How Analytics & BI Are Shaping The Modern Organization

How Analytics & BI Are Shaping The Modern Organization


Big data increasingly takes the central place in digital transformation that today’s businesses aspire to go through in order to stay competitive. Forbes cites it as a foundation for any digital transformation initiative, yet big data as we know it becomes a thing of the past. Now big data needs to be fast, clean and manageable beyond just being 'big', which reflects how important it has become to put vast amounts of data to the right use and do it sensibly.


In its turn, this shift in business thinking drives the BI market that is estimated to reach over $26 bn by 2021 with the compound annual growth rate of 8.4% (Zion Research). The demand is soaring due to the promise of substantial gains – as estimated by International Institute of Analytics, data can save companies up to $430 billion in productivity.

Eventually, those who learn to handle analytics to their advantage will see positive returns from better relationships with customers and employees, as well as streamlined internal processes. And as data becomes an asset to be monetized, more vendors enter the ecosystem offering big data as a service and thus driving cloud-based BI at the same time.


All this does impact the culture and strategy of today’s organizations. Below, there are key areas where we will impatiently wait for transformations to come.


More Smart Machines, Less Humans


Smart machines are becoming an essential element of the working environment. This paramount tendency is made possible due to advances in artificial intelligence and is powered by breakthrough natural language processing, voice and face recognition algorithms.

Though far from outnumbering people at work, in its hybrid form, the trend will result in at least 20% of workers using automated assistance in a little more than 2 years. Meanwhile, economic transactions will be slowly but steadily overtaken by autonomous assistance (5% by 2020).

One of the major innovations that we’re seeing now, chat bots are no news, yet the technology is far from being perfect and still evolves. As it comes, consumer-facing businesses are the first adopters, like luxury hotels and innovative digital retailers, and they set out to pioneer it across channels (mobile, social, etc.), changing the way we perceive our real-time communication with brands.


Fuel For Customer Experience


It’s not accidental that consumer communication gets the most attention in the data land. Data itself gets its central place in shaping and improving customer experience, whether we talk about business-to-customer or business-to-business brands.


From sourcing customer satisfaction data across CSAT surveys, online reviews and social networks to tracking customer behavior and personalizing offers, customer data becomes the key to proactive selling, informed customer support and effective re-engagement of returning customers.

This approach calls for major changes in customer experience ownership that needs to extend beyond marketing departments, as well as for enforcing master data management across silos to get a single, true version of customer data with no duplicated or missed details.


Going  Cognitive


2017 is likely to see a trend towards predicting and promptly satisfying customers’ needs, which will play out most in market leaders’ analytical strategies. This largely relies on machine learning mechanisms that go hand in hand with innovations in artificial intelligence.


One of the most notable examples of the recent times, IBM’s Watson platform is going to play a more vivid role in the coming of prescriptive analytics. Other products loaded with intelligence are likely to be rolled out quite soon to help companies make sense of their data and proactively reach out to customers based on their behavioral and purchasing patterns.


Faster, Real-Time Data


The reality dictates its own requirements for data to be processed right here, right now. This raises the importance of advanced automation at enterprises and implies that all systems should work in sync to consistently interact with both internal agents and customers regardless of the task.

In terms of software architecture, this means a tectonic shift from relational databases towards solutions that could enable real-time streaming of data insights, not just on-demand retrieving. As data flows are getting more robust, businesses will need to make sense of them by adopting specialized platforms like open-source Kafka.

Some of the implications of this trend will include safeguarded operability, better risk management, increased advertising yields, and on-point retailing, among others.


New In Staffing


Of course, such major changes can’t help affecting organizational structures. Chief Data Officer will become a ubiquitous position with the major responsibility to manage an efficient data management strategy to maximize financial returns.

At the first hectic stages, CDOs will observe vast data landscapes and guide their companies into technological transformation, yet the position is likely to fade out once industries learn to harness data on their hands to derive value from it.


The employment market in general is changing drastically. Beyond senior positions, companies will be looking for talents such as data analysts and scientists who are particularly well-versed in machine learning and artificial intelligence.

Shortages in qualified BI consulting workforce will drive employers to ignore the lack of specific industrial experience and get to nurture required competencies in dedicated labs, whether in-house or at higher education and research institutions.

At the same time, though, the market will be seeing more analytical tools for non-coders that won’t require dedicated analysts to figure them out.

Conclusion

We’re living in curious times when data is growing exponentially, and we are those main producers of terabytes generated every second worldwide. Successfully getting over initial frustration, businesses will come to understand thrilling competitive advantages hidden behind unstructured data that they have to face in the course of their daily operations.


With ever more connected devices of emerging IoT ecosystems, innovations in the cloud, and more, mind-blowing innovations become possible indeed. From more digital assistants becoming an everyday reality to new professions we haven’t dreamt of even ten years ago, the business of tomorrow will change tremendously.

Those who want to gain a clear marketing advantage will have to adopt a new data governance model, step up technologically and be ready to transform at the same pace with customers’ expectations.

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