Data-Driven Decision Making for engineers
In an age of digital transformation, engineering decisions can no longer rely on intuition alone. This forward-looking course empowers engineers and technical leaders to harness data as a strategic asset—transforming complex datasets into clear insights and actionable decisions. Participants will learn how to build data-literate cultures, integrate analytics into daily operations, and drive measurable performance improvement across technical domains.
4700£
Target Audience
This course is specifically designed for:
Engineering managers and team leads
Project managers in technical environments
Operations and systems engineers
Plant, maintenance, and quality engineers
Emerging engineering leaders involved in performance, planning, or digitalization initiatives
Learning Objectives
By the end of this training, participants will be able to:
Gain confidence in interpreting and applying data to technical and operational decisions
Learn to identify the right metrics and KPIs for engineering contexts
Understand how to use data tools and visualization platforms to communicate insights
Improve root cause analysis and forecasting using data models
Develop a decision-making framework that integrates data, risk, and business outcomes
Module 1: M&A Strategy and Deal Rationale
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Identifying strategic drivers behind acquisitions and mergers
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Differentiating between horizontal, vertical, and conglomerate strategies
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Understanding market positioning, synergies, and growth scenarios
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Evaluating build vs. buy decisions
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Real-life case studies of successful and failed deals
Module 2: Target Identification and Due Diligence
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Establishing acquisition criteria and target screening methods
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Financial, operational, legal, and cultural due diligence best practices
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Red flags and risk mitigation strategies
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Conducting commercial assessments and strategic fit analysis
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Tools and templates for structured due diligence
Module 3: Valuation and Deal Structuring
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Methods of business valuation: DCF, multiples, precedent transactions
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Deal financing options: equity, debt, hybrids
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Structuring earn-outs, warranties, and indemnities
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Tax considerations and cross-border implications
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Negotiation tactics and value protection mechanisms
Module 4: Legal and Regulatory Framework
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Overview of legal steps in the M&A process
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Competition law, antitrust issues, and regulatory clearance
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Cross-border transaction complexities and compliance
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Drafting key legal documents: LOIs, term sheets, SPAs
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Managing external advisors: lawyers, auditors, investment banks
Module 5: Post-Merger Integration and Value Realization
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Cultural integration and change management
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Aligning leadership teams and operating models
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Synergy capture and KPI monitoring
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Communication strategies for internal and external stakeholders
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Lessons learned and post-deal review techniques
The role of data in engineering leadership and innovation
From gut feeling to evidence-based decisions: mindset shift
Data types, quality, and sources in technical environments
Understanding variability, causality, and correlation
Ethical and effective use of engineering data
Choosing meaningful KPIs: efficiency, quality, reliability, and cost
Building dashboards and monitoring tools for technical teams
Tracking asset performance, downtime, and OEE
Linking engineering metrics to strategic business goals
Avoiding vanity metrics and misaligned data use
Introduction to Excel, Power BI, and basic statistical tools
Data visualization principles for engineering scenarios
Trend, regression, and root cause analysis
Predictive maintenance and failure forecasting
Using data to improve preventive and corrective action plans
Framing technical problems and data-based decisions
Scenario analysis, simulation, and sensitivity testing
Balancing risk, time, cost, and performance
Real-time decision-making with streaming data
Human judgment vs. algorithmic input: when and how to trust data
Leading change in engineering organizations
Encouraging team-wide data literacy and ownership
Embedding data in continuous improvement and problem-solving
Communicating insights to stakeholders with clarity and impact
Aligning engineering and executive priorities through shared metrics
Approach
Industry-specific case studies and engineering data challenges
Group workshops and peer-reviewed decision-making exercises
Interactive dashboards, real-life problem-solving, and simulations
Personalized coaching on project-specific data applications
Templates, tools, and post-training implementation guides
Delivery Format
Duration
3, 5, 10 Days
Language
English, Spanish, German, Portuguese, French.
Wins – What You Gain
Make smarter, faster, and more defensible engineering decisions
Lead high-impact initiatives backed by data and insight
Enhance credibility with executive teams and cross-functional stakeholders
Reduce downtime, optimize resources, and improve ROI
Future-proof your engineering leadership in a data-driven world
Why Attend This Course
Approach
Industry-specific case studies and engineering data challenges
Group workshops and peer-reviewed decision-making exercises
Interactive dashboards, real-life problem-solving, and simulations
Personalized coaching on project-specific data applications
Templates, tools, and post-training implementation guides
