Data and Analytics has increasingly become the “secret sauce” of organisations across the board. Today, service providers are consolidating their big data and analytics (BDA) capabilities into one main service line and are adding AI capabilities to their portfolio to broaden data-related services and compete with their peers effectively. Currently, in its fifth year, our Data Science Leaders Outlook in India 2019 in collaboration with Simplilearn takes stock of the analytics landscape in India and how enterprises have moved up the analytics maturity index. What was once viewed as a competitive advantage is now powering the core operations and helping companies launch entirely new business models. Analytics and Data Science has changed the dynamics of the industry, spawning a winner-takes-all market.
The two key transformational changes over the last five years in analytics domain have been companies beefing up the technology infrastructure to capture more value from data and the rise of AI. Technology has taken a massive leap forward in the last few years with AI becoming embedded in day-to-day processes. Today, Machine Learning and Deep Learning has found use cases across the sector and their applications are now powering product recommendations, language translation, virtual assistants and image recognition.
Key Takeaways
- All respondents expect the demand for Analytics at their organization to increase over the next 12 months
- Analytics is growing more mature and leaders’ sentiment outlook continues to be high this year. This result is consistent from last year
- Across the board, companies report that finding the right talent is the biggest hurdle
- Companies are open to collaborations with technology incubators and startups that give them access to IP, proprietary technology platforms and talent
Maturity Level Of Data Science Adoption
We asked respondents to rate the analytics adoption at their organizations on 3 levels of increasing adoption rates – early stage, mature stage & advanced stage. A majority of organisations have climbed up in the maturity index and are taking advantage of their scale and data to aggressively build new business lines. Maturity indicates they are deriving more benefit from their investments.
- A majority of respondents (38%) believe that their organization is at an early stage of adoption
- An almost equal number believes that they have reached a mature stage if not very advanced
- 23% believed their organizations is at an advanced stage in Data Science adoption
Data Science Hiring Plans
Next, we asked leaders about their analytics hiring plans for the next 12 months. With demand for data scientists outstripping supply, hiring Data Science talent poses the biggest challenge for organisations across the board. Report indicates that companies are actively looking to increase their bench strength.
- 87% of decision makers plan to increase their analytics workforce in next 12 months. This is almost in line with last few years – 2018 (90%), 2017 (87%), 2016 (94%)
- 12% leaders say that their current analytics strength will remain the same in the coming year
We use the hiring plan information to compute the Net Sentiment Score (Calculated as difference of % respondents with plans to increase hiring and % respondents with plan to decrease).
- Net Sentiment Score among analytics leaders in India is at a five year high of 85%. Last year’s score was at 58%
- Overall, Analytics leaders in India exhibit a strong positive outlook towards the industry this year
Key Strategic Decisions
We asked our respondents about the key strategy decisions that they plan for the coming year in order to grow their business. With data being perceived as a formidable advantage, leaders are aggressively investing in data infrastructure and analytical talent to capture more value.
- 65% analytics leaders emphasise “growing the team size” as the top priority for the coming year. This is much higher than a year before at 45%
- 62% are planning to collaborate with external partners, almost in line as last year
- Evidently, most organizations are increasingly getting inclined to grow the teams internally than outsource their Data Science work
Key Challenges
- ‘Recruiting and Retaining Analytics Talent’ continues to be the biggest challenge faced by Data Science Leaders in India
- 58% decision makers believe that ‘Unavailability of Analytics Talent’ is the major challenge that they face. The percentage has gone down from last year at 70%. Clearly, there’s more talent supply available right now in the industry, but the challenge is still top of mind for more leaders
- 50% of leaders believe that ‘Little knowledge of analytics among customers’ is a major challenge for them. This remain the same from last 2 year
- “Procedures/ Processes not standardised” is the third largest challenge faced by the analytics deci- sion makers. Almost 35% of leaders believe to face this as the biggest hindrance to their business
- Few leaders believe that the data science buzz is dying down – just 2%
- A majority, 52% respondents believe that execution speed of algorithms is challenge for them
- 35% believe that it’s not really a a challenge for them
The Talent Crunch That Still Exists
As we enter the fifth year of surveying analytics leaders’ sentiment in India, it’s understandable that some trends will continue to exist. In this case — the talent economy in India remains unchanged with companies continuing to face a supply gap of analytics talent. As organisations move up the analytics ladder, business leaders have to brace for a new challenge — bridge the capability gap in their organisation. Enterprises have to work towards building the next-gen workforce that has the skillset to support new business models and drive better outcomes.
Another key hurdle companies face is that there is no clear set of capabilities for today’s data-driven roles since different problems may require different skillsets. Most organisations are cultivating talent in-house, but what’s required is a holistic, multi-pronged approach to build industry-relevant skills and competencies. The need of the hour is to invest in high-impact programmes and certifications in order to meet their business requirements. To capitalise on the growth wave, it is imperative for companies and business leaders to invest in training the existing workforce in order to meet their business requirements.
Conclusion
Data Science offers the biggest opportunities to companies to create value and organisations are increasingly prioritizing it to gain market share. As market opportunities explode, organisations are hungry to use data to grow and improve performance. To achieve this scale of transformation, organisations have to make major pivots in terms of data infrastructure, capabilities and talent.
A key takeaway is that companies are now working with technology incubators, startups and external business partners to gain access to proprietary technology platforms, IP and in-demand talent. External collaborations also allow them to gain critical digital competencies, expand their business models and scale fast.
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