What are the unique challenges with modeling and operating on “process grains”?
For effective business analytics, three critical “grains” are of interest: time, entities, and processes. Time grains (such as monthly and L28 days) and entity grains (such as user or account segments) are well-understood in this context.
However, there are two distinct challenges when it comes to process grains:
1. Organizational:
Consider a self-serve trial process for a SaaS product where marketing generates leads that convert through sales-assisted channels to paid seats. Even a straightforward process like this, with direct metric relationships during an acquisition process, involves multiple functions with differing incentives and operational cadences.
Marketing tracks leads generated and reacts to daily metric fluctuations, while sales monitors demo completions further down the funnel, and revenue leaders focus on new paid seats over longer timeframes. Operating on this process holistically, navigating through different process steps, requires constant communication and alignment across these functions.
2. Technical:
a) Indirect Processes:
For instance, a support team responding to customer queries does not have a linear and direct impact on downstream retention metrics. Therefore, making decisions around investment levels for efficiency improvements becomes challenging.
b) Data Modeling:
In general, modeling processes and their dependencies is more complex than isolated metrics because processes unfold over time, adding intricacy to modeling the relationships.
We are finally in the era where metrics across business models are getting standardized. Modeling processes and capturing “process grains” as a fundamental concept is at the frontier of our current knowledge.
Over the past decade, with the accessibility of cloud storage and ease of processing power, and the democratization of data querying skills, analyzing data across varying time grains and entity segments has become significantly easier and well-understood.
The next frontier is seamlessly traversing process grains, to zoom in and out of the networked, inter-connected business processes. Excited to work on this problem at Trace.
