A CRM for manufacturing with long sales cycles

In manufacturing you rarely sell from a catalogue. You sell a part made to drawing, a machine adapted to a production line, or a series that fits a customer's schedule. So it usually starts with a request for quote. Then comes a technical review, a quote with prices per quantity, sometimes a sample or a pilot run, an audit by the customer's quality team and a negotiation with procurement. Only then do you get an order, or a framework contract with call-off orders.

That journey easily takes six to eighteen months. On the customer side three or four people are involved: the buyer, an engineer, someone from quality and sometimes management. On your side too: the account manager, a sales engineer, production planning and the project lead.

Here is a familiar case. A sales engineer agreed with the customer's engineer that a tolerance could be a bit wider. That agreement sits in an email in his personal inbox. Three months later procurement asks for a new quote, and inside sales builds it on the old drawing. The price is wrong, the customer hesitates, and the deal stalls for another two months.

After delivery the second part begins. A complaint about a dimension out of tolerance. A question about spare parts. A warranty case. These often reach the field rep, who is not the right person, and afterwards nobody knows whether the complaint was resolved.

Lumo keeps the whole journey on one deal and one organization. Everyone involved is a participant on the deal. Mail with known contacts lands on the timeline by itself. Drawings and specifications sit on the deal as files. The pipeline shows which stage each journey is in and for how long. And complaints and service requests arrive in the helpdesk, with a status and an SLA, next to the deals.

In a journey of a year the risk is not that someone forgets a step, but that a deal sits for months without anyone noticing. That is what automations are good at. A rule reacts to a new deal, a stage change, a won or lost deal, a new lead or organization, a completed activity, or a deal or lead that has been stale for a number of days. It creates an activity or note, updates a field, assigns an owner or adds a label. It does not send email.

Rules manufacturers often use:

• Deal enters Technical review: create a task for the sales engineer due in five days.
• Deal enters Sample or pilot run: create a task Follow up on sample in 30 days.
• Deal stale for 21 days in Quote: create a call with the buyer for the owner.
• Deal won: create a task Handover to production planning and add the Customer label to the organization.

The lead side works the same way. An RFQ from the website that sits on New for a day goes to inside sales. You test every rule with a dry run first, and the rules overview shows which rules are on and off.

Say a machine builder with 120 employees that builds packaging machines for the food industry. For this example we call it Brink Machinery. It has three account managers, four sales engineers, an inside sales team of three and a service department. A third of its revenue comes from Germany, through a dedicated account manager.

Brink creates two pipelines. New machines with the stages from the example above, with a 45 day rot period in the sample stage, which Brink calls Factory acceptance test. And Retrofit and expansion for existing customers, with shorter stages. German deals carry euros, deals with a British customer carry pounds, and reports convert them.

Each deal lists the customer's buyer, technical manager and production manager as participants. The specification and line layout sit as files on the deal. The sales engineers connect Gmail, and the account manager for Germany works in Outlook and puts the BCC address on his emails.

The service department works in the helpdesk. Breakdown reports arrive through a shared mailbox and get a priority. A high priority breakdown has an SLA of four business hours for the first response.

Every month leadership reviews a dashboard with weighted pipeline per quarter of expected close, average duration per stage and lost reasons. It turns out journeys slow down mostly in the test stage. That becomes the management conversation, rather than the question of why the numbers are disappointing.