Part II: The Work of SwissPeaks

The work we do here has always had a data-centric core. I have directed countless presentations and training sessions on good practices in data management, and whether via formal events or simply through informal discussions, I always drive home the fact that the data management process starts when the questionnaire is being written.

A sequel to “The Birth of SwissPeaks” (go over and give it a read if you haven’t already) and part 2 of the trilogy is the Work of SwissPeaks. 

Arguably, if a project is to succeed then data management, as we would like everyone to see it, is much more than just scripts, numbers and all the rest of the geeky, techie stuff. Nonetheless, most perceive data management as building data collection scripts, collating data and running analyses. It is very common for SwissPeaks to get involved with all the non-techie data management tasks such as questionnaire design and field management duties and judging by the number of projects that have crossed paths with us, we can say unequivocally that there are two major problem areas that surround data management: 

• The questionnaire
• The interviewing, training and supervision of the questionnaire

We have invested much time in Africa over the advancement of our lifecycle, and have designed and implemented a sturdy quality control (QC) toolkit over the years. This is mainly for collation and analysis related activities, but also to garner more control over the questionnaires and interviewers. Our initial service portfolio involved working in data processing departments at large research agencies as an overflow service and since then, we have organically expanded our portfolio of data related activities. Yes, we still provide data collection scripting but now we predominantly work from CAPI and CAWI (online) perspectives.

With CAPI in mind, we’re taking on more data collection management responsibility. To facilitate this, we’ve recently created a local divison of SwissPeaks in Nairobi, Kenya. By doing so, we can ensure the collection activities are running smoother by being able to supervise, run and control the activities ourselves. Having accrued a smoother collection method, we can then run quicker collation and analysis processes, enabling provision of deliverables to clients within five days of fieldwork end, which we recently demonstrated on a national project in Uganda.

We’re confident that when more control is taken over front-end activities like questionnaire development and conducting interviews, less time needs to be spent on collation activities thus allowing more time for the creative stuff – utilising data visualisation applications and bringing the data to life. We want more ownership of the data control for one main reason and that is that we want credible, quality-driven data available to us. This way, we can fulfil our dream of making data more accessible, more usable and more insightful. We can ensure that data sources are clean and credible, thus ascertaining that nothing but accurate data is going back to the end user. I’m happy to reveal that we are en route to reaching this vision and subsequently producing high quality and easy to use data visualisation solutions for our clients.

In the next and final part of the SwissPeaks trilogy, I’ll let you in on the problems and shortfalls encountered with questionnaires and interviewers and over time share parts of our quality charter with you. Make sure you’ve followed us on LinkedIn and Twitter or you’ll forever kick yourself for missing out – this is some good stuff!