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

Benchmarking

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

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

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

The Strategy Pyramid

Before setting targets and goals it is important that these are aligned to strategies that support your organisational goals. In this module;
 - Understand your organisational goals
 - See how to balance your strategies
 - Learn how to align the right metrics and targets to your strategies

Root Cause Analysis

Root cause analysis is a core skill for analysts and forecasters but is something that few of us do well.  If we want to predict or shape the future it is vital that we understand the past. In this webinar we will explore:

- Why do we need root cause analysis
- How do we ensure we are asking the right questions
- Common Mistakes
- Use of technology to support root cause analysis

Descriptive Statistics - Part 1

It is easy to lie with statistics it is easier to lie without them. Whether we are an analyst or a decision maker a basic knowledge of statistical knowledge is essential to;

 - Understand the predictability, variability and repeatability of our data and allow us to separate the exceptions from the normal
 - Ensure we are giving the right message
 - Make sure we aren’t being mislead and are focussing on the normal rather than the rare exceptions

In this pre-recorded webinar module we the introduce the principles of statistics including, standard deviation, standard error and confidence levels. The accompanying excel workbook allows you to pause and play, and practice with real life examples at your own speed. 
 

Understanding & Managing Sample Bias

 - How to Identify Sample Bias & ensure you reduce the likelihood of bias
 - The impact on your data and insight validity from Sample Bias and the potential impact to your business
 - Common Sample Bias issues to look out for