"Research is a human experience, not just a tool for data acquisition."
In consulting assignments, we are time and again confronted with decision-making requirements that need a reliable robust data framework. Not only should the customer's existing data be used, but the entire market environment should also be taken into account.In the case of SMEs in particular, we find that entrepreneurial intuition - or sometimes simply "gut feeling" - are sometimes the most influential decision drivers.
Especially with the rapid digital transformation in companies, this is often not enough. Exemplary questions that we encounter again and again are, for example: How are online sales channels changing in B2B business (or even B2C), which market shares with which profitability are coming under pressure - or can easily be conquered additionally? What are the absolutely necessary minimum viable product features for a short time-to-market development, and which ones can follow after the launch? And what are the needs and willingness to pay in different target groups?
To answer such questions, we as consultants also like to rely to proven approaches of market research (MR). MR offers a multifaceted view into the future. And MR is by far not only survey research, but meanwhile very often advanced analytics, social media analytics, creative online qualitative research, secondary analysis of texts, images, and many other sources. An increasing importance is seen with analysis of process-produced data from operations, from automated accessible sources (e.g. partly even public data, or mobility analyses based on mobile communications). MR in the digital age has long since supplemented the classic approaches with new methods - be it sampling, online panels, the use of virtual or augmented reality systems, or highly complex modeling and scenario building with recourse to AI methods.
Thus, models of future possible reality are mapped into decision support systems, supporting or contradicting existing assumptions. This "unbiased" type of second opinion proves itself time and again.
In the past, MR was often considered too slow to still influence a quickly required decision. But in the last 20 years, MR has become dimensions faster. Static considerations in the rear-view mirror or as a fixed picture of a future development are increasingly becoming a thing of the past. Dynamic models, available at any time at the decision maker's desk, are becoming the standard, and "real-time-predictive decision support" systems based on real-time data are already becoming more and more common. In the future, the "budgeted planned" enterprise will become the forecast-based "predictive enterprise", calibrated with real-time data and systematically proposing decisions.
Is MR only something for established companies with big budgets? Most certainly not. Even for startups, "never have a single point of failure" applies, and this can just be a false assumption shaped by founder enthusiasm. Good MR uses a wide variety of ideas and methods to test such assumptions - even with a small four- to five-figure budget. Good MR is creative, and for a given budget it can do the best that can be achieved. Measured in terms of avoided error costs, well-done, quality-assured MR has an excellent return on investment.
And last but not least: MR (from a solid provider) also convinces investors, because they want to know reliably: Is the market there? And is it as developed as assumed? Does the new product/service really hit a well-defined niche with a willingness to innovate? And is the niche big enough to grow? Is it small enough to achieve a unique position with at least limited or delayed copyability? What are the (possibly controversial) views of the potential and actual customers? Are the targeted customers "sufficiently willing to take risks", i.e. open to the product or service innovation offered by the startup? These are all typical MR questions, even for established larger companies, but it is almost always possible to define MR designs that are appropriate to the situation and budget and that ensure a decision with sufficient accuracy. This also applies to the standard key topics such as a.) Communication, b.) Product (features trade off, e.g. also SaaS vs. other licensing models such as subscription, pay per use, purchase license), c.) Optimal price and d.) Expansion and scalability in the achievable market.
At AAA-Advisors, we have experienced consultants with strong MR backgrounds. We are happy to help you assess if and which MR you need. We can assist you with Data Scouts and Data Architects - as idea providers for the valorization or creation of your "Data World" as well as MR-neutral independent consultants. We know the players in the market and can assess and organize the appropriate data analysis and, if necessary, MR approaches on an case-by-case basis - regardless of whether a budget-friendly DIY approach or the commissioning of an expert house is ultimately on the cards.
Recently, we offered a webinar at ProjectTogether.org for founders of social initiatives or non-profit companies - equally applicable for SMEs. We will gladly provide you with the video recording upon request via our contact form.
Picture: by Leon on Unsplash.com
