Implementing your research project: Writing your research report

Judith Barton

The final blog in this series looks at writing up your coaching research project in the ‘appropriate style’ (see section 3, below).

1. The writing process
For many people, the prospect of writing their research report can be quite intimidating!  It can help to remember that basically what you are doing is to tell a story:
•    what you planned to do (and why);
•    what you actually did (and how);
•    what you found out;
•    and what these findings mean.

One way to make it more manageable is to write a draft of sections of your report as you go along.  One of the joys of computerised word-processing is the ease with which you can add notes, edit, cut and paste text and generally update your work as required without the major effort of physical re-writing, so use your word-processing functions to maximum benefit.  When I get ‘stuck’ on what to write, I put down a ‘stream of consciousness’ (relevant to the topic!) just to get started and then go back with a metaphorical ‘red pencil’ to get rid of or re-organise or re-write the text until I get to the point of being reasonably confident that I am communicating what I want to communicate.

So, once you have defined and clarified your research topic and question(s) write a draft of that section in continuous prose which can be incorporated, with any editing, into the final report. Similarly with the other components of your project, draft the report as you go along.  At the end, you can go back through to ensure that the whole ‘hangs together’, is consistent and accurate and tells the story you set out to sell.

It is much easier to write your references as you go along – using a tool such as Reference Manager can be exceptionally helpful, but will probably only be worth the cost and time if you are writing a lengthy report with pages full of references.  Getting to the end of writing your report and then trying to ensure that you have all references in the text also listed at the end and in the same format will be a time-consuming and tedious job – time and energy that could be better spent on writing, editing and generally polishing your work.

A key feature of writing your report is creating titles – the title of the full report and the title of each chapter or section.  These should be sufficiently interesting to attract the attention of the potential reader, whilst remaining sufficiently serious to reflect the nature of your work and the effort you have put into it.

The final task(s) of writing up your research is very careful proof-reading. It can be quite difficult to spot your own typing mistakes, so asking a friend or colleague to double-check can be helpful. Make sure that proper names are spelt correctly and that the grammar is both correct and appropriate to the audience for whom you are writing.

2.  What should you include in your research report?
The key components of a research report are: a description of the aims and objectives of the research; the methods used to collect and analyse data; the findings and conclusions. Depending on the size of the project and the audience of the report, research reports may contain:
•    An introduction – describe/explain what you are going to write about (best left until last, when you have completed your research and know what it is you are writing about!);
•    Aims - describe what you set out to do, what your objectives were;
•    Rationale - your reasons for carrying out the research and the reason why the research is important – this latter may involve a detailed review of the literature;
•    Methodology – how you collected your data and why you choose a particular method/methods of data collection; and the methods you used to analyse your data once collected; information about yourself or the team of people involved in carrying out the research project and their skills/expertise and knowledge may be relevant here;
•    Findings (i) – be clear about any limitations of the data you collected – response rates, statistical issues, limitations to the results – e.g. can you generalise from the data or is it a ‘snapshot in time’?; may a differential response rate from different groups of people bias the results, and how you will compensate for this in your analysis or the conclusions you draw for the data?;
•    Findings (ii) – the results of your data analysis;
•    Conclusions – drawing out the implications of your findings for coaching theory and/or practice;
•    Recommendations – if relevant to your research – these may be directed towards those who purchase coaching services; leaders/managers in organisations where coaching is a preferred management style; practising coaches, internal or external; those running their own coaching practice. 
•    References.
•    Appendices – again, if necessary.

3.  The appropriate style.
By this, I mean that you should think about the intended audience of your research report and adjust your writing style accordingly.  For an academic audience you should retain academic language and ensure that references are always made when referring to another’s work (published or unpublished), including your own (cross-reference within the report or other work you have written). Referencing should follow an accepted standard, such as the Harvard method.  Academic work requires a high level of detail and is likely to be quite lengthy. For academic work a higher proportion of passive verbs, with longer sentences and paragraphs will be acceptable.  If you plan to submit your research report for publication in an academic journal, an ‘abstract’ will be required – this is a summary of the key points of your research written in an academic style.

A management report is likely to be shorter and ‘punchier’ with less detail (although sufficient to support your conclusions and recommendations) and less research jargon, with more focus on the practical, management implications of the research.  A short summary of research methods and analysis is appropriate, with reference to where greater detail can be found.  Greater use of bullet points, short sentences and active verbs are more appropriate for a management report.  Recommendations may be particularly relevant to a management report.

For a report for the professional reader you should avoid research jargon as far as possible or, if the use of technical language is essential to communicate your points, a clear explanation or definition should be provided when technical terms are first used. Again, this type of report is likely to include a summary of your methods and findings rather than all the detail, with the focus on the implications for professional practice - your findings, conclusions, and where relevant, recommendations.

It is of course quite possible that you could write up your research in more than one style.  Again, word-processing makes it a great deal easier to write up the same project for two or three audiences.

4. And finally…
This is the last in this series of blogs – which I hope you have found informative and useful. The key text with much more detail and technical information which I have used for some of the ideas in these blogs is: M Saunders, P Lewis, A Thornhill (2000) Research Methods for Business Studies 2nd edition. 

Implementing your research project: analysing your data

Judith Barton, Director of Coaching

Once you have collected your information you will need to analyse it. In this blog I will be looking at two broad methods of data analysis – quantitative (numbers) and qualitative (words). Then I will comment on drawing conclusions from your data.

1.  Quantitative data analysis.
First, to say that sophisticated statistical analysis should probably best be left to sophisticated statisticians! If your research project includes large data sets based on random samples looking for proof of generalisable ‘cause and effect’ relationships or statistical modelling this is probably best done with the advice of a specialist in this area - who will already have advised you on your research question, research design and methodology. 

Quantitative analysis is basically counting – how many, how much, how often, how long – and aims to be logical, and objective – although this depends on how objectively your data are collected, coded and allocated. In this section I will be providing a brief overview of some types of numerical data and look at simpler analysis which would be relevant for organisational or survey data such as sickness absence rates, staff turnover, customer complaints, sales figures, educational achievement of students or health outcomes for patients.  The focus will be on ‘descriptive statistics’ and graphical presentation of data. 

Numerical data can either be ‘categorical’ or ‘quantifiable’.

Categorical data can be classified into groups and a number allocated – for example, gender.  In this case, you could allocate ‘1’ to subjects who are Male, and ‘2’ to subjects who are Female. Once these values have been allocated to each subject correctly, data can be inputted into a simple spreadsheet such as Excel and the proportion of male to female identified. Analysis can then describe, say, the proportion of male to female participants who take up the offer of coaching training in an organisation or the proportion of male to females who are being or have been coached.  

Quantifiable numbers are real numerical values which can be ranked in order – continuous data can take any point in a range, for example length of service in an organisation; discrete data can be measured precisely, for example number of clients coached or number of customers served.
The first step towards completing your data analysis is coding. This may be done as part of the data collection, as when a survey asks you to select an answer which most applies to you, e.g. what age are you? Are, more usually, which of a predetermined age group do you belong to?  Coding simply refers to allocating a single number to a variable or factor – this might be the actual number, e.g. actual income of a subject; or a number allocated to a grouping of income.  For the former, an example of income might be £21,500; and of an income group, £20,000 - £29, 999 – to which the actual income would be allocated in this example. It is helpful to use established, published coding frames where available and relevant – e.g. classification of ethnic status, social class or marital status as coded by the Office of Population Censuses and Survey. 

Once coded the next step is to input your data into the computer and software programme of your choice.  Once entered, it is crucial to check for errors – in either the coding or the data entry.  This can be very time-consuming, but deciding not to undertake it can be dangerous, as errors (there are always errors!) will feed through into the analysis and findings, and from there lead you to false conclusions.

The first stage of analysis is usually about exploring the data you have collected and looking for findings of interest. For evaluating the effectiveness of coaching in an organisation you may wish to look at the distribution of different age groups compared to the benefit they perceive they have received from coaching, or the number of coaching sessions research subjects have received compared to the number of days lost to sickness/absence. The easiest way to start understanding the data is through the use of tables and, particularly, diagrams such as bar charts (to show the frequency of occurrences from highest to lowest), pie charts (to show the proportion of distribution of variables) or scattergrams (to show the relationship between two variables).  Graphic presentation of data can now easily and speedily be generated by everyday software. Descriptive statistics enable numerical descriptions and comparisons of variables, and focus on the spread of the variable across your subjects; and the tendency of the data to group towards the centre.  Examples of the latter include the mode (the value that occurs most frequently), the mean or average, and the median (which represents the middle value).  Measures of the spread of data include for example: the range (difference between the highest and lowest); the inter-quartile range (the difference within 50% of values) and the standard deviation (the extent to which data differ from the average).  

A word of warning about the ease in which numerical data can be analysed by spreadsheets such as ‘Excel’.  This software (and others like it) can readily be used to present tables, graphs of various sorts and quite complex statistical analyses. Be aware that, although this software can produce sophisticated graphs and statistics these are only as valid and useful as the quality of data input and the correctness of the function requested of the programme – or, the risk is, as the acronym GIGO has it, Garbage In, Garbage Out, even if it is beautifully presented! 

Reference: M Saunders, P Lewis, A Thornhill (2000) Research Methods for Business Studies 2nd edition, Chapter 11.  This includes more technical detail and more information about statistical analysis.

2. Qualitative data analysis
Many of us are more comfortable with words than numbers so there is a tendency to see qualitative data analysis as easy – which is not necessarily the case.  You still need to take care that you can ensure that your conclusions are based on the evidence you have collected. 

A common method of qualitative data analysis is ‘categorisation’ – or coding - which breaks down the data into meaningful and related parts (categories) allowing you to identify key themes from different sources (e.g. interview transcripts or policy documents). These categories enable you to manage your data and bring together concepts and ideas from the data. Coding can be done manually (post-it notes, cutting and pasting from interview transcripts) or electronically (creating a coding table or using computer software designed for qualitative analysis). Coding is an iterative process and is usually done as you go along, after each interview for example, checking all the while that your themes or concepts accurately reflect the data you have collected.  Re-analysing earlier interview data in the light of categories or themes emerging from later interviews can enhance and deepen your understanding of the data and its significance; or you may wish to re-catergorise earlier interviews in the light of understanding developed in the later interviews. It can also be helpful for you to keep a record of ideas and any other information such as the context, individuals involved or non-verbal cues as you go along. Keeping summaries of key points from each interview can also help you to identify emerging themes and categories.

It is probably more usual to use an inductive approach to analysing qualitative data – that is, you seek to build up theory and understanding derived from and grounded in the data you collect (rather than a deductive approach which involves starting with a theory or hypothesis then collecting data to test the theory’s validity).  This inductive approach allows your research participants to ‘drive’ the development of theory and avoids the risk that their views would be forced into a theory or interpretation which they themselves would disavow.  It can be useful to quantify qualitative data – i.e to count the number of times a particular event, issue or theme occurs in the course of your data collection and present this as a table.

3. Drawing conclusions from your data analysis.
Whichever type of data you collect and analyse, great care must be taken to ensure that the conclusions you draw from the data are sound and accurate.  Review your data and analysis carefully and check that you have relevant and appropriate evidence for your conclusions to the research. For example, a small survey of staff who have been on a coaching programme is unlikely to ‘prove (or disprove) that coaching is effective’.  It may however indicate, that for those staff involved, they perceived that their engagement and motivation at work, and hence their performance, were improved.  This could, however, inform a larger study, with measurable outcomes to formally evaluate the effectiveness of coaching in the workplace. Alternatively, a large questionnaire survey could provide evidence of effectiveness of coaching but would be less likely to explore the staff’s perceptions and experiences of coaching and being coached.


Reference: M Saunders, P Lewis, A Thornhill (2000) Research Methods for Business Studies 2nd edition, Chapter 12.  This also includes more technical detail and information.

Implementing your research project - collecting your data

Judith Barton

In this blog I will be looking at collecting information for your research project.  This will include three common methods of collecting data – the survey questionnaire; the focus group; and individual interviews. 

1.  Survey questionnaire.  With questionnaires every effort needs to be made to persuade people to respond – firstly by providing an explanation of why it is important, how completing the question will help – improve services, working life – and secondly by making it as easy as possible for respondents to provide meaningful answers. This is especially important when respondents are answering questions on their own – such as a postal or online survey.  The value of piloting a questionnaire cannot be overstated as a means of ensuring that you have not got any questions that are ambiguous, incomplete or unanswerable. (Piloting a questionnaire means asking a small number of people to complete it and identify any difficulties in answering questions and recording the answers.  You are not interested in the actual answers, only in the ease of use of the questionnaire and the meaningfulness of the answers). 

There are some key principles involved in designing a postal/online questionnaire, which include:

Clarity of instructions – for example, do you want respondents to tick a box? to circle an answer? or to ‘delete as necessary’.  If instructions are not crystal clear, you may end up with returned questionnaires that you cannot analyse without difficulty; that have gaps where respondents could not work out what you wanted; or a low response rate because respondents found it all too difficult and time-consuming.

Clarity of questions – for example, do not include two questions in one. This is relevant to questions asking ‘free text’ responses, such as “please write down how easy was it to establish rapport with your and did your coachee engage in the coaching process?” This should be two questions – the first about rapport; and the second about coachee engagement.  Where ‘multiple choice’ questions are involved there are two points of particular importance.  First, ensure that all possible options are included – often, a question will not be relevant to a particular respondent or not all respondents will know an answer, so the options of ‘not applicable’ and ‘not known’ are essential where this may be the case.  This is particularly significant in online questionnaires, where the inability to provide an answer to one question often prevents the respondent from moving on to the next one. Secondly, make sure that your options are mutually exclusive – for example, if you are asking respondents to allocate themselves to an age range.  ’25-35 years’ and ’35-45 years’ is not helpful for those who are 35 years old!  This could better be classified as ’26-35 years’ and ‘36-45 years’, or ’25-34 years’ and ‘35-44 years’.  The same principles apply to income range; length of time in employment; or any other numerical ranges.  

 2. In-depth interview topic guide. This guidance is intended for face-to-face or telephone interviews. 

The interview process. The first requirement for carrying out an in-depth interview on any subject is to establish rapport and agree the ‘contract’ – how the interview will be carried out, any ‘ground rules’, anonymisation or pseudonimisation, confidentiality (and the limits to confidentiality) – sounds familiar?! Many of the skills and processes of the coaching conversation are equally applicable to the in-depth research interview – except that the purpose is different. In the research interview, the purpose is to collect accurate and meaningful information, relevant to the research topic and question.  So, deep listening, questioning, probing and summarising skills are all central to carrying out a successful research interview.  

You may need to use some ‘closed’ questions for specific information – e.g. age group, length of time in this employment, status within the business/organisation.  But primarily the information you are seeking will be gleaned through ‘open’ questions – ‘how do you feel about …..?’, what do you think about ….?’, ‘tell me more about what happened when …….’  It is good practice to prepare and pilot an interview guide which simply lists the topics you wish to discuss without specifying the order and wording of questions – a particular topic might be covered at the beginning, middle or end of the process depending on the natural ‘flow’ of the interview. 

Recording the interview.  Another issue in common with coaching is recording the interview – the usual process is audio recording, which is transcribed and the interviewee asked to amend, edit or clarify and then confirm the accuracy of the transcript. This often raises issues of confidentiality, especially when a relatively small number of people are being interviewed who all work in the same, relatively small organisation or section/level of an organisation.  You need to be very clear about who will have access to the recording; how the information (recorded and written) will be securely stored; and when/how it will be destroyed.  Interviewees also need to know about how their information will be written up, and how you intend to protect their information.  This can be through using false names, initials or numbers to identify individuals; changing gender, age or using generic descriptions of role or status within the organisation.  Issues of confidentiality should be addressed at the very beginning and can be an important element of creating rapport and establishing trust. 

3. Focus groups

The process. Running a successful focus group needs an experienced and skilled facilitator, who is expert in ensuring that the group is a ‘safe place’ for all members to engage with the discussion, respond accurately, respect each other and their opinions/feelings, and all have the opportunity to contribute in the knowledge that their contribution will be taken seriously. These ‘ground rules’ need to be established at the beginning – and should be written down in the invitation to individuals to participate in the group. Again, these will be common themes to those accustomed to team coaching or group supervision.  Facilitation skills are key.  A topic guide to help you keep the ‘focus’ of the discussion is also crucial – this will also ensure that you do not forget to discuss all aspects of the research question. 

The skills of developing rapport, listening, questioning and summarising are required for focus groups as much as for in-depth interviews, with ‘managing’ the group an additional requirement. 

Recording. The discussion is usually audio-recorded, with the same provisos about confidentiality as the in-depth interview.  If for some reason you (or members of the group) prefer to have contemporaneous notes taken then you will need another person to do this – it is not reasonable to expect one person to facilitate the discussion and take notes. Generally, audio-recording is a more convenient method, providing that you can use adequate equipment and that all members of the group agree to the recording.  

The next blog in this series will look at analysing the information and drawing conclusions from it.

Reseraching your practice

Judith Barton, Director of Coaching&Mentoring

Once you have identified your research topic and refined your research question, the next stage is to decide on your design and methodology – what and how information you will collect to answer your question.  Once you have decided on these, a plan with SMART goals and a realistic timetable is necessary to ensure successful completion. 

Research Design

A key component of your question in determining the appropriate design is whether or not you want your results to be ‘generalisable’ – i.e. to apply to all similar research participants now and in the future; or are happy to find out what applies only to the people who actually participated in your project – a ‘snapshot in time’? The former will require statistical input to identify the sample size sufficient to answer your question; and the method of selection from all the possible participants in who you are interested (the sample)  - the method of randomisation. The latter is much more straightforward – the people in the organisation or setting of interest who you can approach and who agree to participate. 

The nature of the design and methodology will be determined primarily by your research question, but may also be influenced by time and resources available to you. You might ideally wish to generate results which can be generalised, but in the real world time, expertise and other resources may lead you towards a snapshot approach. 

For the purpose of this blog, I am concentrating on research which looks at effectiveness – particularly the effectiveness (or otherwise) of coaching and mentoring. This could focus on the impact on an organisation; a single individual; or a number of individuals.  Examples of research methods which look at effectiveness include experimental, observational, surveys, case studies, qualitative research.  

Experimental research requires that the ‘research subjects’ or participants receive an intervention which is expected to have an impact on them and/or their organisation; measurements are taken before and after the intervention; and the researcher can conclude whether the intervention ‘makes a difference’ to the things which are being measured. Examples of interventions include executive coaching with Board level directors; performance coaching with middle managers; mentoring with young people.  

The ‘gold standard’ for identifying whether an intervention achieves its desired outcome is the ‘randomised controlled trial’ (RCT) (as used in trials of clinical interventions such as new medicines). Briefly, this method involves at least two groups (those receiving the intervention, the ‘experimental’ group’) and the ‘control’ group (who do not receive the experimental intervention).  ‘Before’ and ‘after’ measurements from each group are compared. The two groups are matched for key indicators – e.g. age, gender, level of seniority in the organisation. The total numbers and the numbers in each group are determined by a statistical process, the power calculation.  Research participants are allocated to each group by a process of randomisation, which means that each individual has an equal chance of being allocated to either group. The processes of the power calculation and randomisation improve the likelihood that the results are genuine and can be generalised or happened by chance and only apply to the individuals included.  

RCTs clearly involve complex, expensive, and time consuming processes. Whilst new medications cannot legally be brought to market without proven safety and effectiveness, other types of intervention can be evaluated by less intensive methods – although the results will not be as robust. A more readily used ‘before’ and ‘after’ comparison, either without a control group or with an unmatched control group would be the cohort study – when a group of people are assessed before the intervention – e.g. a programme of executive coaching - and again after the intervention has been completed.  If used with a single organisation this approach could be described as a case study, although a full case study would also involve analysis of the organisational context as well as the impact of the coaching programme. If involving a single individual this would also be a case study, but would not give any information beyond the individual concerned. 

Research Methods

When looking at impact or effectiveness of coaching and mentoring, organisational and individual indicators can be used – for example the impact of management coaching on sickness absence rates and/or on retention and turnover figures; or the reported well-being and motivation of coachees before and after the programme.  This approach (using both quantitative and qualitative methods) is described as a ‘multi-method’ study, rather obviously because - it involves more than one method.  The quantitative information includes those mentioned above – absence rates, turnover, or productivity, which organisations will be collecting routinely.  Information about individuals will probably need to be collected specially by the researcher. This could be achieved through questionnaires, individual interviews or focus groups. Questionnaires may be used to collect quantitative information (e.g. age, gender, ethnicity; or answers to ‘multiple choice’ questions) about participants and qualitative information with their attitudes and behaviour in respect of either giving or receiving the coaching.   

So, what do I mean by ‘quantitative’ information and ‘qualitative’ information? Fundamentally, the former is expressed in numbers; and the latter in language. Quantitative information is expressed through numbers – it may be rates, inputs such as hours worked or outputs such as the number of goods produced or services completed; or numbers may be allocated to linguistic answers (e.g. Male = 1; Female = 2; LGBTI = 3). Qualitative methods are especially useful for researching people’s feelings and thoughts about processes and allow you to probe more deeply into matters which could be quite sensitive.  Some examples of the main methods for collecting information are provided below, with some of the strengths and weaknesses identified. 

1 Questionnaire surveys – these are usually self-completed without you being present to offer clarification to the respondent.  These may be administered as paper documents or, more commonly now, online.  The benefits of questionnaires include the fact that they relatively inexpensive and easy to send out.  Weaknesses include the need to phrase questions so that there is absolutely no ambiguity about precisely what information is being requested and encouraging people to complete and return the questions.  Ease of analysis will depend on how well the questions are phrased and whether the answers requested are numerical or linguistic. A higher number of participants can be approached for the same resource input as interviews or focus groups.

2. Organisational information such as sickness absence rates and staff turnover are usually collected routinely – as a researcher you will need to be able to access this information. Some thought should be given to how this information will be analysed. 

3.  Semi-structured and structured interviews are often used to collect ‘feelings’ information from people, for example about how they experienced the process of coaching or being coached.  These have the advantage of the researcher being present so that the interviewee(s) can seek clarification and the researcher can probe more deeply into the answers provided. If you are wanting to ask about more sensitive and personal issues (e.g. career plans) interviews will have an advantage over focus groups in which people may not be willing to divulge their personal plans and ambitions.  These methods have the advantage of sharing some skills with coaching – e.g. building rapport, questioning and deep listening.  

4.  Focus groups can be useful in that the opinions a larger number of people can be collected at one session; and members of the group may ‘spark’ ideas off each other. Using group discussion will require some additional skills to individual interviews – e.g facilitating the discussion, ensuring all members of the group have opportunity to contribute, similar to team coaching.

There are some similarities in the skills required for research and for coaching, although the purpose is different – to collect information which will enable you to draw conclusions about the question you originally asked. 

Research Planning

As with any complex set of activities, successful achievements depends on a clear and realistic plan.  The precise details will of course depend on the specific details of the research project.  The following example of a plan is based on a case study approach to a research project which will evaluate the effectiveness of introducing a programme of coaching into an organisation.  The organisational plan is to provide Executive Coaching training to Board directors; and Performance Coaching to senior and middle managers. The middle managers will be trained in two consecutive cohorts – the cohort to be trained first will be the ‘experimental’ group and the second will the ‘control group’. Both groups will be asked about their motivation and commitment to the organisation and their engagement.  The research has been commission by the L&D Lead and will be carried out by an external researcher.

Task	Person responsible	Deadline
Coach training programme and associated research agreed.	Board	Day 1
Draft pro forma for collecting information from organisational sources – policy for introducing coaching, procedures for introducing coaching; quantitative information on sickness absence, turnover.	Researcher	Week 4
Draft interview topic guide (for Directors) and focus group guide (for managers and coachees)	Researcher	Week 4
Draft letters for trainee coaches and coachees	Researcher	Week 4
[Identify Board Directors to be trained as coaches	L&D Lead	Week 4
[Identify middle managers to be trained as coaches and allocate them to members of the 1st and 2nd cohorts;	L&D Lead	Week 4
Identify staff to be coached by both Directors and managers.	L&D Lead	Week 4
Negotiate details of research with organisation (HR, L&D, CEO) to have access to organisational information; and to approach trainee coaches and coachees to invite them to participate in the research. Specifically issues to do with confidentiality.	Researcher	Week 4
Pilot and refine as necessary pro forma; topic guide; focus group guide.	Researcher	Week 5
Collect baseline organisational information	Researcher	Week 6
Carry out baseline interviews with Directors	Researcher	Week 7
Carry out baseline focus groups	Researcher	Week 7
Interview Directors	Researcher	Week 25
Hold focus groups with trainee coaches and cohort 2.	Researcher	Week 26
Collect organisational information after the coaching training is completed.	Researcher	Week 27
Analyse organisational information	Researcher	Week 27
Analyse Director interviews	Researcher	Week 28
Analyse focus group information	Researcher	Week 29
First draft of research report	Researcher	Week 35
Review and refine research report	Researcher	Week 38
Submit final report to commissioner	Researcher	Week 39
Present key findings to Board	Researcher	Week 40

This plan includes activities which need to be carried out by other parties, in italics.  The purpose of this is to highlight the dependence of researchers on others.  It may take longer for the organisation to complete its tasks; and there may be reasons (outside the researcher’s control) why the timescale may drift – it is essential to be prepared for this and to be realistic in your timescale and to build in some ‘slack’ so that the eventuality that there are delays it remains likely that you will complete the project on time. 

My next blog will look at issues of data collection and analysis.