DC3-AI Performance Optimisation

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Bring us one problem to solve.

Tell us the problem and we talk it through with you, and tell you how superintelligence can solve it for you. For more than two decades we have turned problems into opportunities through numbers.

A free 45 minutes with Rassie

Brief us in five short questions, pick a time, and we come prepared with a first view of how to solve it.

Brief us and book a time How the call works

What we do

Four pillars, one second brain

How it fits together

A second brain for your business, built around it.

Not a platform built to scale across thousands of companies. One system that joins all your data, from marketing to the production floor, checks it, and tells you early what is changing.

How it works

Four steps

1

Review

We learn how your business actually runs and makes money.

2

Map

We find every source your numbers live in.

3

Audit & consolidate

Superintelligence checks each source against your books and joins them into one.

4

Report your way

Reports and alerts shaped around your business and its rhythm.

What an audit finds

1.5×

For every real sale it could see, the ad platform showed about one and a half.

Real sales in the books100
Sales the ad platform counted≈150

Found in client work: every order upgrade was reported to the platform again as a new sale. Your tracking tool, your ad platform and your books will each tell a different story until they are reconciled.

The difference

Built around your business, not built to scale

Typical tracking software

Built for thousands of companies

  • Trusts what the ad platform reports
  • Stops at revenue at checkout
  • Monthly, or charts you have to watch
  • Marketing data only
  • You work out why something moved
  • You take your providers’ reports on trust
DC3-AI

Built for one company: yours

  • Reconciled to your books, order by order
  • Down to margin and the bottom line
  • On your business’s own cycle
  • Accounts, ads, tracking, shop, service and production
  • Tested explanations, or an honest “unexplained”
  • Claims from agencies, staff and suppliers checked against the data

Your rhythm, not the calendar’s

Spot a problem weeks earlier

Illustration: a problem starts on day 10 of the month.

Monthly reporting · seen in one month’s pack, confirmed in the next
Our cycle · flagged at the first full cycle, confirmed one cycle later
Day 0Day 35Day 70
Problem startsFirst seenConfirmed, time to act

About three to four weeks sooner to a confirmed call, and so to action.

The watchers

Algorithms that know each product

Built for your product lines and back-tested on your own history before they go live. Each one learns what normal looks like for that product, ignores the noise, and speaks up early, on the way down and on the way up.

Slow leaks can cost more than big drops
ABCDnormal range for this product
The pace of your growth matters as much as the growth
EFif the faster pace had heldthe original pace

Illustrations: two products’ orders, cycle by cycle.

  • ASpike. A sudden jump or drop, flagged straight away.
  • BNoise. A dip inside this product’s normal range. Ignored, so nobody chases it.
  • CSlow leak, first sign. Still inside the normal range, but the trend watchers see the drift. Flagged as emerging.
  • DSlow leak, confirmed. More watchers agree. Confirmed, and translated into what it costs the bottom line.
  • EGrowth picking up. The climb gets steeper than its usual pace. Flagged early, so you can back what is working.
  • FGrowth slowing. Still growing, but less steeply. Read as easing, not decline, and flagged before it turns into a fall.
Spikes and dropsStep changesShort-term shiftsLong-term trends, five horizonsSlow leaksGrowth speeding upGrowth slowing downSlowing is not decliningBack-tested on your history

The watchers at work

The fortnightly tracker

Every product, every cycle, read against its own normal range. This is an excerpt from a real client tracker, with the products renamed and the figures scaled.

Watchmen · fortnightly trackerCycle 20 · day 12 of 14
every order counted once
Product3-cycle averagevs last year3-cycleCost per ordervs prior 6Read
Product Alpha217+15%$107 +24%Growing
Product Epsilon188+15%$93 +4%Growing
Product Gamma226+5%$121 +27%Easing
Product Delta326−5%$107 +21%Declining
Product Zeta103own trend$166 −5%Growing
All products, each order once1,463+15%$124 +7%Growing

Nine products, one page, every deviation explained

  • Product Delta: a slow leak of 5%, confirmed by the long-run watchers and held at “developing” because volume is still healthy
  • Product Gamma: still growing, but slower. Read as easing, not decline
  • Click any product for its detail: five trend horizons, what each watcher says, and the last nine cycles

Beyond marketing · the production floor

Production, reported every morning

The same second brain watches the work itself. For a repair workshop it joins the help desk, the payroll timesheets and the books, so the owner knows by 8am whether yesterday was a good day, and every customer can be given an honest date.

Daily output · Mon 5 Oct42 out, 51 orders in: a slow day
sent 08:00

Yesterday we completed 38 jobs and 4 warranty returns: 42 units out, against 51 new orders.

Good or not? No: new orders outran us (−9), and 38 jobs is 31% under a normal day lately (55).

Per technician hour: 0.59 jobs against a normal 0.66. One timesheet gap flagged by name.

Wait times: stagnant. 4 in 5 jobs finished within 10 working days. Falling behind: Theta, Delta, Epsilon.

One page before the workshop opens, a live dashboard behind it

  • Units out against orders in, and whether the backlog grew
  • Output per technician hour, so a short-staffed day is read fairly
  • Every technician’s scoreboard against a fixed target
  • The date to promise any customer, from the workshop’s own recent jobs

In practice

Catch deviations early, and the small leaks others miss

Customised algorithms and reporting, built around your business, make both possible. What the system has caught in client work:

−6%

A slow leak on a major product line: orders a few per cent below last year, too small to see week to week. The long-run watchers confirmed it and traced it to shopping-ad traffic.

1.5×

Sales over-counted by the ad platform, found and explained.

4 wks

A drop blamed on a competitor was a bid-strategy change made four weeks earlier.

What lands on your desk

Noise eliminated, interpreted for you

You don’t have to read the charts. Every report tells you what they mean.

Plain sentences, most important first, ending in one decision. The analytics stay underneath for anyone who wants them.

Example

Product Alpha: growing, about 15% ahead of last year. Nothing to do.

Product Delta: a slow leak, confirmed. Cost per order up a fifth. Review its shopping ads this week.

Everything else: inside its normal range. Ignore.

One decision: approve the shopping review for Product Delta.

See it in practice

The reports you would receive

From our client work: a US online business selling nine product lines, and the workshop that repairs them. Products are renamed Alpha to Iota, and every figure is scaled or changed so the business cannot be identified.

Who you work with

Customised reporting fit for billionaires, built around your business, tested in the real world

Rassie Cloete has built customised reporting for two decades, including the consolidated monthly report for the single-family office of a Forbes-listed billionaire, where he was vice-president for Treasury and Reporting. DC3 combines superintelligence with two decades of audit, family office and private equity experience.

Bring us one problem to solve

Book a free 45-minute call, or write to us directly.

rassie@dc3-ai.com

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