A bit of backstory on Hubbl Technologies

Hindsight.? It’s something every one of us have at some point in our lives which we had as foresight.? At times we envision a life where we made a pivotal decision differently.? Where we saved our money and bought that house.? Where we stayed in that job.? Where we bought those shares. Where we made that introduction. You get the idea.??

Since selling TOD to Salesforce I’ve had plenty of time to replay the decisions I made and resulting outcomes. I’ve also had a front row seat in the failure of several technology companies that had spawned from Uncommon Purpose - the organization I founded as an incubator of the residual IP from the 16 years we spent building out Traction.? ? Those stories are for another post though, as this one is a backstory on the one that many of you are just starting to hear about, Hubbl Technologies.

The very idea of Hubbl spans all the way back to the time I was working at Crystal Decisions.? A company that would be purchased by Business Objects and then subsequently SAP.? Arguably the most influential company I was lucky enough to work for.

There is a much more detailed backstory here, one that should be told at some point, not now.?

In my time working both for a marketing agency that serviced Crystal as well at Crystal itself I grew a fascination with business intelligence and analytics.? I also learnt both how impactful accurate and timely information could be on decision making and alignment in a company.? The challenge though, was that data, while well presented and accurate, didn’t help people answer the question - what if???

Later I would found Traction on Demand and in its first few years, analytics was the core focus.? I would extract massive data sets from existing systems, assemble them into Crystal Xcelcius dashboards (think gauges and charts that allowed you to change inputs and see change realtime - massive conditional formulas, all excel based) and then provide these to decision makers so they could “play” with the data to decide what they wanted to do. Ironically implementing CRM was a necessity in creating good data to feed and action on analytics.??

As demand for CRM implementation became unrelenting, and Traction began to grow significantly as a Salesforce Implementer, data became our superpower differentiator. ? We worked with most of the biggest names in technology over the years, helping them clean, migrate, visualize and activate their data. ? It was in 2009 in fact that I first met [email protected].? Rob had been tasked to lead the integration of Jigsaw - what would become Data.com into Salesforce.??

The relationship with Data.com would eventually mature into a partnership where we would of course implement Data.com and support their customers, in some cases we would also build software to extend Data.com and Salesforce capability.??

Building actual software was eye opening for me.? Not only could we solve a problem for a customer, being a servant leader this was my happy place, we could scale it to others.? I chased that dragon and studied software development.? We internally funded the creation of three software companies that have all done very well.? The early success in software served as encouragement to cast a better look at how services were done.? If we could apply software thinking to professional services implementations, we could serve more customers, provide higher quality services, make better margins and do it all faster.? Rather than call it “software” we termed it internally as Reuse-Its.??

Reuse-Its opened my eyes to the power of metadata.? Metadata is the data that describes what your system does, how it does it, when it does it and what it does it to.? Metadata in combination with the outside world is what creates evolving data.?

Over the next decade we would create thousands of Reuse-Its.? We invested 10’s of millions into their development and maintenance.? We deployed them as packages.? We positioned some as kickstarters.? We even spun some into products.? Mostly though, we delivered projects faster, higher quality, more predictably and at higher margins.

Still, there was a friction with metadata. In a growing number of cases we would jointly see an opportunity to leverage our Reuse-Its for a customer, only to find that their metadata was chaotic.? Deprecated code.? Overloads of workflow.? Excessive record types.? Just heaps and heaps of patches and adjustments to their Salesforce system - that rendered it impossible to simply activate Reuse. Tech debt was a real thing and only getting worse, as customers were continuously trying to improve.? There was no budget to undo the old.? It was always about adding more.?

There in fact were a few cases where we ended up swallowing hundreds of thousands of dollars in free work for unaccounted for technical debt. As a result, our team put forward the idea of developing technology that would assess technical debt, and provide an accurate means of assessing the level of effort to make it manageable, while restoring agility to their Salesforce system.??

When we sold Traction, that IP and the team most passionate about it moved into Uncommon Purpose - and called themselves Hubbl. They had a greater vision for the application and understanding of metadata.??

We envisioned metadata as the equivalent of the genome.? Metadata describes how a company actually operates.? People interact with it. Systems interact with it. It also serves as the pathways for which data flows.? And as data flows through the channels within metadata, new data is generated.? Data that describes the volume, velocity and impact of that actual data.?

Metadata is the equivalent of the genome of a company.??

This was a major aha moment in Hubbl’s journey.? One that led me to reach out to the person I trusted most in the Salesforce ecosystem.? Rob instantly got it.??

It is my belief that Hubbl represents a new wave in our applied use of technology.? One really only actionable thanks to the incredible advances in AI and computing power.? Understanding metadata is not just a way of assessing how a system works - it introduces a way of finding similarities and differences in industries.? In crushing silos between processes.? In uncovering the artifacts of previous experiments, successes and failures in an organization and surfacing all that knowledge - now.

Truly we can say we are upon the dawn of the adaptive enterprise. ? A period where technology can keep pace with the ingenuity and creativity of the people that operate them.? Where we can unlock organizational hindsight and wisdom - and apply it precisely.

I hope you will stay tuned on the Hubbl journey and this was at least interesting.? ?

Thanks for reading

Greg