Operational Effectiveness & Real-Time Modules

Develop a deep understanding of Real-Time and establish key operating principles to be better prepared prior to the day, more effective on-the-day and capture understanding and learning.

Problem Statements & Hypotheses

Description: Using problem statements to generate fruitful hypotheses. Explore how to focus in the right way, becoming clear about the questions and problems you need to address.

Notes: This is a new module intended as part of the introduction to the Box set; How to Drive Improvement with Data & Insight but can also be an independent module

The Scientific Method and the Improvement Cycle

Description: Using the Scientific method to drive improvement. In this module we link the scientific method to the three phases of improvement, and get you started on the next of the practical exercises.
 
Notes
: This is a new module intended as part of the Box Set How to Drive Improvement with Data & Insight but can also be an independent module

Prioritising Opportunities for Improvement

Description: Explore how to focus on the right issues, how to create time to learn and how to balance proactive and reactive work, as analysts. 
 
Notes
: This is a new module intended as part of the Box Set How to Drive Improvement with Data & Insight but can also be an independent module

An Introduction to Accuracy & Confidence

Description: Understand the key statistical considerations that will ensure your conclusions are well founded and can drive confidence. The separate Statistical Confidence box set is an opportunity to drive this further.
 
Notes: This is a new module intended as part of the Box Set How to Drive Improvement with Data & Insight but can also be an independent module

Identifying Opportunities from Patterns & Exceptions

To innovate and be the best that we can we need to identify and exploit the best opportunities not just to improve but also to learn.

In this module we explore,
 - How to find the right opportunities
 - Creating time to learn and improve
 - Striking the right balance between proactive & reactive insight
 

Introduction to the Insight Cycle

Our best practice framework for data, analytics & insight, has the Scientific method at its heart and draws inspiration from methods that drove success with the planning framework last year. In this module we;   
 - Explore the scientific method
 - Introduce our new insight cycle
 - Share an exercise to identify the gaps and opportunity in your data, analytics and insight processes.

Descriptive Statistics - Part 2

Following on from Descriptive Statistics Part 1. In this module we look at applying these techniques to real life scenarios, you will receive exercises to complete before we talk you through the solutions.

Benchmarking

Hosted On 12th May 2020 By Ian Robertson

Benchmarking is important in understanding best practice, comparing ourselves with our competitors and becoming the best, but there are many pitfalls to avoid. In this module;
 - Hear the value of benchmarking
 - Learn how to avoid the common mistakes
 - Hear our top tips for benchmarking

Performance Records, Data Tables, Rigour and Governance

Hosted on 5th May 2020 by Ian Robertson

Clear documentation and structure can help us remove single points of failure, avoid arguments, ensure a single version of the truth and avoid duplicated work. In this module;
 - See how to create a data dictionary to ensure a single version of the truth
 - Learn techniques to ensure metrics are used to drive the right behaviours
 - Facilitate exception based reporting with agreed triggers

Target Typology

Hosted on 30th April 2020 by Ian Robertson

How do you avoid your targets being misunderstood, misinterpreted and misused. In this module;
 - Learn the different target types
 - Understand tolerances & triggers
 - Avoid common mistakes

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