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General Conclusions

Overall we found that the proportion of respondents who used each application was as follows:-

Application

% of respondents who use it

Average % use of functionality surveyed

Standard deviation of responses

Probable range of use of functionality by middle 68% of respondents

Word

98.25%

81.14%

17.54%

63.6% to 98.68%

Excel

85.88%

62.81%

22.04%

40.77% to 84.85%

PowerPoint

80.70%

76.95%

19.96%

56.99% to 96.91%

Outlook

74.85%

71.39%

19.52%

51.87% to 90.87%

 

Whilst Word scored highest overall in terms of ability to use, there was no direct correlation between number of users and ability to use the application.

We would also point out that, whilst there is no doubt that Microsoft Office dominates the office application market, given that this survey was branded as a “Microsoft Office survey” no other relevance can be attached to these percentages.

It would have been impossible to include every function that each of these applications has available to the user within the survey and we therefore sought to include a broad cross-section of functions that (in our opinion) would act as a useful guide to overall ability.

Given that each of these applications varies in complexity there were different numbers of individual functions analysed varying from 26 each for Outlook and PowerPoint, 28 for Word and 31 for Excel.

Each of the functions was scored from 1 to 5, where 1 indicates that the function is not used at all and 5 indicates that the user is fully competent in that function’s use.

Each of the applications had one or more functions that were not used by at least 70% of all respondents while at the other end of the scale there were many functions that were used almost universally (although only one function across all four applications was used by every single respondent who used the application concerned – the spell checker in Word!).

What is clear from the analysis is that those functions which are used most across all applications are the ones which are either accessed directly from icons (e.g. attaching files in Outlook, creating a bullet point list in Word or using auto-sum in Excel), launched by use of Hot Keys (e.g. F7 to spell check in Word) or accessed through a drop down menu command or right clicking the mouse (e.g. cut and paste in all applications). Obviously, all these commands can be actioned by a variety of methods and these examples are simply to highlight the relative simplicity of use of the relevant functions.

The least used functions tended to be those which are perceived to be ‘difficult’ (e.g. using the macro recorder – and this may also be avoided because of its association with viruses) or which require some element of preparation in order to use correctly (e.g. Table of Contents in Word, Pivot and Lookup Tables in Excel and creating Mail-Merges for email in Outlook). Paradoxically, it is these very functions that can give rise to the greatest time savings and increases in both efficiency and quality of management information which these applications can (and should) provide.

Within the analysis we have produced three main elements which, when taken together, highlight the quite profound variations in ability and usage. They are as follows:-

  • Average score of each function across all responders (including non-users)

- This gives an indication of how often (or rarely) the function is used by comparison with other functions

  • Average score of each function across users only

- This gives an indication of how well  (or badly) the function is used

  • Net Ability Score (NAS) of each function – achieved by deducting the total average score from the users average score

- This gives an indication as to how much better (or worse) the function is used when solely looking at regular users when compared to their use of other functions

As an example of this, let’s look at ‘rehearsal of timings’ in PowerPoint.

Across the whole population of respondents the average score for this is 3.02 which makes it the sixth least used function in the list. When we strip out the score for the non-users, the average for the users is 3.69 which is the fifth lowest in the list. This indicates that even those people who use this function are less adept at it than most of the other functions that they use. Finally, the NAS (the difference between all responders and users only) is 0.67 which is the thirteenth lowest score and which therefore indicates that even those who use it do not rate themselves very highly in the effectiveness of its use.

Compare this to ‘password protecting a file’. The average score for all responders was 2.78 (slightly less than ‘rehearsal of timings’) and for users only it scored 3.95, an increase (NAS) of 1.17 which is significantly higher than for ‘rehearsal of timings’. What can we learn from this?

The analysis indicates that while a lot of people use ‘rehearsal of timings’ they do not believe that they fully understand how best to use it. However, while similar numbers of people use ‘password protecting a file’ they are much more confident about their use of it.

From a training perspective this inexorably leads to the need for training across a whole population of users if it was felt desirable to increase awareness and ability of using ‘rehearsal of timings’ whereas if the need existed to train ‘password protecting a file’ the need would tend to reside with those who do not currently use this function.

Across the four applications there are some striking difference when comparing NAS. For Word, there is a broad agreement across all three sets of rankings, indicating that, in the main, where functions are commonly used, the user is reasonably confident in their use and that confidence tends to wane as usage decreases (i.e. people’s confidence is in fairly close ratio to the popularity of that function). Compare this with Excel, where there are consistently higher NAS scores. This indicates that where people do use specific functions they are very confident in their use (and the more complex and unusual the function the greater the distinction).

This strongly indicates two types of Excel user. Firstly there is the casual user who probably utilises a very small amount of its overall capability (using it as a simple flat database, for example) and then the ‘power’ user who is confident in the more complex functionality that Excel offers and is able to interrogate data (using D-functions, arrays, Pivot and lookup tables, for example) in a more complex and ultimately more useful manner.

Again, from a training perspective, this would tend to indicate a more ‘targeted’ approach to training, (possibly in conjunction with some numerical reasoning instruments to identify the most suitable personnel) in order to tap into the extremely powerful functionality that Excel has to offer.

Looking at the analysis for Outlook, the top four functions  relate specifically to email , which strongly suggests that the primary use of this application is as an email client rather than a method of assisting personal organisation.

At the less widely used end of the spectrum there is a clear distinction between the average scores and the scores for users, indicating that those few who use these more unusual functions of Outlook are confident (or very confident) in their use. Even at the well used end there are still some significant differences which indicate overall that people who use Outlook as a personal organiser tend to become relatively accomplished in its use, whereas those who only ever use it to access email are nervous to experiment further. From that point of view Outlook users are similar to (although not in such a pronounced way as) the users of Excel.

PowerPoint users on the other hand tend to be more like the users of Word. With one or two notable exceptions there is a broad agreement across all three measures which again indicates that the more popular functions are used confidently and the less popular functions less confidently. Again, like Word, this would indicate a broad brush approach to training, with the objective to raise overall ability across the whole population of users, rather than target specific users in the manner likely to be more effective for Outlook and Excel.

Read final section - specific conclusions