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Measuring Training

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'Not everything that can be counted counts, and not everything that counts can be ... beneficial effect persisting for 18km beyond the start of Chevrons ... – PowerPoint PPT presentation

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Title: Measuring Training


1
Measuring Training
  • Jonathan Kettleborough Corollis
  • Phil Green Optimum Learning

2
  • Not everything that can be counted counts, and
    not everything that counts can be counted
  • Albert Einstein
  • (1879 - 1955) Genius

3
Our route for today
  • what do organisations measure
  • what do you measure
  • what do others measure
  • gathering data
  • analysing data
  • presenting data
  • overcoming resistance
  • summary and conclusions

4
Different strokes
  • different organisations measure different things
  • happy customers
  • coffee serves
  • safety record
  • show/discuss examples
  • what gets measured gets done

5
Exercise
  • think of the most successful piece of training
    you were involved with
  • what was good about it
  • what were your criteria for success

6
Success criteria
  • think about your criteria for success. Was it
  • time bound
  • financial
  • prestige
  • etc.
  • discuss with colleagues

7
Point of view
  • consider the last exercise
  • was your criteria the same as others
  • if not, why not
  • did your role/position influence your criteria
  • what criteria might a CEO have

8
Gathering data
  • why are you actually gathering the data
  • what data should you gather
  • who should you gather it for
  • who pays for the data to be gathered
  • whats the benefit of gathering it
  • need to consider
  • the expected results
  • who collects the data
  • at what point, and
  • how its done

9
Analysing evaluating data
  • OK, so we have a load of data whats next?
  • consider what you do with the data you have
  • does it make you do things differently in the
    future
  • evaluation is an imperfect science
  • discuss some of the tools and approaches
  • what are the issues
  • what about statistical spin of results

10
Presenting data
  • points to consider
  • who are you presenting it to
  • how do they normally receive data
  • spreadsheets
  • company newspaper
  • Press releases
  • what impact are you trying to make
  • separation of hard and soft data
  • use of imagery to reinforce your message

11
Learning about Skiing
  • Kinetic and Potential Energy
  • Friction
  • Acceleration and Deceleration
  • Gravity
  • Newton's Laws
  • not the same as learning how to ski!

12
Some examples
  • An ideal performance solution but what would
    you measure?

13
Results
  • vast majority of drivers
  • understood purpose of markings
  • felt they were helpful
  • used them without difficulty
  • application test data
  • best for relatively low flow conditions if flows
    are high drivers unlikely to respond
  • drivers in lane with chevrons should be able to
    see signs explaining them
  • marks at 40m intervals encourage drivers to adopt
    2 second gap at 70mph

14
Measurable outcomes
  • 15 reduction in drivers with gap lt1 second
  • 5 reduction in drivers with gap gt 2 seconds
  • improvement in close-following behaviour in
    unmarked (outside) lane
  • little change in vehicle speeds
  • statistically significant overall accident
    reduction of 56
  • beneficial effect persisting for 18km beyond the
    start of Chevrons
  • reduction of 40 in multi-vehicle accidents
  • even greater reduction in single vehicle accidents

15
Retrospective measures
  • measuring retrospectively against a different set
    of criteria is not a recipe for success!
  • its useful to know what you want to measure
    before you embark on the training
  • remember what gets measured, gets done!

16
Your measures
  • what sort of things get measured in your
    organisation
  • discuss
  • was it sales, IT, cultural harmonisation etc.
  • how does location change the measures e.g. sales
    offices, head office, support centres, call
    centres etc.
  • what gets measured may not matter!

17
Resistance
  • You may experience resistance when you try and
    measure results
  • youll need to be clear about the criteria
  • unfair tests wont get measures
  • are you measuring the individual or the
    organisation
  • are you measuring individuals against what they
    are normally measured against
  • criteria for measurement is key

18
Conclusion
  • general wrap up and conclusions

19
Contact details
  • Jonathan t 01606 892011
  • Kettleborough m 07812163004
  • e jonathan_at_corollis.com
  • Phil t 0114 281 6727
  • Green m 0797 023 8641
  • e philgreen_at_optimum-learning.ltd.uk
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