Business · Intermediate
A recorded programme for managers who need to turn supply-chain, production and transport planning problems into precise requirements and controlled implementation.

Planning systems often begin with a sensible ambition: better production schedules, lower transport costs, fewer stockouts, more reliable delivery dates. Then the project meets reality. Different departments describe the same process in different ways, the data is incomplete, the vendor speaks in technical terms, and nobody is fully sure what the algorithm should optimize first.
For managers, the difficult part is rarely the software demo. It is the work before and after it: defining the problem, separating must-have constraints from nice-to-have wishes, writing requirements that a vendor can actually price, and keeping the implementation aligned with the original business goal. When those steps are weak, the system may be delivered on time and still fail in daily use.
This programme teaches the management side of planning optimization. It explains how optimization methods work in plain business language, how supply-chain, production, transport and material requirements planning fit together, and how to run a project from first diagnosis to acceptance testing. You do not need to become an algorithm developer. You need to ask better questions, define clearer requirements and control the project with evidence.
The lessons are recorded and self-paced. You work through short video lessons, worksheets and templates that help you apply the method to your own planning context, whether you are preparing a new system, rescuing a stalled initiative or assessing what a vendor has proposed.
By the end of the programme, you will have a practical management toolkit for planning optimization projects.
Describe mathematical programming, heuristics and combined methods without hiding behind jargon.
See where supply-chain, production, transport and material requirements planning connect.
Match a method to the task, data, constraints and planning horizon.
Describe processes, objects, goals, constraints, interfaces and expected outputs.
Make clear what the algorithm must respect and what it should improve first.
Reduce scope disputes by defining who provides data, rules, testing and acceptance.
Ask informed questions about competence, assumptions and implementation practice.
Check that the system works in your real conditions, not only in a demo.
Anticipate adoption risks and build a clearer communication and role plan.
The programme follows a four-stage logic that mirrors a well-run optimization project. First, analyse the task: understand the business goal, the constraints and the source data. Second, form recommendations: choose approaches, algorithms and solution options that fit the problem. Third, support implementation: keep the work with the vendor transparent, controlled and aligned with the original purpose. Fourth, define the result: measure the effect and make the improvement sustainable.
Each stage is broken into management actions. You learn how to turn a vague request such as “optimize production” into a set of planning objects, decision rules and measurable expectations. You also learn how to translate business language into algorithm language, so that technical specialists can respond to a precise brief instead of guessing what the business meant.
The course is vendor-neutral. It does not train you in one software product or promise a fixed financial result. It gives you a repeatable way to reason about planning systems, compare proposals and control the quality of what is delivered.

Six modules take you from planning architecture to acceptance testing and measurable improvement.

Every part of the programme is designed for practical use at work.
Six modules covering planning architecture, algorithms, vendor evaluation, specifications, implementation and change management.
Structured prompts for processes, objects, goals, constraints, interfaces and output formats.
Questions and criteria for assessing methodology, competence and implementation practice.
A simple way to connect a planning task with a suitable optimization approach.
A worksheet for separating customer and vendor duties before work begins.
Prompts for checking whether the solution works in your real data and operating conditions.
A place to capture your own planning context, risks, requirements and next actions.
Study when it suits you; the recorded material stays available after purchase.
The programme is delivered as recorded video lessons with supporting worksheets and templates. It is self-paced, so you can move through the modules in order or focus on the parts that match your current project. Most learners will need around two to three hours per week, but there is no fixed schedule and no live attendance requirement.
Each module combines explanation with a practical task. You might map your planning levels, draft a constraint list, evaluate a vendor proposal, write a section of a technical specification or prepare acceptance criteria. The templates are designed to be reused in real internal discussions, not filed away as theory.
There are no live sessions, individual consultations or personal coaching included. The value is in the recorded method, the structured materials and the ability to apply them at your own pace. If you want a clear management framework before your next planning project, this format keeps the focus on practical decisions.
You will be able to enter a planning optimization project with a clearer structure. Instead of starting from a vendor demo or a vague internal complaint, you can define the planning problem, describe the objects and constraints, and set out what the system must produce. That makes conversations with technical specialists more productive and reduces the risk of expensive rework.
You will also have a practical way to assess proposals. You can ask how a method handles your data, what assumptions it makes, how calculation time is controlled and who is responsible for testing. During implementation, you can use the templates to track scope, prepare acceptance checks and spot the point where a project is drifting from its original goal.
The course does not promise a specific cost saving or a fixed business result. It gives you the management knowledge to make better decisions, ask more precise questions and judge whether an optimization project is genuinely ready for your operation.
Most learners spend around two to three hours per week, including the short recorded lessons and worksheet tasks. The programme is self-paced, so you can slow down or revisit modules when a real project needs more attention.
No coding is required. The course explains optimization methods in business language. Basic familiarity with business processes, planning or project work is helpful, but the lessons start from the management questions rather than from mathematics.
After payment you receive access to the learning platform where the recorded lessons and downloadable materials are hosted. You can study from any device with an internet connection.
The programme consists of recorded video lessons, worksheets, templates and checklists. There are no live sessions or individual consultations included, so you can work through the material at your own pace.
The recorded lessons and supporting materials remain available after purchase. You can return to the modules when you start a new planning project or need to refresh a specific topic.
Yes. The course is covered by a 14-day refund policy. If the programme is not right for you, you can request a refund within 14 days of purchase.
No. The programme is vendor-neutral. It focuses on planning architecture, optimization methods, requirement writing, vendor evaluation and project control, so the knowledge applies across different systems and proposals.
Yes. The worksheets and templates are designed for practical use in internal planning discussions, vendor meetings, specification work and acceptance testing.
Build a management framework for supply-chain, production and transport planning optimization before your next project decision.