Dubai skyline at dusk with light trails on the highway

Solve what matters.Measure what changes.

We work closely with your leadership team and build a long-term partnership. Together we find the challenges hurting your bottom line and agree how success will be measured. Then we align on the value to create and the return on investment to aim for.

About

We find where your business loses money. Then we fix it and prove the gain.

IncrementumME is a business advisory firm based in the United Arab Emirates. We start where your business loses money and work backwards to the fix. With your leadership team, we turn each challenge into a problem statement with KPIs and a target return.

01

Business first, technology second

We work with your leadership team to identify opportunities to grow revenue, improve margins and reduce costs. Independent of software vendors, we are free to say when AI is the wrong answer.

02

Commercial judgement meets technical expertise

We combine senior business experience with expertise in building AI at scale, translating commercial challenges into practical solutions with a clear business case.

03

From advice to working solutions

We design, build and implement the solutions we recommend, taking responsibility for turning agreed priorities into technology that works in your business. If we can't show how fixing something lifts performance, we park it. An interesting AI use case still has to earn the spend.

04

Built around your systems and people

We connect your existing systems, data and workflows, designing with your teams to reduce routine work and support adoption while keeping people in control. That's why the result feels like theirs.

05

Intelligence that gives you an advantage

We build capabilities tailored to your business, turning your data into useful insights that help your people spot opportunities, make better decisions and act faster.

06

Measurable returns, lasting partnership

We agree success measures and target returns before we build, then track results and refine performance through a long-term partnership focused on financial value.

Growth flywheel

Challenges first. Then the technology that earns its place.

Our job is to create value. And value builds like a flywheel, with each part of the business feeding the next. Better value wins customers, and their revenue pays for the next improvement. Every turn makes the next one easier. When growth stalls, one link is usually dragging on the whole wheel. We find it and repair it with the right mix of business change and technology. Then the wheel picks up speed again.

Approach

From business challenge to measurable outcomes.

01 Understand

As your trusted advisor, we start with how your business really runs. We spend time with the leadership team and with the people on the floor, looking for where work slows down and which challenges cost money.

The question we answer: What is happening, and where could performance improve?

What you get: A shared list of the challenges that matter most.

02 Define

A broad challenge is hard to act on. We find out what is really going on, who it affects and why, then write it down as a problem statement. Everything after this step hangs on that page.

The question we answer: What exactly are we trying to fix?

What you get: A problem statement your team has signed off.

03 Measure

We agree the KPIs before anything is built, and we put a figure on what the challenge costs today. Then we set the return that would make fixing it worthwhile.

The question we answer: What change would count as success?

What you get: Agreed KPIs and a target return.

04 Prioritise

Some challenges need AI. More of them need a better process or a cleaner report. We rank each one by expected return and check that we can deliver it. A few won't make the cut, and we'll tell you which.

The question we answer: What return would justify the spend?

What you get: A business case, or a clear recommendation to stop.

05 Build

We build with the people who will use the result, around the way they work today. We pick the tools last, once the requirement is clear.

The question we answer: Can technology help here, and how?

What you get: A working system your team helped shape.

06 Deliver

We stay after launch, helping teams adopt the new way of working and fixing what breaks. The KPIs we agreed at the start keep being tracked. The engagement lasts as long as you need us.

The question we answer: Did the KPI improve, and did we deliver the return?

What you get: Measured value and ROI against the original business case.

Technology

Six technologies, combined to fit each challenge.

Every project starts with the challenge and the return it should deliver. Then we choose the technologies that get there, usually two or three of the six below working together.

01

Big data

Use cases:

  • Transaction history
  • Customer behaviour
  • Live monitoring
  • Sensor and IoT data
02

Data engineering

Use cases:

  • One version of the figures
  • ERP and CRM integration
  • Automated reporting
  • Data quality checks
03

Machine learning

Use cases:

  • Demand forecasting
  • Churn prediction
  • Anomaly detection
  • Lead and deal scoring
04

Operations research

Use cases:

  • Stock levels
  • Scheduling and routing
  • Workforce planning
  • Budget allocation
05

Generative AI

Use cases:

  • Document review
  • Contract extraction
  • Report drafting
  • Internal assistants
06

Automation

Use cases:

  • Procurement
  • Data re-keying
  • Reconciliations
  • Weekly report builds

Every model we build comes with the KPI it's meant to move.

Focus areas

Where could your business perform better?

Seven areas where we usually find the return. Select one to see the challenge we look for, what we change, the technology we use and how we measure it.

Better decisions

Faster calls on better figures.

The usual challenge
Figures arrive late, and different teams quote different numbers.
What we change
We put the numbers leaders need in one place. Decisions stop waiting for the monthly pack.
Technology we use
Data engineering for one source of figures; Big data for trend history; Machine learning for early signals
What we measure
Decision time, Forecast accuracy, Reporting time

Client intelligence

Use what your teams already know about clients.

The usual challenge
Client knowledge is scattered, and every client ends up with the same treatment.
What we change
Most firms hold far more client knowledge than they use. It sits in the CRM, in email threads, proposals, contracts and in the heads of relationship managers. We pull it together. Then teams can see which clients matter most and what each one values.
Technology we use
Data engineering for single client view; Generative AI for reading emails and contracts; Machine learning for churn and next offer
What we measure
Revenue per client, Retention, Share of wallet, Lifetime value, Conversion, Cost of acquisition

Cost optimisation

Lower cost without cutting what customers value.

The usual challenge
Costs creep up across teams, and nobody can say which spend pays back.
What we change
We trace where the money goes, process by process, and remove the spend that adds no value. Savings are tracked against a baseline your finance team agrees.
Technology we use
Big data for spend and process history; Operations research for scheduling and capacity; Automation for removing manual steps
What we measure
Unit cost, Cost to serve, Process time, Rework and errors

Growth

Money and people on the best opportunities.

The usual challenge
Budget and people are spread across too many bets.
What we change
We help teams spot openings earlier and back the ones with the strongest return.
Technology we use
Machine learning for lead and deal scoring; Operations research for budget allocation; Big data for customer behaviour
What we measure
Revenue growth, Margin, Pipeline velocity, Return on capital

Productivity

Hours back for the work that counts.

The usual challenge
Skilled people lose hours to re-keying and routine reports.
What we change
We take repetitive tasks off people's desks, from re-keying data to building the same report every week.
Technology we use
Automation for repetitive tasks; Generative AI for drafting and document extraction; Data engineering for no more re-keying
What we measure
Hours released, Cost per process, Output per employee, Cycle time

Risk

Earlier warning, quicker response.

The usual challenge
Problems come to light after the damage is done.
What we change
We flag emerging issues sooner, while there is still time to act on them.
Technology we use
Machine learning for anomaly detection; Big data for transaction monitoring; Data engineering for live exposure view
What we measure
Exceptions, Losses avoided, Response time, Risk exposure

Supply chain and logistics

The right stock in the right place.

The usual challenge
Too much stock in one place, too little in another.
What we change
Data on suppliers, purchasing, inventory and deliveries usually lives in separate systems, and decisions get made after the fact. We pick the one operational challenge worth fixing first and put a dirham figure on it. Then we agree what better looks like.
Technology we use
Machine learning for demand forecasting; Operations research for stock levels and routing; Data engineering for one view of supply
What we measure
Inventory levels, Working capital, Lead times, Delivery performance, Logistics cost, Downtime

Each area above ends in a number your finance team can check.

We work inside your team.

Your people are in the room from the first meeting. They help define the challenge and agree the KPIs. Later they test what we build, and when we step back they own it.

Two business partners shaking hands in a Dubai office

Contact

Start with the challenge.

Tell us the business challenge you want to address.
A partner will review it and reply within one working day.

What happens next

  1. 1
    A partner reads your challengeWe check the fit and choose the right people from our side.
  2. 2
    We scope it togetherA short call about how the business runs and what the challenge costs today.
  3. 3
    You get a clear starting pointA written problem statement, with the return worth aiming for.

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