Enterprise by Silkworks

Let's do a little exercise and think—what is the next thing on your task sheet? Perhaps it's a new feature? Opening a new sales channel? Making some workflow more efficient? Whatever it is, my next question would be: why is that one next? Most efficient people want to tackle tasks that have the largest impact on their business (or team, etc.), which usually means, in some way or another, an impact on profit.

OK, then—how much revenue would tackling this task result in? How much of an increase in cost? I'd probably say that 99% of the time, the answer is something like, "It will increase revenue" or "It'll cut costs." OK, but how much—by $1 or $1,000,000? Because between those two numbers lies a vast graveyard of companies that could have been but instead just kind of winged it.

With all the advancements in generative AI, analytics looks much the same. Sure, you can feed an LLM some data, and it will spit out a plot for you, but for the smart businesses that do proper analysis of their decisions, it's still quite a laborious process for their data team. It’s generally done for some KPI that may or may not be easily relatable to company-wide metrics such as cost and revenue.

But it can be argued that a (for-profit) company's reason for existence is to make money. These KPIs are generally proxies for profits in one way or another, which is totally reasonable. It would be impossible to model the effect on profit for every decision that you make. But when you're deciding on a feature that takes up 20 hours of engineering time or leads to a 30% increase in cloud computing costs, you want to know what kind of impact a decision could potentially have on revenue.

This is where Enterprise by Silkworks comes in. You basically set up a "model of your business." Not a business model, but really a model of your business operations. This can be as detailed as you want. It can be just the sales output of your Japan team for the year, or it can be what Jim sold on Wednesday. You then convert these up to the company level.

Jim landed a contract that gets us $150 per week for the next three years (revenue for Product A) but has an 8% commission (cost), plus we have to pay $3,000 a month (cost, but different time series), his benefits, etc. You can do this for all things that influence cost or revenue at the company level, and you funnel it all up.

Now you have a big tree modeling all of your company's operations (really a DAG, but close enough). With this, you can make predictions of the form: "What would a 1% increase in our marketing budget result in, in terms of revenue?" or "What effect would a five-minute increase in the average customer time spent in the app have?" One might have orders of magnitude more impact than another, but you'd never know without modeling it.

This kind of data-driven decision-making is quite common at larger companies. It just requires hordes of data scientists, finance team members, and analysts working full-time on these sorts of problems. But Enterprise by Silkworks is completely AI-based and built to intuitively match the abstract structure of a business. A smart person at a small company could do in days what used to take an entire department at a conglomerate months.

Do you really want to leave all that money on the table?