About the Course
Organizations want process improvement they can prove, not vague claims about efficiency. In business process optimization through data analytics, that means showing how cycle time, rework, throughput, first-pass yield, and service levels change after intervention, using evidence aligned with performance management practice and process governance discipline. A credible approach often draws on process mapping, root cause analysis, KPI design, and methods such as Lean Six Sigma to connect operational waste to measurable outcomes.
This course turns fragmented analytics knowledge into a practical system for business process optimization through data analytics. You will practice current-state and future-state process mapping, define process KPIs, assess data quality, prioritize bottlenecks, build dashboard-ready metrics, and draft improvement actions that can survive day-to-day operational constraints. You will also be introduced to automation-supported workflow analysis and AI-assisted dashboard interpretation at an operational level, so you can use digital workflows without overpromising implementation depth. This course teaches you how to diagnose process performance with data, design measurable improvements, and communicate a defensible case for change to managers and executives.
Many teams work with incomplete data, legacy spreadsheets, scattered reporting, and competing operational priorities. This course is designed for professionals who must improve processes under those constraints while still producing usable diagnostics, KPIs, and action plans that leadership can review and act on.
Target Audience
This course is designed for professionals who need to analyse process performance, improve workflows, and present data-backed recommendations to operations and leadership teams.
- Operations analysts tracking process delays, rework, and throughput
- Business process managers owning cross-functional workflow performance
- Continuous improvement specialists using Lean Six Sigma tools
- Data analysts building KPI views for operational decision-making
- Process excellence managers diagnosing waste and variation
- Operational excellence leads coordinating improvement across functions
- Project managers delivering workflow change initiatives
- Transformation managers aligning process metrics to strategy
- Quality assurance analysts monitoring defects and handoff failures
- Finance business partners assessing cost leakage from inefficient processes
Course Objectives
This course equips you to plan, execute, and measure business process optimization through data analytics initiatives that improve flow, reduce waste, and strengthen management reporting.
- Assess current-state performance using SIPOC, value stream mapping, and process cycle efficiency metrics.
- Apply root cause analysis to process delays, defects, and bottlenecks using Pareto and 5 Whys.
- Design a current-state and future-state process map for a real operational workflow.
- Build a KPI dashboard using Excel or Power BI for process throughput and cycle time.
- Calculate baseline and post-improvement measures such as defect rate, first-pass yield, and rework.
- Evaluate process performance against Lean Six Sigma and continuous improvement criteria.
- Navigate stakeholder priorities and data-quality constraints when proposing workflow changes and controls.
- Synthesize findings into an action plan, executive summary, and improvement roadmap.
Requirements & Prerequisites
You should have working familiarity with business operations, process steps, and basic spreadsheet analysis. Prior exposure to KPI reporting, dashboard reading, or operational data is helpful, but coding is not required. You should bring a laptop and be prepared to work with Excel or Power BI for practical exercises, depending on your organization’s preferred workflow and the datasets provided during training.
Local Application and Business Return in your market
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn business process optimization through data analytics aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on calculation using cycle time, defect rate, and first-pass yield datasets.
- Scenario simulation on a delayed approval workflow with limited capacity and competing priorities.
- Diagnostic exercise using SIPOC, value stream mapping, and a root cause checklist.
- Stakeholder mapping of process owners, data custodians, and reporting recipients.
- Case analysis from manufacturing, shared services, healthcare operations, and logistics.
- Workshop to build a KPI dashboard and improvement action plan under time constraints.
- Reflection exercise comparing current process assumptions against performance benchmarks and waste indicators.
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Business Process Optimization through Data Analytics Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Skills Relevance
- Master cutting-edge analytics techniques vital for modern business landscapes.
- Transform data into actionable insights to drive process improvements.
- Learn to leverage big data for strategic decision-making and competitive advantage.
Expert Delivery
- Taught by industry leaders with real-world experience in Fortune 500 companies.
- Interactive sessions ensure practical understanding and immediate application.
- Gain exclusive access to proprietary analytics tools and frameworks.
Career Advancement
- Enhance your resume with skills in high demand across industries.
- Position yourself for promotions and leadership roles in operations and strategy.
- Connect with a network of professionals and experts in the field of data analytics.
Tools and platforms relevant to this field
Examples local teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
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Power BI MicrosoftUsed to build KPI dashboards, trend views, and operational scorecards that help teams monitor process performance and communicate improvement results.
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Tableau SalesforceUsed for interactive analytics and visual exploration of process data so analysts can spot bottlenecks, variation, and performance patterns quickly.
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SAP Signavio SAPUsed for process modeling, process mining, and workflow analysis to compare current-state and future-state process performance.
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Celonis CelonisUsed for process mining and execution management to reveal how work actually flows across systems and where delays or rework occur.
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Minitab Minitab, LLCUsed for statistical analysis, root-cause investigation, and quality improvement work where teams need to test variation and process stability.
