Spreadsheets and manual rules become risky
The decision depends on many interacting factors and the consequence of a poor plan is operationally or financially visible.
Decision support for operational planning
Better capacity, resource and scenario decisions.
Spacelytics models complex decisions in manufacturing, logistics and distribution when spreadsheets, ERP or standard software do not capture all relevant criteria, constraints and scenarios.
We first prove that the model can improve the decision. Specialised software is built only when that decision needs to be repeated.
Manufacturing / logistics / distribution / COO / operations / supply chain
Where we fit
Too important for Excel. Too company-specific for standard software.
This is where Spacelytics fits: the decision is important enough for manual rules to become risky, yet company-specific enough that a standard module leaves important constraints unresolved.
ERP, WMS or TMS misses the specific decision logic
The system records transactions well but does not answer a non-standard question about capacity, allocation, scenarios or trade-offs.
The challenge is analytical, not only software engineering
The interface is not the hardest part. The objective, constraints, trade-offs and validation logic must be formulated first.
A major transformation programme would be disproportionate
The problem is valuable enough for a specialist engagement without requiring a multi-year enterprise programme.
Types of decisions we improve
Operational decisions with explicit constraints and visible consequences.
Spacelytics is most useful when an important decision repeats, relevant data exists, and the effects of a weak plan can be observed through capacity, cost, service, deadlines or investment outcomes.
Capacity and resources
How much capacity is needed and how machines, people, space, budget or other scarce resources should be allocated.
Manufacturing and logistics
How to align demand, resources, flows, warehouses and operating rules that standard systems do not optimise together.
Scenarios and investment decisions
How to compare expansion, CapEx, configurations and future scenarios when demand and operating conditions are uncertain.
What the client buys
You are not buying a method. You are buying a better decision.
Capacity study
A clear view of constraints, bottlenecks and how the system behaves under different levels of demand.
Resource plan
A structured allocation decision across scarce resources, objectives and operating rules.
Scenario and feasibility model
A comparison of options, assumptions and investment paths before the decision is implemented in the real system.
Decision-support application
A focused tool for repeating a validated decision when users need to change inputs, scenarios and priorities.
Engagement path
From a bounded problem to an operational tool.
We do not begin by building a large application. Each next stage exists only if the previous stage shows that the problem and model have business value.
01
Decision & Modelling Sprint
A fixed-scope starting engagement. We clarify the decision, current process, objective, constraints, data and value case. The output is a decision map, model design and a clear recommendation on whether a PoV makes sense.
02
Analytical Proof of Value
A limited model using real or representative data. We compare the baseline with alternative scenarios, test sensitivity and determine whether the model creates practical value.
03
Optimisation or simulation engagement
We develop the full model, data flow, scenarios, validation and recommendations for the defined operational problem.
04
Decision-support application
Only when users need to repeat the same decision does the analytical engine receive a focused interface and become part of the operational workflow.
05
Model support and evolution
The model evolves when data, process rules, constraints, scenarios or the way the company makes the decision changes.
Demonstration cases
See the decision, not just the methodology.
Demonstration cases use realistic synthetic data to show the problem, constraints, analysis and the concrete difference in the decision.
Available case
How should scarce stock be allocated?
Allocation across minimums, profitability and business priorities.
Open case
Available case
Who should go to which job?
Service scheduling across locations, skills and total travel.
Open case
Available case
Second shift, outsourcing or new equipment?
Investment decision across capacity, scenarios, cost and flexibility.
Open casePartner-led delivery
A specialist analytical engine behind your project.
For ERP implementers, systems integrators, BI/data teams and software companies, Spacelytics can take ownership of problem formulation, optimisation, simulation and decision-support logic when the standard stack does not solve the non-standard requirement.
For partnersExplainability where it matters
XAIOR helps make the result understandable and verifiable.
The analytical engine remains authoritative for calculation. XAIOR is used selectively to translate results into understandable trade-offs, sensitivities and reasons that matter to the human decision owner.
See methodologyStart here
Is this decision worth modelling?
Describe the decision, how it is made today, which constraints are missing from the current system and what happens when the plan is poor. That is enough to assess whether a Sprint or Analytical Proof of Value makes sense.