you a list of things it doesn’t like (usually something wrong with the data), which basically gives expert workers some extremely tedious work.

What software could actually do is almost ‘tease’ the user by showing them some information it has found which look like it might lead somewhere – so the user is inclined to follow it.

Analytics tools could be analysing data all the time for something which the human might want to pay more attention to.

An interesting idea, shared by Paul Cleverley at a Finding Petroleum conference earlier this year,  is that search engines should aim to surprise the user, rather than bring them exactly what they expect.

Case management tools could act like a mentor to the user by being able to say ‘last time the situation was like this, here’s what the people did about it, and here’s what happened’.

This all requires sophisticated software but is easily possible with today’s technology. There’s just a lot of manual work involved understanding the expert’s landscape and the information available, to work out what would be helpful.

SAS, a US analytics company, has a customer base which could be a close match to where the ‘Software for Domain Experts’ concept would work. Let’s go through it. This is all taken from the SAS website.

Capital markets – risk management, fraud, capital management

Casinos – marketing analytics, pricing, gaming analytics

Communications – audience analytics, network analytics

Consumer goods – supply and demand planning, marketing + sales analytics

Defence and security – operational analytics, logistics, predictive maintenance

Health care providers – outcomes, care delivery

Health insurance – managing costs, customer analytics, risk

High- tech manufacturing – product quality, marketing, supply and demand planning

Higher education – strategic planning, data visualisation

Hotels – marketing, customer loyalty, pricing and revenue, operations analytics

Insurance – fraud detection, profitability, compliance

K12 (up to age 18) education – effectiveness

Life sciences – research and marketing

Manufacturing – Supply and demand planning, product quality

Media – audience analytics, ad revenue management

Oil and gas – analysing reservoirs, assets, risk

Public sector – effectiveness, fraud, criminal justice

Retail – marketing, customer insight, demand forecasting, pricing

Small mid size business – forecasting, business intelligence

Sports – fan engagement, operational analytics, player analytics

Travel and transport – revenue optimisation, assets, demand forecasting

Utilities – grid analytics, customer analytics, energy forecasting, revenue

Most people dislike being told what to do – particularly by software.

How much of the problem is in the software itself – and how much of the problem is in the people who configure business software?

We’ve all heard people talk about how you want to get data users to enter data in drop down lists rather than free text so it is easier to process later,

And there are various other tricks that software designers use to get the results they want from users.

Business users are not like home / personal users – they don’t usually get much choice in their use of the software, and they are being paid to do it. So how much incentive is there to make software for business users which is really fun to use?

For the entire business there’s plenty of incentive, if it means that staff are motivated, using much more of their brains and excited by their work.

But for the IT department, are they just another problem to solve?

 

Where does the Software for Domain Experts concept provide the most value?

I think we are talking about domains where:

• there’s an enormous amount of data, in lots of different sources, which people need to somehow make sense of
• there’s high value decision making involved
• the expert roles cannot easily be shoehorned into a process, and efforts to make them into a process have (at times) just made it worse.

We are not looking at domains where there isn’t much data, or the data is very structured already or can be put into a process.

In some fields, the data can be managed by professional researchers and academics writing up reports – and that can be the best way to do it. But we are talking about software and automated tools here.

So domains I think our concept works best in could be:

• Very senior business / organisational decision making at any level
• Any marketing / business development role – figuring out where to take your company next and working out if it is working or not
• Government intelligence role
• Oil and gas role, managing complex infrastructure or reservoirs with enormous amounts of data
• Government policy making role – including running cities and transport systems
• Running health systems

Possibly it could be used in purchasing and hiring decisions – where there is a lot of data available.

The amount of data available in every field is going up astronomically driven by sensors and mobile devices, so this concept will be applicable for more and more fields in the future.

There are probably plenty more fields it could add value in, I am maybe showing a bias to fields I have a better understanding of.

 

How do experts actually want to work – or create the most value for their organisations?

They want the deepest possible understanding of what is happening around them.

They might want to be put in touch with people at a similar expert level to discuss something.

They might have a complex decision to make (which they might want to make going for a short walk, not with ‘decision support software’).

What they definitely don’t want is software which gives them a list of tasks to do, without explaining why they need doing, how they fit into the overall organisation’s processes, what the software does with them, and how it ends up.

In short people like to drive themselves (and their software), not have the software drive them. A sense of serendipity is quite essential.

There are many people talking about data analytics and decision making software. There are many companies in this field. It is hard to tell the difference between the companies most of the time, but still it is clearly an interesting area. I think it would be hard for anyone else to add value there, beyond taking analytics to a new level, perhaps within a specific domain.

There are also many people  talking about improving organisations – this is not a new debate. There are news stories recently published about how horrible it is to work at Amazon, and whether that is ultimately good for business. There are people talking about how to develop character and how this doesn’t happen very easily in big organisations (unless you count narcissism or self centred ness as character). In the oil and gas sector, people are starting to talk about how to bring back trust.

What we offer which is new, we think, is the idea of bringing both of these together. Can more expert centric software help experts both to make the best use of analytics software, and make organisations better to work in? Are we solving two problems at once? Or just merging together two ideas which don’t fit?

Many people are getting excited about the potential of analytics and big data, writing about how, one day, we might be able to find any answer we want – about health, public transport, future sales, finding oil and gas – by gathering tons of data and analysing it.

The ideas are worth getting excited about, even though they haven’t happened yet (although I have read the story a couple of times about the teenager’s father who got upset after his daughter received promotional materials from a supermarket about a pregnancy. The father didn’t know she was pregnant, the supermarket had guessed she might be pregnant after seeing patterns in her purchases which pregnant teenagers usually make).

But another thing worth considering is the risk of people losing track of fact when they are buried in a sea of analytics.

In any job there are key facts that someone in charge of any organisational function needs to know. (For example, what their boss wants them to do, some key change which is happening that they need to respond to, or be aware of).

How can analytics software make it clear what is fact and what is analytics?

Or should be limit the role of analytics software very specifically as analytics – ie here’s a place you can go to, to get analysed data – which is a very different place for where you get your facts?

Some people in the world are happy to be led everywhere, given instructions and told to follow them. They don’t mind using software which gives them a list of instructions to follow as well, with the user having little understanding of why they need to do something or what the software is going to do with the information.

There are also many people in the world who don’t think that way – who like to explore things in their own time and their own direction, who want to ask for information rather than have it forced onto them, and like to use the full power of their brains to understand a scenario based on the information available.

You’re probably familiar with the basics of this discussion – school has been designed to get people to follow the rules because that’s what the industrial revolution needed 200 years ago, and it still suits many companies today having employees who do what they are told, and Google developed a much more freewheeling working environment and look where it got them.

But still – we think – enterprise software has some catching up to do. Most enterprise software still takes users through a list of steps, or gives them tasks for follow, as part of their ”workflow”.

This was fine 10 years ago when people wanted software to automate these tasks, and make sure the company’s processes for sending out purchase orders and so on were followed.

But now we’re at a bit of a cross roads with software. Software can do much more powerful stuff with business intelligence and analytics – and it creates the potential to make software tools much more geared to the way free thinking people like to work.

How can software work better for free thinkers?

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