1.5-day management workshop · No statistics degree required
Data-Driven Decision Making
Make the decision clearer before asking for more data. Learn to define the choice, test the evidence, expose assumptions and communicate why a recommendation is defensible.
- Duration
- 1.5 days · 12 hours
- Focus
- Questions, evidence and trade-offs
- Audience
- Managers and functional leaders
- Prerequisite
- No technical or statistics background
What is the Data-Driven Decision Making course?
Data-Driven Decision Making is a 12-hour practical workshop for managers and functional leaders. Participants use a repeatable decision frame, interrogate dashboards and charts, distinguish correlation from causal claims, identify cognitive and measurement bias, test scenarios with an approved AI assistant, and present a recommendation with evidence, uncertainty and trade-offs. No coding or formal statistics background is required. It is data-driven decision making training for the people who make the decisions, not a course for analysts. In short, it is a data-driven decision making course for managers.
Is this the right course for you or your team?
Who it is for
- Business managers and team leaders
- Finance, marketing, operations and HR heads
- Entrepreneurs and business owners
- Professionals moving into roles with greater decision responsibility
Situations it fits
- Meetings debate opinions because the decision is not framed
- Dashboards contain metrics without thresholds or action
- Correlation is presented as proof of cause
- AI produces fast options but their assumptions remain invisible
Prerequisites
- No technical or statistics background required
- Experience participating in workplace decisions
- Bring one representative decision or dashboard if attending a private programme
More data does not automatically produce a better decision
The workshop focuses on the habits that connect evidence to action.
“The question keeps changing”
Teams gather data before agreeing what choice is being made.
What you practise
Write the decision, options, criteria, constraints and deadline first.
“The dashboard looks persuasive”
Scale, denominator or aggregation choices distort the conclusion.
What you practise
Check source, definition, base rate, comparison and what the visual omits.
“Everyone sees what they expected”
Confirmation, recency and sunk-cost effects shape interpretation.
What you practise
Use a pre-mortem, counter-evidence prompt and independent review.
“AI generates a recommendation”
The answer blends evidence with invented assumptions.
What you practise
Provide verified inputs, request alternatives, and label every unsupported inference.
What participants will be able to do
Practise the skills below through course exercises, then check the results and explain how you would apply them to your work.
Frame a decision
State the choice, objective, options, criteria, constraints, owner and deadline.
Interrogate evidence
Check source, definitions, denominators, comparisons, uncertainty and missing information.
Recognise bias
Use structured countermeasures for confirmation, availability, anchoring, overconfidence and sunk-cost effects.
Test scenarios
Compare assumptions and sensitivities instead of presenting one forecast as certainty.
Use AI as a challenger
Generate options and counterarguments while keeping facts, assumptions and judgement separate.
Communicate the recommendation
Present the evidence, trade-off, uncertainty, action and review trigger concisely.
Applied to each team’s real work
Sales and marketing leaders
Territory, campaign, pricing, pipeline and customer decisions.
Operations leaders
Capacity, service, inventory, quality and process decisions.
Finance and strategy
Investment, budget, forecast and scenario choices.
HR and people leaders
Workforce planning, hiring, learning and policy decisions with privacy safeguards.
A decision workflow managers can reuse
The programme is tool-light by design; each capability produces a visible part of the final recommendation.
Decision framing
Core
Make the choice, criteria and constraint explicit.
Covers
- Decision statement
- Options and criteria
- Owner and deadline
What to verify
Would two readers agree on what is actually being decided?
Evidence review
Core
Judge whether the evidence supports the conclusion.
Covers
- Source and definition
- Comparison and base rate
- Uncertainty and omissions
What to verify
Can each material claim be traced to appropriate evidence?
Scenario and bias check
Core
Test assumptions and seek disconfirming evidence.
Covers
- Sensitivity analysis
- Pre-mortem
- Counterargument and review
What to verify
What evidence would change the recommendation?
1.5 days · 12 live hours
Detailed curriculum
3 modules, each pairing short instruction with guided practice. Sequence and examples can be adjusted after the training-needs discussion; the core outcomes stay the same.
Module 14 hours From problem to decision frame
- Choice, objective, options and criteria
- Questions before data requests
- Baseline, constraint and decision owner
Practical activityFrame a real management decision and receive peer challenge.
Module 24 hours Data literacy and analytical judgement
- Charts, denominators and comparisons
- Correlation, causal claims and base rates
- Cognitive bias and structured countermeasures
Practical activityAudit a dashboard and identify which claims it supports or cannot support.
Module 34 hours Scenarios, AI assistance and communication
- Sensitivity and scenario thinking
- AI for options, critique and synthesis
- Recommendation, uncertainty and review triggers
Practical activityPresent a data-backed recommendation with explicit assumptions and trade-offs.
Need a learning plan around your goals?
Share your experience, stack and goals. The proposal sets out the suitable modules.
Exercises and practical outputs
Participants apply each concept to one decision case across the day and a half.
How every module runs
Frame
Define the actual choice and its criteria.
Interrogate
Test the evidence, comparison and omissions.
Challenge
Run scenarios and seek disconfirming evidence.
Recommend
State the action, uncertainty and review trigger.
Exercises use realistic examples with no sensitive data. What participants make in the workshop is for practice and review, and anything they keep is their own working material.
Useful AI needs an owner, evidence and clear limits
Your people learn to build risk checks and review into the work itself, not to add a warning once a pilot is already live.
We use the NIST AI Risk Management Framework as an optional reference. It is not legal advice and does not replace your own legal, privacy, security and compliance review.
Name the task and the owner
Say what the task is, who it affects, who is responsible and which decisions the tool may or may not influence.
Protect information
Use only approved data and accounts. Follow your company’s rules on confidentiality, retention and access before you try anything.
Measure the real task
Pick quality, risk and take-up measures that fit the real task, and write down what you cannot measure yet.
Review and improve
Watch for failures, user feedback and changes, then tighten controls or stop using the tool when you need to.
How the course is tailored and delivered
We shape private training around how far along you are with AI, your approved tools, who decides what, the roles involved and the projects already under way.
From first conversation to evaluation
Agree the decision
Agree what your people must decide, design or put in place after the programme.
See where you are now
Look at roles, tools, policies, data limits and any AI or automation work already running.
Pick the examples
Choose realistic examples that are useful without exposing restricted information.
Agree the handover
Confirm the document, its owner, who reviews it and the next check-in after training.
Delivery formats
Public live-online cohort
Best for: Individuals joining a published batch with people from other companies
Live Zoom sessions, with notes, assignments, lab guides and three months of recordings on the Technovids LMS.
Private corporate programme
Best for: Teams that want examples from their own company and a shared piece of work
Live online or at your office. Scope, group size, materials, support and price are confirmed in writing.
Delivery modes
Live online
Trainer-led sessions with group work, shared documents and live review.
Onsite
Private training at your office, with the same exercises and review.
Discussion, practice and decisions—not a lecture marathon
Technovids training sessions with different groups. The photos do not name a client, course or result.
Photo 1 of 10: Hands-on session 
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Photo 5 of 10: Classroom session 
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Photo 7 of 10: Computer-lab session 
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Photo 9 of 10: Classroom session 
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Course details at a glance
The published course parameters on one page. Final scope, dates and fees are confirmed in the written proposal.
Discuss your training goals| Course | Data-Driven Decision Making |
|---|---|
| Duration | 12 live hours across 1.5 days or an agreed equivalent schedule |
| Audience | Managers, functional heads, entrepreneurs and decision owners |
| Prerequisite | No technical or statistics background required |
| Output | Decision frame, evidence review and presented recommendation |
| Delivery | Public live online; private live online or onsite |
Who may deliver this programme
We choose a trainer whose subject knowledge and teaching experience suit your group and the agreed scope.
Pankaj Rana
Co-founder & Lead Instructor, Technovids Consulting
Pankaj is a co-founder and the lead instructor at Technovids Consulting. His programme work spans practical AI adoption, AI engineering, evaluation, responsible production AI, data analytics and corporate learning design, with an emphasis on hands-on exercises connected to workplace tasks.
Expertise:
- Practical AI adoption
- Prompting and evaluation
- Responsible AI
- Corporate learning design
Junaid Khateeb
AI & Machine Learning Trainer, Strategist and Consultant
Junaid is an AI and machine-learning trainer, strategist and consultant with more than 22 years of training experience. His work combines enterprise AI education, business-centred adoption, responsible AI practices and applied solution design, helping professional audiences connect AI concepts to real organisational needs.
M.E. in Computer Engineering, specialising in Artificial Intelligence · author of programming books on Python, Java and C++
Expertise:
- Enterprise AI and ML training
- AI strategy and adoption
- Responsible AI
- Applied AI solution design
Pradeep Varadarajan
Technical Trainer & Curriculum Architect
Pradeep is a technical trainer and curriculum architect with more than 20 years of experience across enterprise technology, cloud infrastructure and advanced AI systems. He designs practitioner-focused programmes, labs and assessments covering AI, LLM systems, Python and machine learning, translating complex technical subjects into structured learning experiences.
Bachelor of Engineering in Electrical Engineering · instructor-led, virtual and blended delivery
Expertise:
- AI and LLM systems
- Curriculum architecture
- Python and machine learning
- Hands-on lab design
The trainer for your sessions is confirmed with the dates or in the written proposal.
To book a trainer for your team, call +91 86183 46384 or email [email protected].
Updated
Organisations we have trained, and participant perspectives
Feedback shared with permission, and clients who agreed to be named, show how we deliver. They are not a promise of any particular result.
Organisations we have delivered training for
Hands-on training for people and teams in AI, data, cloud, productivity and workplace skills.
Participant experiences across workplace roles
What people we trained found useful in their day-to-day work.
- Gauraw DeshmukhData Engineer · Capgemini
Technovids AI training was very practical and well structured. The sessions helped me understand how AI concepts can be applied in real data engineering and business workflows, instead of only learning theory. The trainer explained the topics clearly with relevant examples, which made the learning experience valuable and easy to follow.
- PriyanshaSoftware Developer
The AI training from Technovids helped me gain a better understanding of Generative AI, prompt engineering, and practical AI use cases for software development. The course was clear, interactive, and focused on real-world applications. It gave me confidence to explore AI tools more effectively in my work.
- Sidda RajuData Engineer
Technovids delivered the AI training in a very practical and industry-relevant way. As a data engineer, I found the examples and hands-on discussions useful for understanding how AI can improve data workflows, automation, and decision-making. The sessions were well planned and easy to understand.
- Akshat KabraData Engineer
The AI training program by Technovids was insightful and professionally delivered. It covered important AI concepts in a simple and practical manner, with examples that connected well with data and analytics use cases. The sessions helped me build a stronger foundation in applying AI in real business scenarios.
- MangeshSoftware Engineer · Siemens
Technovids conducted the AI training in a very effective and engaging manner. The sessions were practical, easy to follow, and focused on how AI can be used in real software engineering and business workflows. It was a valuable program for understanding the current direction of AI adoption in the industry.
- ReshuSoftware Developer
Technovids AI training was a very useful learning experience. The course explained AI concepts in a practical way and showed how developers can use AI tools to improve productivity, problem-solving, and application development. The trainer's approach was simple, clear, and focused on industry use cases.
Common questions before planning this course
Answers about the course as published. Your written proposal records any changes we agree, how it is delivered and the price.
Are public cohorts available for Data-Driven Decision Making?
Public batches run live online when dates are published. An enquiry records your interest. Your place is confirmed only when Technovids sends the batch schedule and enrolment terms in writing.
What does a public cohort include?
The Technovids LMS gives you notes, assignments, lab guides and recordings for three months after the batch. Live sessions run on Zoom.
Is a certificate included?
Learners who meet the completion requirements get a Technovids certificate with a unique ID you can check on the Technovids website. It is not a vendor certification.
What equipment or accounts do participants need?
Bring a suitable laptop and the accounts named in the batch details. Tool subscriptions, usage charges and paid API use are not included unless we say so in writing.
How much of the course is about AI?
AI is one part of the final module. The durable core is decision framing, evidence review, bias checks and scenario reasoning. Those methods remain useful regardless of which AI tool is available.
Is this a statistics course?
No. Participants learn the practical questions needed to interpret evidence and dashboards. The programme does not teach statistical formulas or analytical software.
Can a leadership team use its own decision case?
Yes in a private programme, provided the case can be discussed safely. Technovids can also use a sanitised or neutral version when details are sensitive.
Plan your next step with this course
Tell us whether you are enquiring for yourself or a team, which development tasks matter and what access you have. We will confirm suitable delivery options and commercial details in writing.
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