Is that consultants are paid to think.
Service providers are paid to do.
If you’re not sure which you are, here’s how to think about it.
If your clients say “we have this problem, we’d like you to come and work out how we should solve it” – you’re a consultant.
If your clients say “we have this thing we need to do, we need you to come and do it” – you’re a service provider.
It’s natural that engagements will have elements of both – this is a continuum with pure consulting at one end, and pure service provision at the other.
You’ll get service providers who spend time with clients to help them work through the design choices that need to be made before the can quote the service.
You’ll get consultants who do fixed term engagements and have a process to work through.
The basics though, are that you pay consultants to think, you pay service providers to do.
Yesterday I wrote about the de-professionalisation of records.
Ultimately, it comes down to trading off accuracy for perceived efficiency.
Efficiency is only “perceived efficiency” because what we really do is shift the cost of records from a professional team, to other teams in a way that means we can’t measure the costs easily.
That’s not great, but loss of accuracy is actually far more of a problem.
Accuracy is what you will build the entire future of your organisation on. Any process that relies on the records relies on their accuracy.
Unfortunately, when we try and measure the cost of a loss of accuracy, we fail because what we have to measure is the value of work that won’t get done becasue it isn’t feasible.
This is the work that won’t get done because our records aren’t accurate enough to produce reliable results, and the costs of making them accurate are so large that it’s not feasible.
There are going to be winners and losers in this.
Winners will have high quality records, and will be able to take advantage of machine learning, high quality decision support systems, and many, many more automation technologies that are the only way we can deal with exponential growth of records and information.
Winners will also pass audits – which is nice.
Losers will have to do one of two things –
- Start a records program to produce high quality records.
- Wait for strong AI that can do the work anyway (in 70 years time).
The job a product does is very different from what it does, and what it delivers. Thinking about a product as though it does a job gives us a way to think about what it competes with, and other things that can do that job just as effectively.
Wine is a great example. When we think about wine and what we might choose instead, we typically think about beer or spirits. This largely depends on the job wine is doing for us.
If the job of wine on that night is to help us deal with stress, the competitors aren’t just beer and spirits, they are exercise, a massage, a walk somewhere pleasant, a trip to the beach, a good book – the list is far larger. If the job of wine is to show that we have refinement and taste, the job might also be done with nice clothing, a high end car, a day on a yacht or tickets to an opera.
Thinking about the job a product does provides us with a different lens, and helps us think more widely about who we compete with and what our opportunities are.
“Regulatory audits are enjoyable experiences.”
That’s what organisations say when they have good records.
The audit process is smooth, efficient, and low stress, because they’re permanently ready.
Mostly though, regulatory audits aren’t enjoyable experiences. They are high stress, and there’s a huge rush of last minute work to try and be ready.
The last minute rush is record assembly.
It’s trying to create complete records out of all the pieces of information collected and created by your process.
When you have a complete record, you can hand it to the auditor knowing that it’s everything you have.
And the audit is, for lack of a better word – enjoyable.
“It doesn’t work” is a dangerous phrase.
It’s almost always untrue.
People use it as code for any number of other ideas.
A couple of types of “doesn’t work” –
- Results didn’t occur quickly enough (so we stopped before they appeared).
- We don’t really understand the task (so we didn’t get results)
- It’s inefficient (it works, but costs more than we get out of it)
- No one else has got it to work (yet)
- Defies physics (can’t work under any circumstances)
History is littered with people who were unsuccessful because they mis-read the “doesn’t work” they were dealing with.
Recognising which “doesn’t work” you’re dealing with gives you options – but only if you recognise which one it is.
We are in a world where privacy regulations are giving control back to people, and imposing significant penalties on organisations that don’t adequately secure personally identifiable information.
There are only really two possible things your organisation can focus on to navigate this new landscape.
The first is to spend more on securing your data than you ever have before. This is the easy route – because greater magnitude of harm means greater risk mitigation expenditure. The maths is simple, the board will get it.
The second way is to reduce data data capture to the bare minimum, and delete or anonymise what you’ve captured as soon as you can.
This isn’t easy, it requires your whole organisation to take a disciplined approach to data capture that recognises the new risks.
It requires questions like “why do we need that data to deliver our service, and for how long” to be asked and acted on as a matter of routine. If you’re doing really well, you’ll have a business case for every bit of data you capture that will also have a time value.
Innovative solutions will be required to gain the advantage of broad and long term data capture, without incurring the liability, and without becoming target.
The hardest part will be getting people to hit the delete button, because we’re used to hoarding, not minimalism. We’re convinced that data is the new oil, when it’s actually the new Plutonium, and needs to be handled like it.
There will be two types of organisations in the future – those who overspend on security, get nothing back on their investment and still get fined, and those who capture only what they have to, and innovate. The second way is better.
Stop making copies.
Creation of original content is difficult and time-consuming.
Creation of a copy takes seconds.
When we went digital, copies got cheap. So we make more.
When you stop making copies search gets easier, and quality goes up.
If you want to raise your information quality, and make search easy, stop making copies.