Why don’t records systems tell us what should be there, and what’s missing?

When simplified far enough, every process has informational inputs, a process of decision making with outputs, then a set of actions that follow from that decision.

So why aren’t records systems structured like this?

For routine processes, if there are four inputs, why aren’t there placeholders for those four inputs?

Something to say “this object goes here” and “it’s here” or, “it’s not here”, and to help us assess completeness, and provide meta-data so we can report on completeness.

It seems like an obvious thing to do – so why isn’t it done routinely?

Automation needs either structure or AI – and records can help.

Automation needs structure to function.

This is because all automation is rule based. 

It has to function on an “if this, then that” basis, and it doesn’t work if the “this” isn’t where it should be.

Most AI at the moment is being used to try and structure information after it’s created, rather than during. 

“We didn’t classify that, so we’re using AI to do it” or “We didn’t structure that document, so we’re using natural language processing to populate some meta-data about it”.

Every time I see a new pitch for an AI tool, I wonder how much money an organisation will have to spend on the promise of a magical result, that could have been done far more simply (and cheaply) with a better structure.

I think structure to support automation is one of the great opportunities for RIM professionals. So many organisations with a great records managers are going to benefit from their approach to structure, and their deep understanding of the power of meta-data.

Why talking about customers in government and inside business is a mistake, and we need to do better.

There’s a really simple relationship in customer service.

Investment in service is determined by switching cost.

The harder it is to switch to another service provider, the worse the customer service generally is. 

So service just has to be good enough to prevent “customers” switching governments, or finding a new job.

That’s not very good.

The ongoing values clash between Records and IT is our fault.

Recurrent conversation:

IT – “do we need all of this information”

Records – “they’re records”

IT – “yes but surely some of them are high value and some are low value”

Records – “they’re records”

IT – “do we really need to keep all of them”

Records – “they’re records”

I’ve also had hundreds of conversations with practitioners who tell me that it’s not important to define records.

So we keep having the recurrent conversation, because IT don’t understand records, because we can’t tell them.

Trading off accuracy and efficiency in records destroys the future productive capacity of your organisation.

Yesterday I wrote about the de-professionalisation of records.

Ultimately, it comes down to trading off accuracy for perceived efficiency.

Efficiency is only perceived as efficiency because what we really do is shift the cost of records from a professional team, to other teams in a way that we can’t measure.

That’s bad, but accuracy is far more troubling.

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, what we end up trying to measure is the cost of work that won’t get done because it simply isn’t feasible, because our records aren’t accurate enough to produce reliable results, and the costs of getting them there 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 and many, many more automation technologies as they become available. They’ll also pass audits – which is nice.

Losers will have to do one of two things –

  1. Start a records program to produce high quality records.
  2. Wait for strong AI that can do the work anyway (in 70 years time).

The way to win is to automate and architect. When information enters the organisation in pre-defined structures (or semi-structures), and gets handled automatically you can have both efficiency and accuracy.

The impact of the de-professionalisation of record keeping and the failure of accountability.

Is really a tradeoff between the cost and quality of records.

There’s an interesting trend in records.

We’re de-professionalising record keeping.

Record keeping duties have been given to non-professionals – “business users.”

What hasn’t moved though, is accountability.

Records managers still have accountability for the quality of organisational records.

Their ability to ensure quality though generally boils down to the ability to “ask nicely again”.

So the quality of records we’re producing is deteriorating, while at the same time the compliance statements are being signed, and the bill for the records team is going down.

What’s really happening is that we’re – 

  1. Moving the cost of records from a records team to business users (non-professionals).
  2. Accepting a deterioration in the quality of our organisational records.
  3. Making large portions of the cost of records invisible.

The reasons are understandable, if record keeping is always done by professionals, the number of record keepers required scales linearly with the size of the organisation.

I have to wonder though, if the long term costs will be more expensive than the perceived gains.

Are we making a trade off? Or just making it harder to understand the costs we’re incurring, and making the value that we’re providing look like it came at no cost?