The newest tech on the block, be it Gen AI, NLP, or Blockchain, is making a lot of noise and inviting strategic moves by organizations. Today, every firm is an analytics firm because they want to make decisions based on data. However, companies are turning cautious and focusing on monitoring the ground-level tech impact before making decisions. Given this context, Tiger Analytics, which hires a large chunk of digital natives, emphasizes on making their people understand what they stand for as a business. In conversation with Venkataraman KR, Head – People Development, Tiger Analytics, we dive deeper into the skills challenges they are trying to solve and how they are getting it done.
State of Organisational L&D
Today’s new-gen workforce has consumer-type expectations and short attention spans. This ‘instant gratification’ expectation extends in their roles as an employee and a learner too, making conventional training methodologies ineffective. This poses a unique challenge, where learning organizations must explore what content they can release, to ensure their people are learning something new, and in the format, they like to consume it.
Tiger Analytics espouses Learning as a core value, and provides multiple avenues to get people to participate in learning:
Talent blend of build-buy: Tiger follows a blended approach. A talent-build approach works well for entry-level and early-career talent, while go-to-market works for specific niche talent at mid to senior levels. A significant population joins through campus hiring and go through their Springboard programs (early career learning journeys). In parallel, the organization actively syncs up with external SME partners for certain niche skills. Venkat shares that they are working on a co-facilitation model with both internal and external SMEs coming together. Being in the sunrise industry, 70% of L&D at Tiger Analytics is in-house.
Blended learning: Learners are offered a variety of formats to meet how and where they want to learn. This includes, bite-sized learning, peer-learning, self-paced learning, instructor-led learning, and a hands-on case-study approach wherein a business problem is tied to a particular tech or use-case. Social learning happens through hackathons and case-study competitions.
Digital upskilling: Digital broadly includes Social, Mobile, Analytics, and Cloud skills. Tiger is a digital-first organization, and every initiative is anchored on the two pillars of Analytics and Cloud. Hence, their advanced digital learning programs extend beyond the conventional. Venkat elaborates that while Machine Learning (ML) is a hot skill, their internal Machine Learning Engineering (MLE) program focuses on how to productionise ML models for clients. Likewise, even Enabling Functions i.e. Marketing, HR, L&D, Finance, etc. are expected to understand tech fundamentals through their foundational tech program – Tech 001. Digital is the language for Tiger across functions, whether delivery or non-delivery.
Business-led learning: Learning at Tiger Analytics focuses on the business core – what Tiger is doing and why. Intentional learning forms 60% of the learning pie, while business-specific tactical programs account for 40% of learning (30-35% being just-in-time, while 5-10% being just-in-case learning). All learning interventions are very closely tied to business imperatives, with learning partners assigned to each business practice. While all the Springboard programs are flagship programs, there are also other flagships like ‘Storytelling with Data’. In fact, Tiger Analytics received a Brandon Hall Gold award for one of these programs.
Mentorship and guidance: A robust mentoring program helps drive engagement for entry-level joiners in the first 12-16 weeks. Every new joiner is assigned a mentor from Day 1. This ensures assimilation into the culture, standards and enables the passing on of tacit knowledge. Mentors and mentees have an unsaid system like a ‘gurukul’, wherein senior leaders were mentored by the founders, and there is the habit of giving it back to their junior team members subsequently. This has delivered promising results for us over the years.
Process-driven knowledge management: A strong knowledge management process through documentation, capturing snippets of what has worked in the past, crowdsourcing content, etc. are a way of life (the Knowledge Ecosystem). People come together and run deep-dives (on different work topics) for the entire organization, which are recorded and uploaded, serving as a steady-state repository of how the organization delivers value.
Right metrics: To foster continuous learning, Tiger has done away with traditional metrics like training man-hours. The bottom line is, “How well and how quickly are we enabling our folks to deliver on projects?” and “Are these programs enabling us to meet key business and client requirements in the shortest time?”. The ability to ensure people are deployed and deliver value to our clients is the core metric, and this enables a pull-driven learning approach.
Cultivating a Culture of Innovation and Learning
Venkat believes the following four pillars help build a thriving innovation-centric culture:
Providing a sense of accomplishment to the audience in solving complex problems
Providing avenues for people to socialize their innovation-success and be visible
Offering a way for people to own their successes
Offering people an element of positive surprise and interest
Creating innovative ways to cascade and communicate this is what gets people engaged. Culture cannot be limited to learning alone. Venkat shares that Tiger Analytics doesn’t have high attrition thanks to its good culture. In fact, their attrition is amongst the lowest for such a high-growth sector. One key factor is providing interesting and complex problems for people to solve. People feel engaged by solving cutting-edge problems and delivering industry-leading solutions. Given the right ecosystem, there is an inherent curiosity to learn. Getting people to see what challenges the organization / client is facing, has propelled this curiosity, and therein, Tiger Analytics’ hypergrowth.
Final Thoughts: The Future Outlook
The future of learning shall unfurl at two ends – the organization end and the learner end.
At the organization’s end, it should avoid jumping the gun for any tech endeavours. Leaders often make the mistake of looking at downstream solutions like NLP, AI, etc. expecting immediate impact, without realizing that the quality of data greatly impacts the output.
Venkat recommends an upstream-to-downstream approach, first investing in the right upstream efforts i.e. data warehouses, data pipelines, and data formatting applications / processes. This approach is usually more successful and sustainable, especially when we are trending towards a product-centric and platform-centric based tech strategy. Organizations must adapt their learning solutions to meet these tech trends.
At the learner’s end, better business understanding is a core necessity. In the era of instant gratification, can we enable people to start understanding business problems more? This demands another skill i.e. Curiosity – people need to be curious about the problem one is trying to solve. Given the pace of growth, often the big picture gets missed. Hence, providing the right tech leadership, building leadership skills around business, storytelling, collaborating, etc. are necessary. Even as a tech-first company, Tiger Analytics believes that tech should be a mere enabler. Any tech or tool exists to serve a business purpose, to solve a business challenge. And these tie into human psychology because humans are wired for curiosity.