The growth of the digital economy today depends on algorithmic business to a great extent. But it still remains difficult for IT, data and business leaders to work out what to do and how. Here we look at some things CDOs should know and understand before stepping into an algorithmic business.  

Organizations, in the coming years, would not be valued just for their big data, but also for the algorithms that turn data into actions and, ultimately, improve the customer experience. Algorithmic business is expected to be pivotal to competitive advantage. It is expected that by 2018, more than 50% of large organizations globally will compete using advanced analytics and proprietary algorithms, causing the disruption of entire industries.

1.   Algorithms are not new

Algorithms have been at the core of manufacturing control systems, marketing automation and campaign management. They have played a pivotal role in financial services for the past few years. The broadening introduction of algorithms as researchers develop ways to make algorithms smarter and more effective at mining new or previously untapped data resources has been observed.

2.   Different from business intelligence

BI usually focuses on the analysis of data to describe and understand prior events, ideally with the aim of predicting future opportunities and challenges. But everything we do is impacted by algorithms in some way. This includes planning, control, internet, social media, mobile commerce and process automation. BI is just one part of that and will be affected by algorithms, just like everything else.

3.   Prepare for speed and scale

Algorithms usually work at a much greater scale and speed. This cannot be easily matched simply by scaling human workforce. As digital business takes hold, increasing the use of algorithms will represent the most cost-effective and efficient wat to handle the handle the volumes of data and to exploit the growing numbers of business moments that arise.

4.   Accelerating rate of technological change

Rapid changes in technology, growing levels of connectivity between individuals, smart devices, growing volatility and flux observed in marketplace will lead to favor the increased use of non-human systems to identify and exploit opportunities. Cloud computing, ubiquitous connectivity, growth in smart connected devices, more data and the growing social acceptance of in-line activity and technology based solutions, termed as background trends, contribute towards growing acceptability. At the same time, these background trends also provide the infrastructure to support data collection and analysis on a hitherto impossible scale.

5.   Autonomous business

It’s easy to assume that algorithmic business and automation go hand in hand. But most algorithms that are in wide use today directly or implicitly operate under the direct responsibility of humans who are in control of the analytical process or task outcome. Algorithms only kick in to maintain your car’s speed, based on what it senses about the environment, when you turn on cruise control. You can turn off cruise control whenever you want. Autonomy is where algorithmic business gets really intriguing, and becomes the next big challenge for CIOs and business leaders. An algorithmic business has three building blocks, or functional roles, which we have described here:

is important that CDOs and business leaders aggressively pursue the technical capabilities necessary to drive algorithmic and autonomous business initiatives within their enterprises.

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