Decision makers drown in information but are thirsty for actionable intelligence

Artificial intelligence, big data, deep learning, machine learning (supervised or unsupervised), are all buzzwords we are confronted with on a daily basis and reflect the hype that we are currently experiencing. A bubble, that correlates highly with the low-interest rate and easy money environment, in which investors are desperately looking for ways to generate higher returns and thus become susceptible to such concepts.

The reality is that there is no real artificial intelligence yet, and that the solutions we see can nicely be sorted into the “narrow AI” space used to identify patterns by learning from inputs to generate respective outputs or employed to identify insights from unstructured data. In many instances teaching those systems, such as in machine learning, requires tremendous manual work before they become more efficient and serve their purpose, a point that is generally discarded to give users the impression that they will profit from day one by using respective solutions. The best systems furthermore will always rely on solid data, and conventional wisdom like garbage in and garbage out hold even true for the brave new world of AI, big data, and network science. Furthermore, they will rely on the people involved who play a crucial role in developing those systems but also infer the right conclusions.

I argue that major corrections in the stock markets, and a reorientation of investors to less risky business models will sort the wheat from the chaff and potentially lead to over 90% of existing businesses in this area disappearing over the coming years, as we had experienced with technology-related companies during the last major bubble in the year 2000. Solid organizations will heavily profit from this correction as they are not built on imitation and noise but are focused on sustainable and long-term solutions that provide real value added for clients, and particularly actionable insights. The future, above all, clearly lies in combining the various approaches into a meaningful whole. Here network analysis/science will play a crucial role as it literally connects the individual disciplines and provides a framework to look at the world from an interconnected and embedded perspective. All research disciplines will profit greatly from network analysis that considers the ties that connect individual building blocks in a complex system to really understand what drives it. So it is not about AI, deep learning or network science separately but more importantly about the integration of all concepts into a more powerful process, such as Ecosystem Intelligence, to empower humans.

It is therefore about how we use technology and latest advances in a complementary manner to empower people, reduce complexity, and give control back to decision makers who increasingly have the feeling that they are no longer in control of things.

 

Ecosystem Intelligence: Going beyond the scope of traditional intelligence

AI is certainly not a new subject, and anyone in the field will have read about the ups and downs the research faced in the last decades. The future will bring about increasing complexity and to understand complex systems, people will need to look beyond and understand the wiring (i.e. the interconnection between the individual building blocks). That is where network analysis/science comes into play and increasingly will form the basis for new developments. Technology will help us to speed up and automate processes, to identify patterns, to manage complexity, and to offer the basis for decision makers to act upon the various insights generated in an informed manner. It is therefore about how we use technology and latest advances in a complementary manner to empower people, reduce complexity, and give control back to decision makers who increasingly have the feeling that they are no longer in control of things as they can`t adequately cope with dynamic changes and the opportunities and threats that emerge. The integration and convergence of concepts such as artificial intelligence, big data, deep learning, and machine learning will provide unique and actionable insights (which can be seen in SONEAN`s Ecosystem Intelligence).

Ecosystem Intelligence sets a new standard when it comes to monitoring the competitive and external environment of corporate decision makers globally, helping them to spot opportunities and threats dynamically in an unparalleled way. In Ecosystem Intelligence, an ecosystem model serves as the basis for the monitoring process and incorporates social as well as organizational networks among organizations. Data is thus structured, researched, and connected in a way that companies receive a dynamic, connected and 360-degree view of the global sector in which they operate connected to daily events captured across the world, in any language and country that are related to the ecosystem in which the organization is embedded. This allows decision makers to receive unparalleled intelligence, and make vital and informed decisions.

Take the example of a corporate CEO who is in charge of a global company and faces an increasingly volatile, uncertain, and complex environment where unique, connected and dynamic intelligence becomes a game changer. This CEO is literally “drowning in information but thirsty for intelligence”. He or she feels to be no longer in control due to the complexity of the competitive, and external environment his/her company operates in, and which dynamically changes. If an organization operates in more than one hundred countries it needs to find a way to create one intelligence platform, in a single language with independent insights for the whole global marketplace. This platform has to provide dynamic intelligence related to all opportunities, and threats that emerge across the world in a given sector, ecosystem,  in which the company is active. This also means to go beyond the scope of traditional intelligence to create, analyze and monitor a perpetually improving, and dynamically adjusted map of the company`s entire global ecosystem by applying social, organizational, and meta-network related analysis and connecting data in a unique manner.

Empowering our real intelligence

A lot will happen in the next 25 – 30 years with computers emerging that potentially start matching our brain`s capacity. We will also figure out the wiring better of our 100 billion plus neurons in the brain. In the meantime, though we should use the individual concepts such as narrow AI to uncover patterns in data, machine learning to turn inputs into outputs and network science to connect data in a unique manner and provide a 360 degree perspective of the environments in which we operate. Technology can be used along the entire process from building an ecosystem model that drives the research process, to monitoring millions of relevant data channels, and consequently using those insights to predict future outcomes. We have all the building blocks to create intelligent systems and processes that facilitate global decision making using a single platform, and with Ecosystem Intelligence e.g. we are already working on the future of corporate intelligence. Let`s concentrate on empowering our real intelligence, the people that run organizations, and take high stake decisions on a daily basis, and let`s use AI, big data (smart data), and network science in a complementary manner to provide a better basis for people to take decisions in a much more informed manner. Network analysis and an understanding of the ecosystem in which companies and people operate will be vital for any intelligence process in the future. This will also affect international lawyers who increasingly will rely on connected and global intelligence to better serve their clients. Bear also in mind that roughly 10% of board members of the largest 50 European stock exchange listed companies (STOXX 50) have a legal education and thus will potentially play a relevant role in the future adoption of latest technologies. Welcome tomorrow!

Written by: Dr. Murat Unal

Bio: Dr. Murat Ünal

Dr. Murat Ünal, Chief Intelligence Officer SONEAN, is Alumni of the Executive LLM and the Legal Bridge to Silicon Valley Executive Program. He also earned a Doctorate in Business Administration from IE Business School specializing in social network analysis (SNA).

Murat founded SONEAN in 2013 with his team, building on its sister entity Funds@Work AG (F@W)`s experience since 2002 in over 250 international projects in the wealth, and asset management industry with more than two dozens of international awards received for its consulting & unique intelligence. SONEAN was designated as “innovative young company“ in 2015 by the German Ministry for Economics and Energy and became part of Germany`s Excellence in Big Data campaign rolled out globally in 2016. 

Murat participated in the IE Alumni Forum 2016, and was selected for the Epic Award at IE. Earlier this month, he participated in “A Changing World” alumni meeting. He regularly lectures at leading universities globally focusing on the unique application of SNA.