Business A professional view Can industry standards of professionalism be maintained while pressure mounts for ever faster and cheaper insight? Christian Walsh, digital director of MRS, chaired an MRS Delphi Group discussion on this A t the end of last year, the MRS Delphi Group convened to discuss what constitutes that vital quality of any thriving sector professionalism. What does professionalism in the research sector look like, whose responsibility is it, and how do we make sure it is valued and embedded in the business of research for the new decade? The focus on professionalism is the first element in a three-part action plan for the sector in 2020, as proposed by Jane Frost, CEO of MRS. The plan covers: professionalism and ethics; a shared narrative; and inclusion and talent. Jane Frost, CEO, MRS: MRS has been relentless in its pursuit of standards, ethics and professionalism to defend our margins and eliminate bad research. A large FMCG client told us they were getting really stressed about the level of professional delivery they were getting from reputable agencies, with basic failure around questionnaire design and sampling. What do we mean by professionalism in the context of the research sector? Is this different for data analytics? Phil Sutcliffe, UK board director, Kantar TNS UK: Professionalism is adhering to high standards of quality throughout the research process: how we interact with consumers; the techniques we use to get insight from them; how we analyse the data; and how we deliver insight back to business or government. Data isnt different its just a component of that. Gemma Procter, partner, Sparkler: The fragmentation of our industry means that levels of professionalism and standards have started to differ particularly on the data analyst versus qualitative researcher side. I dont think there is anything at an industry level that is speaking both languages. PS: Data is now all-pervasive in industries, which is both a good and a bad thing. A lot of people who dont understand the potential bias in the data are making decisions off the back of it. 54 Colin Strong, head of behavioural science, Ipsos Mori: Ive worked in this industry long enough to be very familiar with that kind of bias complaint. If youre going to put people under more time and budget pressure, what is delivered back to you will be eroded. We need to be a bit careful about putting the responsibility for professionalism purely on the shoulders of agencies. Its a collective responsibility and we need to understand what everybodys collective roles are. Rhea Fox, head of insight and strategy, Aviva: I havent felt a decline in standards. What worries me on the professionalism side is that there appear to be a lot of start-ups who are selling insight get it back faster, cheaper but they dont seem to have credentials. The data industry has sold a very compelling story to stakeholders that data can solve everything. When youre client-side, half the job at the moment is helping stakeholders realise what data can solve and what it cant, and when a conjunction is needed. The only other factor may be that, in the old days, everyone graduated and went to Millward Brown, and read data tables for two years and learnt the basics, and thats not a route anymore. JF: Some still do. Ipsos puts everyone through the basic MRS qualifications. Do organisations understand the risks of faster, cheaper research? RF: The trap that insight teams sometimes fall into is thinking: If I deliver really fast, everyone will love me. But once youre in that space as an insight team, its very hard to pull yourself up the strategic spectrum. Practically impossible. GP: Research just becomes a validator, rather than starting at the beginning. RF: Clients need to be more disciplined and recognise that if you need an answer in half an hour, its probably not a gamechanging decision. PS: When done well, automation should be an enabler of better insight. It allows professionals to