Technology appears to follow a nice progression
Each new version is slightly better than the last
Rarely do we see completely different new, because it’s much easier to stick with we know works
Every so often though, somebody comes up with something new and this triggers a new wave of innovation
Then there’s a new direction to follow
At the start of the 20th Century, we built cars in much the same way as we built ships
We created massive structures, the cars stayed still, and the specialists moved around them.
Henry Ford’s invention of the moving assembly line changed that, and took the product to the people, not the other way around
This allowed him develop experts in a specific tasks. They performed their activity and the product moved to the next stage
Through this could could produce a standardised vehicle in 90 minutes, rather than 12 hours, lowering the cost of manufacture considerably
If you look around at a modern IT department, you’ll see all sorts of specialists working on data
Some people will look after the pipelines, some the storage, some the modelling, visualisations, security and deployment
And each activity will come with its own set of tools
Any wonder, IT costs in organisations are blowing out of control, as the technology becomes increasingly complex
But for some time now, I’ve wondered whether this is reason smaller businesses struggle with technology adoption
So perhaps.. instead of the technology moving around the data..
We move the data through the technology and create an assembly line for business knowledge
Well, thanks to cloud computing, and a few other emerging technologies, that’s exactly what we’ve done
Our approach is to ingest raw data at one end, and push business knowledge out the other in a one-shot continuous operation
Now of course this doesn’t work in every scenario, and as you’d expect, not all cars are built on a moving assembly line
And we continue to build ships in the same way
But not all organisations will need – or can afford – a complex sets of data processing technologies
So our approach with Knowledge Orchestrator is to work with customers to build integrations that help them solve specific problems
Instead of investing in technology that sits around idle, we use cloud computing to dial up the resources as and when we need them
And because we process everything in-memory, we don’t have to worry about data being corrupted along the way through storage and retrieval
This makes it more secure and reliable than the traditional multi-stage approach involving database technologies
But as we were developing this, we realised there were some other unintended advantages
Because data is processed in a highly standardised way, it becomes very easy to incorporate advanced steps such as Artificial Intelligence algorithms
Which means our customers can get access to some amazing technologies, without having to invest the hardware, software and resources themselves
This production-line approach helps lower the cost of knowledge production, so customers focus more on what they do best
It’s another reason why we think Knowledge Orchestrator can help customers transform to the modern workplace
