Your commercial organisation in three levels and six steps

AI speeds up the work in your commercial organisation, but not everywhere to the same degree. A quote is on paper faster, a mailing is written in an hour. Yet part of the work stays put until someone takes a decision on it. To see where AI speeds up the work and where it gets stuck, you need a map of how your commercial organisation fits together.

I use my own framework for that. It describes a company's commercial organisation, from the commercial policy down to the daily work of every employee. I developed it to see quickly, at my clients, where their organisation gets stuck and what needs to be redesigned. I look at a commercial organisation on three levels and in six steps.

Three levels

Every commercial organisation has three levels:

• Level 0, the strategic layer: the commercial policy. Which customers you want, what you offer them, how you price and through which channel you sell, plus where you look for growth and how much.
• Level 1, the operating layer: the operating rules on roles, collaboration, handovers and escalations.
• Level 2, the operational layer: how each employee does their daily work, with their skills, their tools and the infrastructure.

The three levels connect from top to bottom. Level 0 holds the choices that steer the decisions in the organisation on level 1, such as how you qualify a prospect, how far a salesperson may go on discount and which customer gets a dedicated account manager. On level 1 you translate those choices into operating rules for the work on level 2, so every employee knows what they may decide and when to escalate. Level 2 describes how they apply that in their daily work.

Six steps, with gates in between

On level 1, commercial work runs through six steps.

1. Demand. You raise the interest of customers and prospects until they come to you with a concrete request. This is where the digital marketer works, and the salesperson when prospecting.
2. Quote. You understand the request, specify the solution and price it. In a manufacturing company this is often the heaviest work in the whole organisation.
3. Close. You negotiate price and terms until the customer orders.
4. Onboarding. You guide the new customer's start and install what they bought, up to handover.
5. Retention. You build the relationship with the customer, so they keep coming back and do not switch to a competitor.
6. Expansion. You grow revenue with an existing customer by selling a more expensive or more extensive version (upselling) or additional products (cross-selling).

Between the steps sit gates. A gate is a decision about what may move on to the next step. The best-known gate is qualification: which request gets a quote?

At every gate the levels work together. Level 0 provides the criteria: which customers you want and which jobs earn a margin. Level 1 draws the gate: who decides, how heavily that decision weighs and with what information.

Walmart is a good example. In 2021 it had a chatbot negotiate with a hundred of its smaller suppliers. You read that story in the first part of this series. The choice of suppliers and the goals of the negotiation were level 0. The chatbot's mandate and the approval of those limits were level 1. You see the same pattern at the gate to a dedicated account manager and at the gate to expansion.

Creation and control

With the levels and the steps you know where the work sits. Two concepts then show where AI speeds up the work and where it gets stuck:

• Creation productivity is how much usable output an organisation produces per hour: quotes, configurations, emails, presentations, reports and notes in the CRM.
• Control productivity is how much of that output an organisation checks responsibly per hour. Someone reads the piece with due attention and decides whether it may go out as it is.

On the balance line, control keeps pace with what your organisation produces: everything that needs checking gets checked. Generative AI pushes your organisation to the right, below that line. That is where output without the checks it needs appears. There are two ways back to the balance line: you limit the output, or you build up control with rules and context.

Where AI speeds things up first

Creation and control sit on different levels. The judgement on a quote rests on the choices of level 0. If those choices are missing, someone has to work out for every quote whether the customer and the margin are acceptable. Making the quote itself, with tools and skills, happens on level 2. That is where AI speeds up the work straight away, in your own team and at your customers.

The pressure on control therefore depends on how much extra work lands on level 2. How many more quotes and price requests do your team and your customers produce, now that they work with AI? I look at that in the next part, on the wave of creation.