CONSIDERATION ONE

Give yourself more time than you think you'll need

The data collection process often takes longer than you expect. Whilst we recommend, as a general rule, that you give yourself more time than you think you'll need to collect data, delays are not always a problem. Unless you have given yourself a very short timeframe to collect data, a delay of a week or two is often manageable. However, there are a number of issues that can cause significant delays. If the time you require to collect data is towards the longer end of the scale (e.g., 3-4 months for an undergraduate or master's level dissertation), these issues can become more acute. Significant delays in the data collection process cause a lot of stress for students, especially because you can quickly find yourself running out of time to do a proper job when it comes to the Data Analysis and Writing Up stages, both of which take a good deal of time in their own right. To be prepared for these issues (or at least aware of them), you need to consider (a) the nature of your research strategy and (b) potential issues around access:

• The nature of your research strategy

  Delays in data collection can be influenced by the nature of your research strategy (i.e., your choice of research design, research methods and sampling strategy), especially if you (a) are using repeated-measures designs, (b) have a small sample size, and (c) are using research methods that require additional permissions or are found to be lacking in the field.

  If you are using an experimental or quasi-experimental research design that requires measurements to be taken at more than one time point there can be a number of scenarios that lead to delays (i.e., these are known as repeated measures designs; for example, where a person's weight is measured at the start of the experiment, followed by a 4 week weight loss program, at the end of which the same person's weight is measured again). This problem is increased the more time points you have (i.e., the more times a participant has to be measured) and the smaller your sample size, unless your data collection takes place in a single instance (e.g., a laboratory experiment, structured observation, a face-to-face survey or structured interview on a single day). In these repeated-measured designs, it is not uncommon for: (a) participants to drop out between time points (e.g., they become unwell, loose interest, move job, are unable to maintain the requirements of a treatment, such as stopping smoking or a weight loss plan), which leads to a loss of data (i.e., you cannot use the data from the first time point when participants drop out); and (b) delays to occur between time points, sometimes caused by just a small number of participants not being able to complete a time point according to your pre-planned schedule (i.e., this can be especially acute if your data collection requires lab time or access to other equipment, rather than something like a structured interview, which is more easily rescheduled). Many doctoral students know this only too well, but unlike doctoral students, undergraduate and master's students do not have the flexibility in their schedules to account for long delays (i.e., for some doctoral students, the need to ensure that each participant completes all time points to maintain an acceptable sample size means that they can be prepared to wait weeks and even months, in some cases, to get all available data; time that undergraduates and master's students just don't have). Such problem can be partially alleviated by making sure you have sufficient data, which is a sampling issue; something we discuss in Consideration #3.
  
  Certain research methods can also require additional permissions, such as the use of covert structured observation where informed consent is rarely attained (i.e., in theory, informed consent could be attained after the fact, but this rarely happens, and brings with it other problems). Such research methods can cause delays because access can be harder to attain, or in the case of organisations, stopped during the research when observed participants become aware of the research and complain. However, it should be noted that only a small proportion of research methods required such additional permissions, and in practice, these should have already been granted through an Ethics Committee (i.e., when you perform certain types of research that may breach some of the basic ethical principles of research, there is generally a requirement for prior approval by an Ethics Committee). In some cases, the research methods (or more specifically, the measurement procedure you used) can be found to be lacking in the field, meaning that it doesn't work as well you expected (e.g., people feel that a survey is too long to complete such that a large proportion of people don't fill it out or skip sections). We discuss this further in terms of the need to be flexible (i.e., Consideration #2).

• Access issues

  Even though you will have identified potential issues relating to gaining access to data in STAGE SEVEN: Assessment point, there are many access-related issues that you simply cannot plan for, which can cause delays during the data collection process. Whilst delays can be caused when trying to gain access to human subjects, especially if your degree is in the human or biological sciences, as highlighted in the previous bullet, the risk of delays is often highest when access is required to one or more organisations.
  
  In the case of collecting data within organisations, we have known delays to arise from key people (i.e., usually gatekeepers who granted you access or championed your dissertation within the organisation) either leaving the organisation, taking maternity leave, falling sick, or in some cases, simply losing interest in your research. Unanticipated events, such as organisations going into administration, or changes in policies towards accepting student research can also causes problems. Neither is it unknown for organisations to grant access (even in writing), delay access for weeks after it was intended that data collection should start, and then go on to revoked access altogether for no good reason (although this is relatively rate). Building in additional time for such delays is particularly important if (a) you only have one gatekeeper granting you access to an organisation, or (b) it would take a long time to gain access to another organisation in a worst case scenario (i.e., some access is granted immediately or in a few weeks, especially if you are speaking to a decision maker in an organisation, but in large organisations, this can take a lot more time).

Giving yourself more time to complete the data collection phase is always a good rule-of-thumb, but if you recognize any of the potential challenges above in your dissertation, we would suggest that you start the data collection phase as early as possible.

If you end up with extra time, this can only be a good thing, especially because it will give you more time to work with your data, which can often be time consuming, especially if you (a) are not used to performing statistical analysis, or find this process challenging, or (b) are unfamiliar with using software to statistically analyse your data (e.g., SPSS), which are typically required. We discuss this further in Consideration #4.