Services
Demand forecasting, inventory optimization and production scheduling.
Everything hangs off the data. A forecast is only as good as the sales history feeding it. A buy plan is only as good as the forecast. A production schedule is only as good as the buy plan. Get the data right and the other three get easier.
Start anywhere below.
Demand Forecasting
Most forecasts tell you what they think will happen. Ours also tells you how wrong it has been lately.
Underneath, it does what any good forecast does: it looks at how much you normally sell, whether that is climbing or falling, and how your year is shaped. Then it does the part most tools skip. It checks its own recent misses, works out which way it has been leaning, and corrects the next month before the month is over. A normal forecast finds out it was wrong a quarter later. This one finds out now.
Below is the platform itself. No login, nothing switched off. Start on Dashboard for forecast versus actuals with rolling accuracy and bias. Top-Down and Bottom-Up build a forecast from opposite directions, New SKUs handles products with no history, and BOM Demand blows it through to components. First load takes a few seconds while the server wakes.
Purchasing & Inventory Optimization
Hold less stock and still have what people order. Both, not one at the cost of the other.
Almost every business we meet has too much of the wrong thing and not enough of the right thing at the same time. That is not a buying problem, it is that nobody ever set the rules: how much cover each item needs, and when to order more. Below, decide how often you want to have things in stock and how much cash you can put into it, and watch which orders survive.
How often a customer gets exactly what they ordered. 100% is ruinously expensive.
What suppliers actually deliver against what the system assumes.
The constraint nobody models. When it binds, something has to give.
| SKU | Fcst / mo | Safety | ROP | Buy | Spend | Status |
|---|
What the last point of service costs
Average inventory at every half-point of service level. Flat to about 95%, then a wall.
Where the money goes
Green is fully funded and teal is trimmed by the cash ceiling.
Manufacturing & Production Scheduling
The order you build things in is worth hours a day.
Every time the line switches from one job to the next, somebody cleans something, swaps something, and waits. Run similar jobs together and most of that disappears. The catch is that ten jobs can be run in three million different orders, so planners fall back on habit, and habit is expensive. Drag the jobs below into whatever order you like, then let the computer try to beat you.
Sequence · drag to reorder
Keyboard: focus a job, hold Alt with up or down.
The production block
Synthetic data, not a client schedule. The optimizer runs nearest-neighbour from every start, then 2-opt. It is the same approach as the scheduler we built in Python for a door manufacturer, which runs against their live order book daily and took on-time delivery from 54% to 97%.
Data Management & Analytics
This is the center. Everything above reads from it.
We pull the numbers out of every system you run: the ERP, the till, the spreadsheets somebody keeps on their desktop. Then we make them agree with each other and keep them in one place, set up under your account rather than ours. If you fire us on a Friday, everything still runs on Monday.
Hover anything for detail. Click any bar, slice or bubble and every other panel filters to it.
Total sales over time
Monthly, with a twelve-month moving average
Mix by product family
Flips to channel once a family is selected
Top selling products
Within the current selection
Growing
Year over year
| SKU | 12 mo | YoY | Change |
|---|
Declining
Year over year
| SKU | 12 mo | YoY | Change |
|---|
Stock position
Cover against demand, sized by inventory value
Where the inventory sits
Cycle stock versus safety stock, at cost
Projected cover
What to do about it
Thinnest cover first
| SKU | Fcst / mo | Cover | ROP | Buy | Spend | Position |
|---|
D3 running in your browser on generated data. In an engagement this is Power BI or Tableau against your warehouse, but the rule is the same: a few views tied to recurring decisions, and every visual filters every other one.
Seen enough?
Tell us which of these sounds like your business, or where the data runs out before it answers the question. Scoping a full project plan costs you nothing.