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Quest Training

Performance Analytics & Data-Driven Performance Management Training Course

Builds the skills to turn performance data into decisions through KPI analysis, trend and variance analysis, dashboards and root cause investigation.

KPI · Performance Management & KPIAll Levels#2862ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Quality Management & Operational ExcellenceCategories:Performance Management & KPI

Course Overview

Performance analytics enables organizations to transform operational and business data into actionable insights that improve decision-making, resource allocation, and organizational effectiveness. By combining performance indicators, analytical methods, and structured reporting, managers can identify performance trends, understand the factors affecting results, and make informed decisions that support strategic and operational objectives. This course focuses on applying analytical techniques to performance management, including data preparation, KPI analysis, trend identification, variance analysis, performance dashboards, and root cause investigation. Participants explore how to connect performance data with business objectives, distinguish meaningful patterns from isolated fluctuations, and use descriptive and diagnostic analytics to understand performance outcomes. The programme also addresses data quality, analytical interpretation, and the limitations that can affect performance-related decisions. Through practical exercises and business case studies, participants develop the skills to analyze performance datasets, interpret analytical findings, communicate insights to stakeholders, and translate results into measurable improvement initiatives. The course emphasizes evidence-based management, reliable performance reporting, and continuous monitoring to strengthen accountability and improve organizational performance.

Learning Objectives

  • Apply performance analytics methods to evaluate organizational and operational results.
  • Identify relevant data sources and assess data quality before analysis.
  • Analyze KPIs, performance trends, and deviations from established targets.
  • Apply descriptive and diagnostic analytics to understand performance outcomes.
  • Develop dashboards and reports that communicate performance insights clearly.
  • Identify relationships between operational activities and performance results.
  • Investigate performance gaps using structured root cause analysis.
  • Translate analytical findings into practical management decisions.
  • Establish performance monitoring routines supported by reliable data.
  • Develop data-driven improvement plans with measurable objectives and follow-up mechanisms.

Who Should Attend

Department managers and performance management leaders. Operations managers and supervisors. KPI and business performance analysts. Strategy and business planning professionals. Business intelligence and management reporting specialists. Quality management and continuous improvement professionals. Project and process managers responsible for performance outcomes. Professionals involved in data analysis, performance reporting, and operational decision-making.

Learning Outcomes

  • Structure performance data for consistent and meaningful analysis.
  • Evaluate the reliability, completeness, and relevance of performance datasets.
  • Analyze KPI trends, variations, and deviations from targets.
  • Distinguish descriptive, diagnostic, and predictive analytical approaches.
  • Interpret performance dashboards and identify significant patterns.
  • Investigate relationships between operational drivers and measured results.
  • Apply root cause analysis to explain recurring performance problems.
  • Communicate analytical findings through concise reports and visualizations.
  • Prioritize improvement opportunities based on evidence and business impact.
  • Establish a repeatable framework for data-driven performance monitoring and review.

Course Outline

Day 1

Performance Analytics Fundamentals and Data Preparation

  • The role of performance analytics in organizational management.
  • Connecting strategic objectives, operational goals, and performance indicators.
  • Understanding quantitative and qualitative performance data.
  • Identifying data sources, ownership, reporting frequency, and measurement definitions.
  • Assessing data accuracy, completeness, consistency, and reliability.
  • Preparing datasets for performance analysis and reporting.
  • Recognizing data limitations, misleading comparisons, and interpretation risks.
  • Practical Exercise: Review a sample performance dataset, identify data quality issues, and prepare a structured dataset for KPI analysis.
Day 2

KPI Analysis, Trend Identification, and Variance Assessment

  • Analyzing actual performance against targets and historical baselines.
  • Calculating absolute and percentage variances.
  • Identifying trends, recurring patterns, and significant fluctuations.
  • Comparing performance across departments, teams, periods, and operational units.
  • Applying descriptive statistics to summarize performance results.
  • Segmenting data to identify areas of strong and weak performance.
  • Distinguishing isolated deviations from persistent performance issues.
  • Practical Exercise: Analyze a monthly KPI dataset, calculate performance variances, identify key trends, and prioritize indicators requiring management attention.
Day 3

Performance Dashboards and Analytical Reporting

  • Principles of effective performance dashboard design.
  • Selecting appropriate charts, visualizations, and reporting formats.
  • Defining dashboard metrics, filters, thresholds, and reporting periods.
  • Designing management-level and operational-level performance reports.
  • Communicating performance status, trends, and exceptions clearly.
  • Using comparative analysis to support departmental and operational reviews.
  • Improving reporting relevance, readability, and decision-making value.
  • Practical Exercise: Develop a performance dashboard from a sample dataset and prepare a concise management report highlighting key findings and recommended actions.
Day 4

Diagnostic Analytics and Root Cause Investigation

  • Moving from performance measurement to performance explanation.
  • Identifying operational drivers that influence performance outcomes.
  • Applying diagnostic analysis to investigate performance gaps.
  • Using segmentation and comparative analysis to locate problem areas.
  • Applying the 5 Whys and fishbone diagram for root cause investigation.
  • Distinguishing correlation from causation when interpreting data.
  • Evaluating improvement opportunities based on evidence and operational impact.
  • Practical Exercise: Investigate a recurring performance problem using a simulated dataset, identify plausible root causes, and recommend evidence-based corrective actions.
Day 5

Data-Driven Decisions and Continuous Performance Improvement

  • Integrating performance analytics into management decision-making.
  • Translating analytical findings into measurable improvement initiatives.
  • Prioritizing actions according to impact, urgency, risk, and resource requirements.
  • Establishing performance review cycles and monitoring responsibilities.
  • Tracking corrective actions and measuring improvement outcomes.
  • Communicating analytical recommendations to management and stakeholders.
  • Developing a sustainable framework for data-driven performance management.
  • Practical Exercise: Prepare a data-driven performance improvement plan that defines priority KPIs, baseline values, improvement targets, accountable owners, and review milestones.

Upcoming Dates

Selected date

Baku · 8 – 12 Mar 2027 · Classroom

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CityDatesPrice per ParticipantEarly Bird
IstanbulScheduled
9 – 13 Nov 2026€4,700—
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JeddahScheduled
15 – 19 Nov 2026€4,200—
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KigaliScheduled
23 – 27 Nov 2026€5,100€4,590until 2 Nov
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ErbilScheduled
29 Nov – 3 Dec 2026€3,100€2,790until 9 Nov
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DubaiScheduled
29 Nov – 3 Dec 2026€4,400€3,960until 9 Nov
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Kuala LumpurScheduled
30 Nov – 4 Dec 2026€4,400€3,960until 9 Nov
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LisbonScheduled
7 – 11 Dec 2026€5,400€4,860until 16 Nov
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MakkahScheduled
14 – 18 Dec 2026€4,200€3,780until 23 Nov
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IstanbulScheduled
14 – 18 Dec 2026€4,700€4,230until 23 Nov
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MadinahScheduled
14 – 18 Dec 2026€4,200€3,780until 23 Nov
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ManamaScheduled
21 – 25 Dec 2026€4,700€4,230until 30 Nov
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MuscatScheduled
28 Dec 2026 – 1 Jan 2027€5,300€4,770until 7 Dec
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OnlineScheduled
3 – 7 Jan 2027€1,700€1,530until 14 Dec
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JeddahScheduled
10 – 14 Jan 2027€4,200€3,780until 21 Dec
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RiyadhScheduled
11 – 15 Jan 2027€4,200€3,780until 21 Dec
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SalalahScheduled
18 – 22 Jan 2027€5,300€4,770until 28 Dec
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Sharm El-SheikhScheduled
25 – 29 Jan 2027€4,300€3,870until 4 Jan
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SingaporeScheduled
25 – 29 Jan 2027€6,700€6,030until 4 Jan
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TrabzonScheduled
1 – 5 Feb 2027€4,700€4,230until 11 Jan
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KigaliScheduled
1 – 5 Feb 2027€5,100€4,590until 11 Jan
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AbujaScheduled
8 – 12 Feb 2027€5,100€4,590until 18 Jan
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AccraScheduled
15 – 19 Feb 2027€5,100€4,590until 25 Jan
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AmmanScheduled
21 – 25 Feb 2027€3,100€2,790until 1 Feb
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Kuala LumpurScheduled
22 – 26 Feb 2027€4,400€3,960until 1 Feb
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AmsterdamScheduled
1 – 5 Mar 2027€5,400€4,860until 8 Feb
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BakuScheduled
8 – 12 Mar 2027€4,800€4,320until 15 Feb
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BarcelonaScheduled
15 – 19 Mar 2027€5,400€4,860until 22 Feb
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BangkokScheduled
15 – 19 Mar 2027€6,100€5,490until 22 Feb
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LisbonScheduled
15 – 19 Mar 2027€5,400€4,860until 22 Feb
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BeirutScheduled
21 – 25 Mar 2027€4,000€3,600until 1 Mar
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Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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