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Feature · Management & leadership

The monthly figures arrive on the 20th. The decision was taken on the 5th. On gut feeling.

As the managing director of an SME you take most decisions on experience and gut feeling. Not because you want to, but because the figures arrive too late, from three systems, in three versions. AI and automation bring the figures up to today and the summary to your phone. What they do not do: predict the market or take the decision. That remains your job.

// A feature at a fictional manufacturing company with 60 employees, an owner-director, a controller three days a week, Exact Online, a CRM and an Excel sheet that is “the real dashboard”. The company is fictional, the situations are real: we run into them again and again.

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Sound familiar?

  • The monthly figures only arrive on the 20th, when the decision has already been taken.
  • Three versions of the truth: the sales Excel sheet, the accounts, and the gut feeling.
  • The dashboard that was built once and never updated again.
  • The two-hour meeting without a decision or an action list.
  • The cash-flow surprise: a VAT payment or a late payer just not spotted.
  • The quote margin that is only known at actual costing, if that ever happens.
  • KPIs that are defined differently by each department.
  • All reporting runs through one person: the director is the bottleneck.

What usually runs here

The software we come across here most often. It does not have to go; we build around it and in between.

Excel the one true reporting toolExact Online / AFAS / Twinfield accounting, dashboardsVisionplanner accountant dashboards, forecastsPower BI dashboards on Microsoft dataLooker Studio free dashboardsHubSpot / Pipedrive pipeline and quotesTeams / Zoom / Meet meetingsCopilot / Fireflies / tl;dv meeting reportsSimplicate / Teamleader projects, hours, margins
// the same working day, twice

A day in management & leadership: now and next

On the left, the day as it usually runs now. On the right, the same day once the dull parts are automated and AI does the groundwork. Watch what changes: not the people, but where their time goes.

// how it goes nowWithout AI
  1. 07:30DirectorCoffee, phone: 62 emails, three “got a minute to call?”. He doesn’t know how the month is going; the controller comes in on Thursday.
  2. 09:00Management teamWeekly meeting: two hours. The sales figures come from yesterday’s Excel sheet, the revenue from last week’s Exact. Discussion about which number is right. No decision.
  3. 11:00ControllerWorks on the monthly report: export, paste, correct. Ready on the 20th.
  4. 13:30DirectorQuote for a major customer: price on gut feeling, margin unknown. “We’ll see when we do the actual costing.”
  5. 15:00BankNobody had noticed next week’s VAT payment. Two large debtors are paying late. Some juggling required.
  6. 16:30DirectorReads the report of last week’s meeting. Three action points, no owner. Two haven’t been done yet.
  7. 21:00DirectorLaptop open. Tries to work out in Excel why the margin is dropping.
// how it will goWith AI and automation
  1. 07:30DirectorThe weekly briefing is in his inbox: revenue up to yesterday, margin per product group, open quotes, cash flow six weeks ahead, three things that need attention. Five minutes of reading.
  2. 09:00Management teamWeekly meeting: 45 minutes. One dashboard, the same figures for everyone, refreshed overnight from Exact and the CRM. Two decisions, with owner and date.
  3. 11:00ControllerNo more pasting. Works on the question of why the margin on product group B is dropping, with today’s figures.
  4. 13:30DirectorQuote: the system shows the margin and actual costing of comparable projects. A price he can back up, in ten minutes.
  5. 15:00BankThe cash-flow forecast had already shown the VAT payment and the late payers three weeks ago. Reminders have been sent; nothing had to be juggled.
  6. 16:30DirectorThe report with decisions and actions was in the task system an hour after the meeting, with an owner. Two of the three have been done.
  7. 21:00DirectorLaptop closed. The margin question is with the controller, with an answer tomorrow.

Where AI makes the difference here

Per use case: what the automation does, what a person keeps doing, and whether it is proven or still promising. We say which one honestly.

01proven

Dashboards from the systems you already have

Revenue, margin, pipeline, hours and cash flow from Exact, AFAS, your CRM and time tracking, refreshed daily. One truth.

Still human: defines the KPIs and reads them.

Working more efficiently
02proven

Cash flow six weeks ahead

Outstanding items, payment behaviour, fixed costs, VAT and payroll in one forecast with scenarios.

Still human: assesses scenarios and decides; AI does not predict the market, it only extrapolates your history.

Better security Working more efficiently
03proven

The weekly briefing

AI summarises email, reports and figures into what needs attention; in your inbox on Monday morning.

Still human: decides what happens with it.

Saving time
04proven

Meetings with a decision and an owner

Purpose and agenda beforehand; AI report as a draft with decisions and actions in the task system.

Still human: checks and steers.

Working more efficiently
05proven

Monitoring margin per quote

Actual costing automatically from hours and purchasing; with a new quote you see comparable projects and their real margin.

Still human: sets the price.

Working more efficiently Handling more with fewer people
06promising

Decision preparation

AI sets out options, assumptions and risks side by side and looks up the figures to go with them. Useful as preparation; not yet to be trusted as an oracle.

Still human: takes the decision and owns it.

Working more efficiently
11%
of revenue is paid late; companies with AI in payment management report fewer late payments. [1]
72%
of meetings are ineffective; 77% result in a follow-up meeting. [2]
60%
of AI projects without AI-ready data are abandoned. Garbage in, garbage out. [3]

Honestly: what AI does not do here

  • AI doesn’t predict the economy, a competitor or a customer who walks away. It extrapolates your history. That’s useful, not a crystal ball.
  • A dashboard is only as good as the definitions behind it. If sales and finance count “revenue” differently, AI only shows that faster.
  • Most AI pilots deliver no measurable result. That’s why we start with one question you ask every week, not with a platform.
  • You don’t solve the director-as-bottleneck with a tool, but with decisions that are allowed to sit with others. The tool does make that easier.

The objections we hear — and whether we can close them off

We looked them up and heard them from clients. For each objection we say whether it is really solvable, partly solvable, or a risk that stays and that you accept knowingly.

Can it be closed off: partly. That’s the right conclusion to the wrong question. Six in ten AI projects without clean data are abandoned; that’s why step one with us is always a data audit and one source per metric. AI helps with the clean-up, but doesn’t replace it.

// how we start, the first thirty days
  1. 01Week 1: core session with management and the controller; we count how many days it takes before a decision has the right figures, and which KPIs are defined twice.
  2. 02Weeks 1 and 2: one source per metric (revenue, margin, hours); a dashboard that reads daily from Exact/AFAS and the CRM.
  3. 03Weeks 2 and 3: cash-flow forecast six weeks ahead with reminders to debtors; weekly briefing on Monday morning.
  4. 04Weeks 3 and 4: meeting reports with decisions and actions in the task system; actual costing per project.
  5. 05Week 4: measure. Days until monthly figures (target: 1), hours of reporting work, meeting time. Only then decision preparation with AI.
// what it costs and how it works

First the free AI scan, then a core session on your floor (a half-day of 4 hours, €596 excl. VAT and travel costs) with a core report and an honest go/no-go. We build on a project basis with fixed hours: €110 per hour for straightforward work, €165 for complex development.

More hours only with your written approval. If we cannot deliver, you pay nothing for what was not delivered.

AI scan & strategy Process automation Custom software & integrations

Want to know what this means for your management & leadership?

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// which industries this matters most in
Construction & fit-out Transport & logistics Professional services Accountants & bookkeeping firms Lawyers & legal services Healthcare & social care
// from our insights
Where do you start with AI in your business?

Most businesses start with the tool and then get stuck. It is better to start with one piece of work that comes back every week and nobody enjoys.

What does AI automation really cost?

The build costs are usually the easiest part of the bill. The surprises are in the clean-up beforehand, the monthly usage and the maintenance afterwards.

// other departments
Administration & finance Sales & quotes Purchasing & stock Production & workshop Construction & installation Field service & maintenance Transport planning & administration Marketing & content Customer service & communication HR & recruitment Planning, scheduling & events IT, security & data
// sources
  1. Intrum, European Payment Report 2025 (2025)
  2. Atlassian, Workplace Woes: Meetings (2024)
  3. Gartner, Lack of AI-ready data puts AI projects at risk (2025)
  4. Exact MKB Barometer 2025 (69% use data, 42% want to be more data-driven) (2025)
  5. Virtualization Review (MIT NANDA), The GenAI Divide: State of AI in Business 2025 (2025)
  6. Microsoft WorkLab, Breaking down the infinite workday (2025)
  7. Accountant.nl, Dutch DPA sounds the alarm over data breaches caused by AI (2025)