Interview with Stefan Oglesby about his upcoming DGOF Workshop “Smart Data - Methods, Models, Use Cases”
The workshop is scheduled for Tuesday 12. November 2019 in Cologne.
Dr. Oglesby, on 12 November you will offer a workshop entitled "SMART DATA - Methods, Models, Use Cases" under the umbrella of the DGOF in Cologne. Most people are now familiar with the term "big data", but what exactly does "smart data" mean?
"SMART" refers to the meaningfulness and relevance of data in the context of a stringent data strategy. Big data today accumulates in large quantities, in a wide variety of formats, and continuously, for example through transactions on the Internet, sensors (Internet of Things) or even company-internal processes. Although this data is valuable, it makes no immediate sense. By SMART Data, I mean data that makes immediate sense and thus enables better decisions. There are two prerequisites for SMART Data. First, the data must be stringently processed in a pragmatic, proven process. The starting point for this process is not the data, but the strategic issues of an organization - that can be an SME or a global corporation. Secondly, the right data sources must be identified, intelligently linked and modeled to best and efficiently answer the strategic question. Today, every company needs a data strategy, especially in view of the growing amount of available data. SMART Data is a proven, science-based yet simple concept for implementing a data strategy in the enterprise. SMART Data is essentially a smart data strategy for the enterprise.
You say that Big Data is now making traditional consumer surveys superfluous. Why is that so?
In fact, it can be observed on Google, for example, that the search term "market research" has been replaced by the term "big data" in recent years. Both the German and Swiss associations of "classic" research institutes reported a decline in the total order volume in 2018 despite the good economic situation. To a certain extent, Big Data thus appears to be replacing the classic consumer surveys. However, the conclusion that Big Data makes classical market research superfluous is wrong. Rather, market research - or "Consumer Insight" - must return to its strengths and core tasks: Answering strategic questions from management, marketing, corporate communications, the innovation department, etc. Digital data sources ("big data") often provide a precise and objective picture of consumer behaviour patterns. But it is only through the skillful combination with other data sources - such as surveys or comments on the Internet - that a clear picture of the person behind the data patterns, their needs, expectations, values, and preferences emerges. In this sense, SMART Data - specifically the SMART Data Model - is a blueprint for how market research can effectively fulfill its core task in the era of big data.
Can you give us some examples where Smart Data has already been used successfully?
SMART Data is used across the entire spectrum of questions in marketing research. The SMART Data model is most commonly used for consumer segmentation. The goal is effective content marketing. Another application is the development of price strategies based on objective price data from websites in combination with consumer price expectations. The digital measurement of actual advertising contacts - online and offline - forms the basis for estimating the impact of advertising campaigns. The combination of survey data with social media data allows comprehensive brand tracking. In addition, there are interesting individual applications, for example in retail. The integration of transaction data, tracking on the web and via mobile app creates a comprehensive picture of the customer journey.
Who is your workshop suitable for and what will you teach there?
The workshop is aimed at everyone who is interested in how different data sources can be used for relevant, implementable insights about consumers and markets. Previous knowledge in statistics or data analysis is not necessary. The workshop gives an overview of the relevant data sources, shows the implementation of SMART Data using concrete case studies, and points out the challenges in dealing with digital data sources.