Data-Driven Automation – Threats and Opportunities for IT/ ITES
The evolution of analytics, big data and IoT has led to the era where corporations are leveraging data to create business value, provide insights to take quicker and smarter decisions, and gaining a competitive edge in today’s volatile and dynamic marketplace. Data drives every single organisation and data-driven decisions have become one of the most competent factors for their growth. We are in the era of big data, IoT and AI and these are the technology trends which nobody can ignore. The big data and analytics market is growing at an overwhelming pace.
According to a Report by IDC, the worldwide revenues for big data and business analytics market will grow to $203 billion by 2020.
However, like any other new technological entrant in the market, data-driven decision-making ability has presented a host of opportunities and risks for IT and ITES companies. Let me explain –
• Massive Growth – Big data is one of the leading trends in the IT and ITES industry with a huge demand for industry experts in the space. The big data market is also expected to grow at an annual rate of 23% until 2019 and the annual spending is expected to reach $48 billion by 2019. Most of the industries are depending heavily on data – generated by systems, processes, and people – to make business decisions, and at the same time, data is growing exponentially with the current volume of business transactions and data transfer. Driven by the growing demand for analytics, the industry is witnessing a rapid growth.
• Abundant Opportunities – ITES/ BPO industries today are depending on advanced technologies and solutions such as chat bots, Smart IVRS, Robotics and real-time analytics to automate customer service processes, to bring down costs, enhance the speed of operations, and enhance customer experience. The demand for these technologies is only going to increase.
• Innovation – Recently, the term “disruptive innovation” has caught the attention of the industry. Experts describe that disruptive innovations are cheaper, more accessible, and are based on business models to deliver cost advantages. The new world of modern innovations is heavily based on data at their core. With data, entrepreneurs and innovators are targeting various angles of the industry which was impossible in the traditional path of disruptions. Data is making the cutting-edge data-enabled disruptions cheaper and more accessible.
• Co-Innovation – I had earlier written a detailed post on co-innovation as a mantra to co-exist. I believe that co-innovation allows companies to highlight their domain specific expertise. Co-innovation leverages the collective intelligence and is based on the convergence of ideas, collaboration, and co-creation of experiences. With big data and analytics, organisations are able to co-innovate with their vendors and customers to build the solutions, tools, and technologies that the customers really need and care about.
Threats to watch out for
• Adaptability to change – As we continue to see the hype and greater awareness in analytics and big data realm, the pace of the technological advancement is also happening at the same rate. That has not only fuelled the growth of startups but a lot of major mergers and acquisitions as well. With a variety of open source tools available such as Hadoop, Hive, and Spark, to name a few, companies developing analytics tools now have to justify the value propositions to the customers for the value add and benefits for the implementation costs. Vendors need to come up with a lean and easy-to-build-and-use solution in order to sustain in the analytics and big data market.
• Engagement Models – Organisations need to come up with newer and innovative engagement models that will address the business goals and objectives of their customers. Billing models which rely on efforts are no more relevant because, with data and analytics, the efforts for achieving certain objectives have gone down considerably. IT/ ITES vendors need to innovate models where they can bill for the value add and not only the efforts.
• Key Talent – While the demand of qualified professionals is going up, there is a massive shortage of qualified manpower who can gather and analyse data and build solutions around that. According to a study by McKinsey Global Institute, by 2018, there will be a shortage of 190,000 data scientists in the US alone and a shortfall of 1.5 million managers and analysts who can leverage the data to make decisions.
• New Skills and Mindset – With the proliferation of big data and analytics, the ideal human resources will be those who possess business, statistical modelling, and data analytics skills to predict the right trends. Also, organisations need to keep on rotating the talent across different domains in order to build diverse and unbiased experience. Lastly, it is also crucial to stay abreast of the changes and innovations in analytical and big data technology.
Keeping in mind all these factors I would just like to opine that all in all, big data can be a boon or a bane depending on how companies are able to cope up with the wave. What is your take on this?
Thank you for reading!