Software in Crosshairs: Part 2

After publishing “Software in Crosshairs” last week, I received some interesting feedback. One email from someone who works in enterprise SaaS stood out as he took bit of an issue with how Foundation Capital outlined incumbent companies’ inability to capture the context graphs. I am publishing his email with his permission:

“I want to correct a few things on Foundation Capital’s piece that they either over simplified or didn’t know:

1. Salesforce as a current state memory system: this is extraordinarily easy to accomplish in Salesforce. It’s true we can’t capture conversations in the hallway but no one is proposing that nor would that make economic sense to store 90% of hallway garbage conversations in a database. If it’s on video, a phone call, a slack message, etc. We can trace these things, I think they have a misunderstanding of our product offerings and capabilities. These are not new.

2. Zendesk/Slack example- most enterprises aren’t using Zendesk, it’s either Service Cloud or ServiceNow. This is do-able (tying context together).

They are right that software in theory is at risk, core applications less so in my view but there are challenges for each group and their lack of knowledge is a big one (we have a lot of people who have built terrible systems due to this). Undoing decades of short term decision making is a monstrous task and very few are doing this because a CEO isn’t measured on all of the system cleanup they did nor does IT understand the context of the data for a LOB to transition these into rich insights or create new ones. Incentives, awareness and skill sets are the big issue.

What people don’t appreciate is that building all of these foundational tools and modules (the modules are the key) natively is not worth the effort nor will you get them all right so you’ll create the same silos eventually.

I can go on but I’ll save the rant. There is a fundamental misunderstanding of core software applications like CRM, HRIS, ERP, etc. They’re misunderstanding the downsides, the upsides and the actual risks.”

Indeed, the difficulty for incumbents may largely come from their culture and org structure while competing with companies designed from ground up keeping AI models’ increasing capabilities in mind. I go back to a pithy remark made by John Collison during his conversation with Satya Nadella last year:

…people point out a lot that current companies are modeled after manufacturing companies and Alfred Sloan type stuff, despite the fact that we're doing knowledge work today and not running a little manufacturing line.

I will discuss more on this as well as Veeva’s approach to AI behind the paywall.

In addition to “Daily Dose” (yes, DAILY) like this, MBI Deep Dives publishes one Deep Dive on a publicly listed company every month. You can find all the 65 Deep Dives here