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Expertise

Visualizing data

The importance of visualizing data is usually underestimated. But what could is a sophisticated analysis if the intended audience does not get the message? It is our job as researchers to get the message through. Over the years we have learned that the clear and sometimes creative use of visualizations is a powerful communication tool. It is an art to capture a lot of complex (often composite) data into one clear, self-explanatory graph. Hence we pay due attention to the composition of graphs, be it static ones in reports or dynamic ones in online management dashboards.

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Another important trend that we are closely watching is the increasing use of geographic representations of data. Google Maps is a well-known success story, who has spread the use of maps all over the place. We use Geographic Information Systems to analyze the geographic dimensions of data, and mapping tools to present data .

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hotspots of riots versus poverty, Manchester, 2011
 

For the analysis of data we use the full statistical toolbox, ranging from basic statistical tests to regression analysis and linear modeling and advanced techniques such as Structured Equation Modeling.

In a prior exploratory stage, we use data mining techniques such as classification trees, cluster analysis, C4.5, CN2 Rule and k-Nearest Neighbor algorithms.

We are also experienced users of social network analysis (SNA), which is not just suitable to analyze and visualize the links between people but also between firms. In essence, SNA is suitable to describe and analyze the structure of any kind of network. But don’t bother about statistics. We will get the maximum out of the data.

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social network plaatjes, t0 >> t1
 

Collecting data

We use a wide variety of ICT-based tools and applications to collect data. For qualitative purposes we use online surveys, including scripts that give instant tailor-made feedback to the respondent. To discern emergent preferences we use advanced techniques such as Conjoint Analysis. For the automated collection of data we use site-centric measurements (such as web crawlers) and client-centric measurements (scripts that are installed on a PC or mobile device and that automatically collect data from the client).

With regard to secondary data we use the data that we track in your own organization (you probably have much more data than you expect) and combine it with existing reliable open data sources.

But don’t bother about the data. We will get it for you.

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near real-time network coverage map based on user-centric measurements on mobile clients. Developed by one of our research partners, Oberon interactive
 

Intelligence

The only reason why organizations survive in the long run is because they adequately respond to the constant changes in their environments. These organizations are intelligent and alert.

Adequate responses in turn are based on relevant, accurate and timely information. This requires a purposeful and coordinated monitoring of the environment. Your organization should be able to anticipate the strategic moves of your rivals. You should determine what your rivals are doing before they actually do it. You should also be keenly aware of the changes that are occurring on the edges of your field of vision. Blind spots for emerging trends can be deadly in the long run.

No single general can do without good intelligence. Yet, many CEOs still base their strategic decisions primarily on gut feelings. Their firms do not have intelligence units, and they simply do not dispose of the information to make substantiated decisions.

Why we can help you (and others cannot)

First and foremost, we can provide you with the tactical information that you need, either on an occasional or recurrent basis. Through our experience, we translate your questions into meaningful and concrete indicators, trace the underlying data from internal and external sources, combine it, analyze it, enrich it, and visualize. This will lead to clear answers that can directly be implemented in strategy.

Lack of data is not a problem. On the contrary, you are probably flooded with data. There is also an abundant supply of management information systems, data mining algorithms, management dashboards and so on. However, these are just instruments. By themselves, they will never generate the knowledge that you need. This is where we are different. We work the other way around. We start at the demand side – define your needs, define the information that you need and then trace the relevant data.

The history of Dialogic Intelligence explains why we work this way. Our roots are in strategic research, not in IT. During the last 15 years, we have become extremely well-versed in the use of many kinds of software tools to collect, analyze, and visualize data. For instance, Dialogic has been one of the frontrunners of using internet data for official statistical purposes. Still, we are researchers at heart. Our drive is to answer the strategic questions that bother you.
 

ICT in sociaal-wetenschappelijk onderzoek

We maken zelf veelvuldig gebruik van ICT-applicaties in ons onderzoek, zoals blogs, wiki’s, keuzetools, spiders en websurveys. We bouwen ook websites speciaal voor projecten, zoals voor de Friese ICT-innovatiealliantie en vuistregels voor usability. Voor het Centraal Bureau voor Statistiek hebben we de mogelijkheid onderzocht om crawlers en spiders in te zetten voor het verzamelen van statistische data (‘Internet als Databron’).
 
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