The layer behind the dashboard — Achintya Verma

The ambition was never to put another dashboard in front of an enterprise. Enterprises have plenty. Each one was built to answer a question somebody once asked, and each now sits in a row of others, mostly unopened.

I wanted to build the layer behind the dashboard.

01What a dashboard can and cannot do

A dashboard shows you what the data says. It is only as good as the data, and only as useful as the person reading it at that moment. It does not know that two of the rows are the same thing. It does not notice what is missing. It reports a duplicate payment faithfully, after it has been made.

02Four things the layer behind it does

It understands the data. It knows that three descriptions are one bearing.
It sees patterns. The same vendor, the same amount, two days apart.
It catches what people miss, because it looks at everything and people look at a sample.
It turns fragmented systems into something that can reason across them.

03Recording and understanding

Enterprise software became very good at recording what happened. It is remarkably bad at understanding what should happen next. That gap is the one Quantum Beetle exists to work on.

04What this looks like in a product

MIDAS is the clearest example. A material master is a list. You could put a dashboard on it and count the records. MIDAS does something different: instead of simply storing another material code, it is designed to understand what that material actually is. Once a system understands that, duplicates, substitutes and missing data stop being things you search for. They become things the system tells you.

05The test I use

When we design something, I ask whether it would still be useful if nobody ever opened a screen. If the answer is no, we have built a dashboard. If the answer is yes, because it stops the wrong order or flags the wrong payment by itself, we have built the layer behind it.

In short

A dashboard reports; it does not understand the data it shows.
The layer behind it understands, sees patterns, catches what is missed and reasons across systems.
Enterprise software records well and understands poorly; that gap is the work.
The test: is it useful even if nobody opens a screen?

Questions

Does Quantum Beetle build dashboards?

It builds dashboards where a client needs to see something. Its focus is the intelligence underneath: the layer that understands the data and acts on it.

What is "the layer behind the dashboard"?

Achintya Verma's phrase for intelligence that understands enterprise data, finds patterns in it and says what should happen next, as opposed to software that only displays it.

Which product shows this best?

MIDAS, which is designed to understand what a material actually is and not only to store its code.

Sounds like your problem?

Tell us about it. We'll say honestly whether the swarm can help, and what it would take.

Talk to us hello@quantumbeetle.ai