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In my experience, I find that most people who buy research software spend most of their time considering the look and feel of the software and the features it contains. And, of course, price is a big, and often the biggest, determinant of what is bought. What is often given little or no consideration is how productive the staff using the software will be. Maybe, it’s because it is hard to measure productivity when evaluating a software product. Maybe, it’s because it doesn’t seem important. I think it is important, often the most important issue, so let me explain why and how you can measure productivity.
Let’s say that you are considering two possible software products that seems equally suitable that are priced at $5000 and £10000 per year to use. Let’s also say that the cheaper product needs a team of three people paid $20000 per year and the dearer one offers productivity benefits that means you need two people paid $20000 per year. Which would you choose? Well, obviously, you would choose the dearer product. But, would you really? I would contest that many would buy the cheaper product because they wouldn’t consider productivity sufficiently. So, let’s dig a bit deeper.
There are six key things that affect productivity when using market research software. They are:
I’ll now discuss each of these topics in more detail.
This is the one that can work contrary to the example I cited in “First, some simple business logic” and means that my example could rightly be challenged. It is true to say that often more productive software needs more skilled staff to use. Maybe, the less productivity-focused software would need three staff at $20000 per year and the more productivity-focused software would need two staff at $30000 per year. Clearly, in this case, the increased productivity makes no difference to profitability. You might even add to this that the cost of training and familiarisation will be higher for the productivity-focused product as there may be more to learn. But, there is an important counter-argument which is often neglected. That is, productivity-focused software can make an exponential difference.
An example of making a ‘big difference’
It wasn’t so long ago that I came across someone labouring with a software product that was being used on a big market research tracking study. The company was spending about 30-man days per month to process the data and produce various analyses. The problem wasn’t that the software product that was being used couldn’t do what was needed, but that it didn’t have the right tools to do it efficiently. I am not saying this to promote our MRDCL product, but MRDCL was the right fit on this occasion and would have reduced the time needed per month down to 1-2 man-days per month. The potential client didn’t buy our software as they compared price tags and just could not imagine that they could really save over 300 man-days of labour per year. It was beyond their comprehension.
Exponential differences happen in data analysis
One truism that is often ignored when it comes to data analysis is that efficient vs inefficient methodologies or tools can make a difference of 2, 5, 10 or even 20 times. This may not be seen in a typical office environment where something carried efficiently vs inefficiently may make 10-15% difference – and, rarely, more than a difference of two times.
I’m a big fan of short-cut tools, but I’m also unexcited sometimes by some short-cut tools. What does matter is whether they make a big difference. Well-designed software deals with things, which I tend to think of as usually being at the two ends of the spectrum – these are simple repetitive/laborious tasks and complex tasks.
The simple and the complex
Frustratingly, perhaps, market research questionnaires are remarkably similar yet mostly different. They often contain rating scales (or grids) which in terms of data collection, data analysis and data reporting have repetitive requirements. You, therefore, needs tools that handle this in a highly convenient way – without, copying and pasting, for example. Similarly, many projects will have some complexity, something that is unique to that survey or type of survey that you handle. You will need tools that can make the handling of these complex needs as risk-free and focused on productivity as possible. In our MRDCL tabulation software package, for example, we allow users to build customisable templates that can cover a set of data management or analysis needs in a simplified user interface. Other software packages may have other solutions. Simplifying the complex can be important, especially for long-term projects such as tracking studies and audits.
Too many software companies do not consider how it would benefit their users in terms of usage as a team. For many survey platforms, it is necessary to have a policy of one person working on each project. This really can cause bottlenecks in terms of production and client delivery. Therefore, I think productivity increases if the software has at least some tools to make it possible for colleagues to share projects and workloads as well as making it easy to hand over a project to colleague if they are ill or leave.
Getting the right level of staff working on a project
Software platforms that facilitate the sharing of projects offer a secondary benefit too. It means that you can have the right level of staff working on each aspect of the project. There may be a need, for example, to produce some complex analysis from a research project. However, if a lot of the work requires keying a large amount of text, for example, you ideally want some less able to key in the text, leaving the more experienced person to do the complex work. Too often, I have seen experts keying in text effectively becoming expensive typists.
This is an obvious one and barely requires further comment, but you do need software tools that can provide whatever the client asks for (within reason, of course). Sometimes, there are ways to get round something that is more difficult than usual. If this occurs infrequently, spending a few hours on something that may be conceptually quite simple but awkward in your chosen software product doesn’t matter too much, but it starts to become a problem if it is a regular event. Enough said, I think.
I like software that has more than one way to achieve what I want. Obviously, that is not always possible or practical, but what I mean is that I like software that offers different approaches to tasks. That might all sound rather vague, but software that has more than one route to achieve many requirements is more likely to offer productivity gains where productivity gains can be made. For sure, some tasks are just a case of entering into a computer what you want or clicking a checkbox, but market research, as cited previously, often comes with repetitive needs or one-off complexities. For such things, you need that software flexibility.
I suppose many would bracket this last point with the previous point, but I always feel more comfortable with a software product if I know there is more that I could learn. This doesn’t mean that I will learn everything, but it means that I can be more confident that I can find a way to solve any future tasks that I might be presented with. Take something like Microsoft Excel. Most users of Excel use a very small percentage of the functionality available – I suspect I use more than many other users, but it’s still a small percentage of what is possible. What I like is that I know that I can find solutions for more or less anything I want to do in Excel. This means that I can have productive way to do whatever I want to do – which matters!
So, I’ve tried to make that the point that productivity matters. I’ve tried to help others to assess productivity. Yes, it’s difficult when trialling software, but I think it needs to be high on the list even if it is no more than a best-guess assessment. As a software supplier, I would actually like to be challenged more about the productivity users can expect from our software, yet, we are rarely challenged. Feel free to challenge me by writing to me at email@example.com. If it is relevant, I will gladly add your comments to this post.