Follow sourcingfocus on Twitter

Donald Trump and business analytics – trends in BI in 2017

by JCommerce

It has been estimated that as many as 91% of the ‘facts’ from Donald Trump’s election campaign are untrue. The scale of this phenomenon means that the denial of false information has ceased to be effective, because such messages are drowning in a sea of memes, tweets, catchy titles and brainless posts. No wonder that Oxford Dictionaries declared post-truth the word of the year for 2016. In a broader sense - not just in political terms - this could be due to the phenomenon of data-pollution. Just as Polish cities are suffocating in smog, virtual reality is suffocating from too much information. Experts from Qlik say that this phenomenon is so severe that it will come to define technological trends in the coming years, just as with business. Certainly this is the case in the field of Business Intelligence. 2017 will be the beginning of the fight against data illiteracy, which is the process of spreading the skill of “reading data”, its analysis, verification and selection. Other trends for 2017 are Big Insights, business intelligence based on context, and the increasing use of data analysis tools by employees at all levels.

Data-pollution
It is estimated that by 2018, 80% of data stored will be completely useless, with neither the possibility nor sense of processing it. This is directly related to the abovementioned phenomenon of data-pollution. Infrastructure for data storage is cheap and widely available, so companies are producing an increasing number of bytes - unfortunately, their value is questionable at best. The collection of such data is often art for art’s sake, without purpose and strategy, just a vague idea that it may prove useful sometime down the track. The result is that even information which is important to a company often dies in the black hole which is the database. Such a situation fails to facilitate the wider use of IoT, which is the Internet of Things. Like every great idea, which originally was to serve the good of humanity (economical and ecological houses or cities, the comfort and convenience of senior citizens and people with disabilities, etc.), the Internet of Things is becoming a caricature of itself. The Internet can be connected to absolutely everything from the kettle to the cat’s litter tray, collecting terabytes of completely useless data. Wired magazine mentions that the ironic term the Internet of Shits is ever more popular - which basically means the imminent death of ideas, at least in their present-day, gadget-like form.

Big Insights and data visualization based on context
Everything points to the fact that the coming years will mark the end of the Big Data fetish and the beginning of Big Insights, which is a critical approach to the data being processed. And there will be more and more of this data, which will be more nuanced. Expanded reality and IoT will bring about the contextualization of data in the real world, which will enable the capture of specific events (our actions, decisions, and behavior) in a particular place and time. And this will further blur the boundary between the physical and virtual worlds. The game Pokemon Go is just one such example. This also means that business analytics will need to exceed this limit.

Data analysis must be based on an ever wider context. Otherwise, the company runs the risk of operating in a virtual bubble. A similar phenomenon is now being observed by social networking researchers, who have noticed that their users operate in an environment of friends who are similar to each other, with access to selected information served to them depending on the choices made (the number of likes) and calculated by preference algorithms. This is the so-called filter bubble. Of course, the image of reality which thus arises is false, distorted, and is also harmful in many respects because it means that our choices influence the shape and content of the information presented to us. For business this situation is equally dangerous: a company functioning in the business reality created by the paradigm of their own data is on the direct route to being isolated from the expectations of customers, the situation on the market and, of course, to financial disaster. By the way, it is completely unaware of this danger - because of course it uses the most modern IT solutions. The conclusion is obvious, it is not enough to analyze their own data – it is ever more important to confront this data with external data and take that into account in the decision-making process. Even if - and perhaps especially - when such data makes us uncomfortable and disturbs our comfortable perspective.

The democratization of data analysis

On the one hand, we must decide what data to collect, but on the other hand, we must learn to read the data. In companies it will mean the dissemination of tools for business intelligence. But what does this mean exactly? Well, access to advanced analytical tools can no longer be reserved exclusively for top-level executives. Access must also be granted to all employees, who can more effectively carry out their tasks thanks to the use of data. Not only that - analytical initiatives (i.e. how and what is to be analyzed) must be bottom-up, because every employee knows their area of operation best and knows what data is most useful. An employee also adds his own input, a unique perspective, which significantly reduces the risk of enclosing decision-makers in a virtual “filter bubble” distorting the image of reality. Companies must therefore develop a new complex ecosystem of Data - People - Ideas. The IT department must be at the center of this, and must be equal to the task in terms of the provision of relevant data and the mechanisms for processing it.

This is obviously a much more complicated task than simply implementing the appropriate Business Intelligence tools - entrepreneurs should in fact change the operation of their businesses, focus on the education (training) of employees in the framework of acquiring, analyzing and using data on the job. Data analysis soon ceases to be a narrow specialization for IT people only, but becomes a key competence of every employee, regardless of his position - it can be considered on a par with language skills and ability to work in a group in one’s CV, without which employment in a modern company is practically impossible.

Author: JCommerce
Article from NearshoreIT - Blog


 

  • del.icio.us Favicon
  • Digg Favicon
  • Facebook Favicon
  • NewsVine Favicon
  • Reddit Favicon
  • StumbleUpon Favicon
  • Technorati Favicon
  • TwitThis Favicon