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10 COMMON
EVALUATION MISTAKES
by Melvyn Tan
L I N E C O N S U LT I N G . C O M
QUESTION?
What are these
common mistakes and
how do you avoid them?
TOP 10 COMMON MISTAKES
1. Not back by right data/information
2. Not consistent
3. Not structured
4. Too structured
5. Lack of documentation
6. Lack of in-depth analysis
7. No improvements identified
8. Not feedforward
9. Over-reliance on hard data
10. Over-reliance on supplementary data
Data and information
• A set of valid and reliable data and
information is required
• Apart from hard data, use
supplementary data
• Using supplementary evidences alone
TOP 10 COMMON MISTAKES
Structured approach
• Lack of consistency
• Lack of a structured approach
• Too structured – one size fits all
• Does not translate to future plans
TOP 10 COMMON MISTAKES
Best Practices & Improvements
• Lack of in-depth analysis
• Sub-standard improvements
• Lack of proper documentation
TOP 10 COMMON MISTAKES
HOW TO AVOID THEM
Mistakes WhatTo Do
Data and
Information
• Valid and reliable data
• Hard and supplementary data
• Avoid supplementary data alone
Structured
Approach
• Consistency
• Well-defined process
• Feedforward to future plans
Best Practice &
Improvements
• In-depth analysis
• Sources of improvements
• Proper documentation
SIGN UP AT NO CHARGE
LINECONSULTING.COM

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10 Common Mistakes When Conducting Evaluation (How You Can Avoid Them)

  • 1. 10 COMMON EVALUATION MISTAKES by Melvyn Tan L I N E C O N S U LT I N G . C O M
  • 2. QUESTION? What are these common mistakes and how do you avoid them?
  • 3. TOP 10 COMMON MISTAKES 1. Not back by right data/information 2. Not consistent 3. Not structured 4. Too structured 5. Lack of documentation 6. Lack of in-depth analysis 7. No improvements identified 8. Not feedforward 9. Over-reliance on hard data 10. Over-reliance on supplementary data
  • 4. Data and information • A set of valid and reliable data and information is required • Apart from hard data, use supplementary data • Using supplementary evidences alone TOP 10 COMMON MISTAKES
  • 5. Structured approach • Lack of consistency • Lack of a structured approach • Too structured – one size fits all • Does not translate to future plans TOP 10 COMMON MISTAKES
  • 6. Best Practices & Improvements • Lack of in-depth analysis • Sub-standard improvements • Lack of proper documentation TOP 10 COMMON MISTAKES
  • 7. HOW TO AVOID THEM Mistakes WhatTo Do Data and Information • Valid and reliable data • Hard and supplementary data • Avoid supplementary data alone Structured Approach • Consistency • Well-defined process • Feedforward to future plans Best Practice & Improvements • In-depth analysis • Sources of improvements • Proper documentation
  • 8. SIGN UP AT NO CHARGE LINECONSULTING.COM

Editor's Notes

  1. To start things off, let’s look at the definition of “evaluation”. There are several definitions but I’d like to start with the one from EFQM (or European Foundation for Quality Management). Their definition is:
  2. So, what must we do when conducting an evaluation? No matter what tools you use or which process/approach you adopt, just remember these are the three key areas to pay attention to: Monitoring & Performance: you need a set of activity indicators to help you monitor the implementation of the planned approaches You also need to have a set of corresponding performance indicators to inform you whether the program/process is performing up to expectations Learning: You need to make sense of the information gathered and knowledge gleaned from the analysis. Based on what the analysis is, you need to know what’s working and what’s not working – and as a pro tip, how to highlight what’s working as a best practice of your organization Improvements: at the end of the day, evaluation is to help us improve, to help us become better, to help us go from good to great. So, what are the improvements? Are these incremental improvements – ie baby steps, or are these breakthrough improvements – ie those that will enable you to leap-frog and go beyond just the 5% increment.
  3. According to EFQM, the definition is defined as such. Here’s a few keywords that I’d like us to focus on: Monitoring, analysis, and refine