Digital transformation has become inevitable for businesses and they need to evolve their IT information systems, else they would end-up risking their competitive positioning and advantage. Vasant Shetty draws from his experience to highlight the challenges faced by IT and their digital transformation initiatives. He also has a word for the wise regarding the future, which will be built on data analytics.

The challenge faced by most CIOs in today’s corporate enterprise is to ‘keep the lights on’ and at the same time deliver disruptive IT innovations to businesses.

Due to data explosion over this decade, the business user’s need for information has increased multi-fold.

Digital Transformation has become inevitable for businesses and they need to evolve their IT information systems, else they would end-up risking their competitive positioning and advantage.

So what is hindering this evolution? The reasons why it is hard for any CIO or Head of informatics to transform towards disruptive solutions are:

1. Relationship and goal alignment between IT and business
2. Existing business intelligence investments
3. People skills and mind-set

Let’s look at each of the above mentioned reasons:

1. Relationship and goal alignment between IT and business: Driven by attaining efficiency and cost optimization, many organizations move their IT systems to a centralized model, where architecting next generation information systems takes a backseat; instead optimizing the infrastructure, systems, and processes becomes the primary goal.

   The IT organization works in silos with separate teams – EA, Development, Data Analytics, Infrastructure, and many others. The IT teams are aligned to businesses that approves IT budget based on its business and functional needs, which are typically vertical and functional based.

   With new technologies coming in all the time and the pressure to reduce costs, IT is always hard pressed to look for solutions that will manage both requirements. However, the transition to a newer technology stack will typically yield results in the form of better ROI over a period of two to three years. The biggest challenge for the IT organization though is to fund short-term and long-term strategic projects with minimal friction.

   Consider this simple example:

   Scenario:
   An IT manager at a large healthcare firm is managing five data warehouses that were developed at different times and funded by different business users. Each of these data warehouses has a different set of users, using data for various business reports. Each business user is satisfied with the reports and hence the function of the warehouse.Challenge:

   1. Over the last 10 years, large amount of data duplication takes place across the given data warehouses.
   2. IT is under pressure to reduce costs.

   Proposed solution by IT:

   The IT warehouse manager is trying to sell the concept of managing the data in a big data lake rather than in data warehouses, because it will make them efficient and improve information delivery, lowering costs in the long run.

   The resistance:

   The IT manager has to convince each of the business users to fund the big data project as a separate initiative. The business users are not convinced as the initiative does not add any significant value to their experience because the new system will create the same old reports.

   Now let’s look at the other side of the spectrum:

   Scenario: A CIO at a large insurance company was phenomenally successful because the board and management had decided to invest three years of strategic budget to leapfrog the technology progression of IT.

   Background: The leaders of the company had the foresight to acknowledge that in the coming three years, the business would be run on a next generation technology stack that leverages Cloud, Big data, Machine Learning, and Advance Analytics.

   Result: The IT function is way ahead of the business now and is able to deliver information analytics better than before and at a much lower cost of ownership of data.

The next generation of business competition will be decided over the analytics edge and competitiveness, not just using IT as a support function.

The corporations need to have Information Analytics reporting directly to the CEO and not to business or have decentralized business IT and only centralized IT infrastructure.

2. Existing business intelligence investments: The second big barrier for disruption? Large existing BI investments. These investments where right 10 years ago but in the last 5 years the cost of managing data, processing, and transferring data has dramatically decreased.
   Large enterprises are stuck with prior investments and are finding the transition to new technologies difficult or slow.The new enterprises or startups don’t have past information challenges and therefore are able to move faster and leverage the latest technology stack (Cloud, Big data and Analytics) to create new business models.
3. People skills and mindset. For analytics to be in the forefront of a corporation’s future, the culture of the next generation enterprise needs to be designed to have speed, specificity, and flexibility for analytics.
   Most IT people think of solving business problem in a structured and incremental way. The reason for such a thought process lies in past behavior:
   • focus on using internal electronic structured data and
   • tendency to deliver business solutions in a step or incremental model
   • rigid structures and strict governance model of the organization

Clearly, such thinking is completely opposite to the recipe for innovation.

Another aspect that hinders innovation is outsourcing of the IT function. All large and mid-size vendor business models are based on solving IT cost issues and the consulting firms models are based on time and material. The time and material and the cost-based business models are completely opposite to the goals for IT innovation.

The future with data analytics

The new data analytics solutions have to be innovative and disruptive, because currently and in the future, the 3 V’s of data; Velocity, Volume, and Variety will help us find solutions, which have never been defined or designed.

Organizations may be forced to carve out a separate team directly reporting to the CEO and the board, creating a visible change in the mindset and the culture of the organization to embrace analytics and become a differentiator in the industry.

The sad truth though is that you will find few companies, which are already on this path and reaping the benefits of their investments. It is time to stop being risk-averse and invest in data analytics, as this is where the future lies.

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