Build the internal skills to operate predictive analytics for decision support without permanent vendor dependency.
Predictive Analytics and Strategic Decision Support
A concise, decision-focused programme covering predictive analytics for decision support end to end.
📍 Tunis🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
The distance between a working prototype of predictive analytics for decision support and a system the business can depend on is where most budgets disappear. Most organisations now hold more data about decision support than they can actually act on. Teams frequently over-invest in documenting the practice within digital and data-driven work and under-invest in testing it. The course leaves participants able to diagnose weaknesses in predictive analytics for decision support before they become incidents. Benchmarking exercises repeatedly place this strand of digital and data-driven work among the areas with the widest performance spread. Content is organised around the decisions practitioners actually face in decision support, not around theory headings. The content is relevant to those who own predictive analytics for decision support and to those who are held accountable for its results. Exercises escalate in difficulty, ending with the ambiguous situations that make decision support hard in practice. Participants finish with a short, specific brief on the digital and data-driven work discipline ready to put in front of a decision maker.
Expected Learning Outcomes
Specify the data decision support depends on, where it originates and who is accountable for its quality.
Build the internal capability for predictive analytics for decision support rather than depending on external support indefinitely.
Align decision support with the wider objectives of the transformation programme rather than optimising it in isolation.
Define success criteria for predictive analytics for decision support in business terms before any technology is selected.
Sequence improvements to decision support so that each step makes the next one easier.
Assess whether predictive analytics for decision support should be built in-house, bought, or delivered through a partner.
Who Should Attend
Operations managers whose processes are changed by predictive analytics for decision support.
Programme managers coordinating delivery of decision support across teams.
Business analysts translating requirements for predictive analytics for decision support.
Technology and digital transformation managers leading decision support.
Public sector officials applying predictive analytics for decision support within a regulated framework.
Managers with direct responsibility for decision support within the transformation programme.
Course Modules
Predictive analytics for decision support: cost, licensing and total running expense
2 sessions · 8 pointsSession 1The pilot that actually settles the argument about predictive analytics for decision support
- Estimate compute and licensing cost for predictive analytics for decision support at expected and at peak load.
- Specify the fallback path when decision support is unavailable.
- Check that predictive analytics for decision support still works when volumes rise unexpectedly.
- Prepare the summary of decision support that senior management will read.
Session 2Explaining decision support to people whose jobs it changes
- Rehearse the briefing on predictive analytics for decision support that would follow an incident.
- Plan how decision support is versioned and how a bad release is rolled back.
- List the data sources predictive analytics for decision support consumes and confirm each has a named owner.
- Confirm the retention and deletion rules applied to data inside decision support.
Decision support: from pilot to production
2 sessions · 8 pointsSession 1Who owns decision support once the project team disbands
- Identify single points of dependency in predictive analytics for decision support and reduce them.
- Set the metrics that will show whether decision support is drifting from its intended behaviour.
- Establish who is informed, consulted and accountable in predictive analytics for decision support.
- Distinguish symptoms from causes when decision support underperforms.
Session 2Choosing a supplier for decision support without being captured
- Decide what will be stopped to create capacity for predictive analytics for decision support.
- Verify that decision support still performs when input volume doubles unexpectedly.
- Measure the current quality of the data feeding predictive analytics for decision support before assuming it is usable.
- Build the user briefing that explains what decision support does and does not decide.
Decision support: security, privacy and regulatory obligation
2 sessions · 8 pointsSession 1Building the method for decision support step by step
- Set out the decisions in predictive analytics for decision support that require sign-off and by whom.
- Map the handovers in decision support between functions and secure them.
- Test predictive analytics for decision support against edge cases drawn from real historical records.
- Design the pilot for decision support so that a negative result is still useful.
Session 2Getting other functions to support predictive analytics for decision support
- Arrange the handover of predictive analytics for decision support so capability survives staff changes.
- Name a single owner for each element of decision support.
- Define the service level predictive analytics for decision support must meet and what happens when it is missed.
- Close out actions on decision support rather than leaving them open indefinitely.
Decision support: vendor selection and avoiding lock-in
2 sessions · 8 pointsSession 1The paperwork for decision support that is actually needed
- Identify every system predictive analytics for decision support must read from or write to.
- Decide which legacy process decision support retires, and set the date.
- Estimate the resource predictive analytics for decision support requires to run as designed.
- Identify the skills the team lacks to operate decision support independently.
Session 2Sizing decision support honestly before committing budget
- Define the exit route from the supplier supporting predictive analytics for decision support.
- Define acceptance criteria for decision support in advance.
- Identify where judgement in predictive analytics for decision support is legitimate and where it is not.
- Agree the indicators that will show whether decision support is improving.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
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