In my last post, I wrote about the Single Source of Truth (#SSOT) and the main barriers to achieving it: https://lnkd.in/dgiiMdKG

Before I jump in straight to the #dataflow, which enables us to reach the SSOT, I want to emphasize:

1. SSOT is necessary to enter the automation and AI world fully. Quality of data = quality of outcome.

2. Moving towards SSOT means making biiig leaps toward operational excellence. Your company is faster, more profitable, and you have more satisfied teams and clients.

3. SSOT makes creating beautiful and powerful in-depth dashboards much cheaper.

So let me explain why I have chosen the above setup.

A year ago, I needed to make a choice on how to run our company further when Excel was no longer enough.

- should I buy expensive enterprise-class software?

- should I develop my own custom software?

After a few meetings with recommended ERP software providers, I realized that it's an extremely risky project. It would rely on expensive subcontractors outside our power. And how many excuses could they make, with such a rapidly changing landscape of my companies?

That's why our team in Automation House decided to attack the subject differently, as shown in the title picture.

In this approach:

- everyone can still use their favorite modern-looking apps,

- we connected them via Make to give them new superpowers based on automation scenarios,

- we can create a full-fledged Business Intelligence system, maintaining elasticity in the quickly-changing business and market realities,

- every element of the system leaves clean data in a SSOT database, so you always know what the truth is about the current numbers in the business.

Even without changing one app in your company, you can collect all the data in a data warehouse (or a simple database at first), and view it on dashboards in one app from every device.

If you have any questions about this setup, please let me know, and remember to follow me not to miss the next posts about the data we can extract with one click from this dataflow.