We listed a few of the core concepts if you don’t want to read the history document.
When we first started, back in 2001, our original goal was inventory tracking. As things progressed, one of our main goals was to figure out a way to help fill the gap or create a “bridge” between operations and accounting. There seemed to be a very large and visible disconnect between what was happening in the field (operations) and what the final output was (accounting and final numbers). In one of our brainstorming meetings, we came up with the analogy of a “zipper”. One side of the zipper was operations and the other side was accounting. Our goal was to start bringing them together one cog at a time, like a zipper being pulled upwards until it came together.
We came up with the theory “track every penny in and track every penny out”. With this thought in mind, we started to track each penny from start to finish. What we found was that every transaction had a life-cycle that it went through. We decided to enter the items and data as easily as possible on the operations side and then track it through a number of steps until it found itself finished or completed. Along the way, we started time-stamping each step with a flag and a date. Each flag and date combo became what we called a “checkpoint”. As each new flag was added, we would lock the prior steps below that based on permissions.
This process of passing data from checkpoint to checkpoint, based on permissions, is how we track your data. A great analogy of this process is if you imagine what it takes for water to turn into ice. This process doesn’t happen all at once, it needs to go through different phases, states, or status levels. As your data passes through these different phases, called checkpoints, we simply help you flag and date the data as it runs over time. Just like the ice analogy, the water droplets are very loose at first “operations” and slowly become crystals, then slush, and finally become completely frozen or ice “final numbers and accounting”.
We then use a process called “roll call accounting” to virtually map backwards in time to where the data was at a given date or time. Another synonymous term for roll call accounting is data mapping. The reason we use the term roll call accounting is because that is what we ask the computer to do. Imagine data that is flagged and dated as it goes through certain checkpoints. Pretend that the computer is an army General giving out a roll call or a flag/status report. The computer says, “I need all of the invoices that were not fully paid at such and such a date to step forward”. Only these invoices would then be counted – based on flags and dates. You could then use the computer to do the math and give you the totals you need. Each time you want more information, you simply tell the computer what criteria to use for the roll call and eventually it will tell you the story of what is going on.
To sum things up “literally”, by keeping track of your normal day-to-day operations, we can get very complex results like aging, histories, usage, reports, final numbers, and accounting. Thus the accounting becomes the date sensitive sum of the details. These values are what make up your “Business Intelligence (BI)” or “Big Data” concepts. It all comes back to managing and tracking your data. Because every piece of the puzzle still exists in the database, you are able to virtually go back in time and see what was where and when it moved out of each checkpoint. If the data is correct, let it flow. If a modification is needed, make the correction, lock it down, and let it keep flowing. The accounting becomes more of a check and stamp of approval rather than entering numbers from different journals or locations. When you put it all together, what do you know… All Data Is Live And Searchable.