Analytics India Magazine got in touch with Hareesha Pattaje, the managing director of Synechron, to get his views on the biggest challenges that analytics industry faces today. With over 20 years of expertise in IT services, program delivery and client relationship management, he is responsible for global delivery of Synechron’s software services its major clients. He has also played a pivotal role in delivering key Innovation Programs at Synechron and is counted as a top leader in the software delivery space.
Analytics India Magazine: What are the three key challenges you face being in analytics industry?
Hareesha Pattaje: Data and analytics are a rapidly changing part of almost every industry today. With digital transformation in the forefront, big data analytics has become an important part of the overall business strategy. Data analytics is at the core of all the disruptions currently underway in the business landscape. Some of the key challenges that we have observed while working with our clients are:
Strategic Alignment: One of the biggest challenges is convincing traditional companies to move to a data-driven decision-making process. The best way to overcome this is to provide use cases to the customer highlighting the impact data analytics can have on their business. Synechron typically engage our domain experts and business consulting resources to help our clients get past this hurdle.
Information Maturity: Analytics solutions are only as effective as the maturity of underlying data. Data platform implementations often struggle due to low quality and insufficient data. This usually happens as a result of lack of clear data source definitions or complexity of existing data. During initiation phases, our business consulting teams help clients identify clear requirements in terms of mapping right set of data sources and different patterns associated with it.
Stakeholder Commitment: Apart from the fact that data analytics solutions enable enterprises to pave a path for business process transformations, it also requires a lot of involvement and upfront commitment from domain experts to define future business processes driven by analytics platform. Many service providers and analytics platform builders do not consider this as a key aspect while starting new initiatives and suffer down the road on their journey with the client. We identify and engage key stakeholders and ensure the right commitment is obtained from the client side while defining the analytics roadmap for them.
AIM: Talent shortage is often considered the biggest challenge. What are your thoughts about it?
HP: In our opinion more than the shortage of talent, the industry is facing the challenge of mismatch between supply and demand of right skilled talent. On one hand there is an abundant supply of existing resources who have domain knowledge and experience needed for enterprise implementations but have outdated technology skills, and on the other hand, there are a fresh set of resources coming out of colleges every year. Out of this very big pool, one needs to find the right fit for the challenge at hand. A lot of universities now offer specialised courses in data analytics to help bridge this gap. Businesses today believe in investing in their existing resources as well as acquire talent from the market. They regularly run intensive training programs to cross skill and upskill our existing workforce to ensure availability of right resources for our customer engagements.
AIM: What are the key challenges while setting up analytics and AI startups?
HP: Although Synechron does not fall under this category, we see challenges for analytics and AI startups in various areas. We often notice that most startups are unable to classify them as an AI venture and present a strong case study on the value they bring to the table for investors, which creates issues in securing funding. Secondly, the highly unpredictable structure of AI as products pose another challenge for startups if they are lacking in proper understanding and right talent. Creating a generic AI platform product that can cater to various domain and industries is again a major challenge for startups.
AIM: What is the biggest challenge in carving an AI roadmap — budget, talent or senior management buy-in?
HP: All the points mentioned here are the challenges in carving the right AI roadmap, however, the main challenge is to identify and demonstrate the business case leaving aside the hype and expectation around AI. An AI Roadmap should clearly be relevant to the business scenarios and align with the ecosystem one is operating upon. This will help an organisation to get the management buy-in, budget and clients buy-in too. This will also augment the process of creating and retaining the right talent to cater to the business.
AIM: What are the biggest challenges in moving from pilot stage to production stage?
HP: Creating the synergies between the ideation and the operationalisation of an AI solution and platforms and taking the holistic approach towards a business case seems to be a major hurdle in elevating your pilots to production. Creating an analytics solution and platform that matches expectations of various stakeholder groups is a key challenge as they generally will have a different mindset and have different priorities, for the right reasons. Groups that drive ideation and new initiatives mainly focus on the disruption and transformation aspect of the solution whereas groups that manage application and platforms in production are more concerned about non-functional aspects of the platform like stability, performance and maintainability to name a few. Teams and solution providers who do not take these aspects in consideration early, suffer either a major rework or the solution getting shot down later in the game defeating the business purpose and causing an increase in sunk cost.
AIM: What are the challenges specific to the industry/domain that you are working with?
HP: Data and analytics including many topics such as data science, data lakes, and data visualisation is of growing interest – not only across banks – but also across business divisions and support functions. Given this, banks are looking for ways to overcome internal silos and leverage their data analytics capabilities across the organisation. Banks are also now changing their strategies from being “Customer Focused” to “Customer Centric” and advancement of technologies have opened a renewed challenge to derive meaningful insights from the vast amount of data received from multiple channels to help them predict and respond to the changing consumer needs.
AIM: How is the tech industry grappling with finding the requisite skills to beef up the bench strength?
HP: The entire tech industry is facing the challenges including managing and retaining the right talent. This indeed is a very big challenge finding the right kind of resources with the depth of skills required as there is a shortage of analytics professionals because it requires a unique blend of expertise in areas such as mathematics, computers and domain. Most organisations nurture the talent they have and reskill them to match the market requirements. In fact, they are devising internal training framework which collaborates with educational institutes to ensure parity between skilling programmers and addresses the industry’s requirements. Leading players are customising training frameworks and infrastructure and collaborate with recruitment partners. Furthermore, they have a sharp focus on cross skilling and upskilling of our resources through our training modules like Analytics, Artificial Intelligence (Python, NLP, NLG, BOTS, Robotics), Machine Learning, Big Data and Cloud to name a few.
AIM: Ways to overcome the commonly faced challenges in the industry.
HP: Service providers and analytics platform builders should take a holistic view of their offerings and align them to client requirements. Businesses need to provide end-to-end services for building analytics solutions and that have focus on the core areas of business. The specialists need to engage with clients right from the ideation and to the design phase, define the path to production and help clients implement the solutions.
AIM: How does one decide what part of the IT budget should be allocated to emerging tech — ML applications, AI-based products?
HP: In today’s world, with the potential disruption that new technologies like AI and Blockchain can have on the future of organisations, the leadership team is faced with a dilemma of prioritising today vs future. Technology is now deployed in every business function, but the investment varies. Unless a business has a clear innovation strategy in place, attention to short-term burning problems take precedence and allocating resources and budget to long-term innovation initiatives often remains unaddressed. We have typically seen companies allocating budgets ranging from 5% – 15% to innovation projects based on their focus areas.
AIM: What performance metrics are used by the C-suite to measure the business outcome — growth in revenue, improved business margins or other factors?
HP: Organisations typically track investments in these areas and compare it against innovation project investments to new product/service rollouts, revenue and margins coming out of them as a result of technology transformation effectiveness. Another important factor that the leadership teams consider is the impact of not doing the investment on the future of the organisation due to potential disruptive nature of these technologies. In some cases, there can be a major impact and result in an organisation losing market share to competitors and products/services offered can become redundant in the marketplace.
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