Can an age old concept of milestone based sequential puzzle solving game of TreasureHunt be applied in a simulation based learn-by-doing environment?

Why did we build Analyttica TreasureHunt?

We are in the middle of a data explosion that started decades ago with the advancement of technology, computing, storage, and communications. More data is being created in a year than in the entire previous history of human race. They say data is the new oil; the oil that promises progress, fortune, prosperity and development. But, what can one do with oil, if there is an inability to scale up powerful engines? The metaphorical engines in the context of this new oil, are perhaps the data analysts, business analysts, and data scientists, who play a pivotal role in helping businesses grow and optimize. Analysts lie at the confluence of three streams – data science skills, industry/domain understanding, and technology advancements – each of these are essential factors for an analyst to drive tangible and incremental business impact, using data-driven solutions, with an ability to create a simple bridge for the business manager from “data to impact”.

A couple of decades ago, I was asked to build a world-class analytics organization for a global financial services firm. At the time, analytics wasn’t as widely recognized a field as today, and was considered more of a support function with MIS creation. Working across geographies and over the years, I have been a fortunate witness to a fascinating, almost overwhelming, transformation of this strategic ability, perhaps a case pointing to the fact that analytics is not a “process or a tool”, but is in fact the core element of a “culture” in an organisation. What has however remained fairly consistent, is the “inability or incapacity” of analysts to keep pace with the emergence of new data, continuously improving technology and techniques, automation and machine learning, and complex business problems. On the other hand, the impact of analytics on the bottom line has remained imperceptible even to some of the most successful organisations. Today, leaders across the world continue to concur to this observation. And a large part of this issue arises from the fact that the bridge from “data to impact” is not effectively communicated or implemented by the analysts, primarily driven by a lack of “Business Contextuality”.

This challenge existed decades ago, and still runs at large. Analyttica Datalab was set up in 2012 to take this challenge head on, largely  driven by “experience” rather than “technology” or “process/tools” alone. By definition, an analyst should be considered as an income-generating asset by an organization. An analyst should be able to generate tangible business impact and drive future strategy. When this mix of tangible and intangible outcomes are delivered, an analyst is said to have created “value” for the organization.

So why do analysts still struggle to create value today?

Value creation, in many respects, occurs through insight generation, through an ability to connect the dots, through using data points to interpolate, and extrapolate, and use substantial “art” in addition to “science”. The existing approach to learning in this field, which is primarily focused on instruction based learning a new coding language and/or mastering tools and techniques, rarely allows for those qualities to foster, and nourish, leading to micro-retention of knowledge over time, and severe distortion of business elasticities viewed from an analyst’s versus a manager’s perspective. For example, to connect the dots, one needs to be aware of the universe and the constraints they are operating in, as to exactly what the “dots” are, before proceeding on how to optimize “connections”. An emphasis on “application and business context”, crucial to connecting the dots, is perhaps missing to a large extent, and is left to “on-the-job experiences” over the years.

Compounding this challenge, is the fact that the world of data and technology has been rapidly evolving. Because of the dynamic nature of the industry, even highly competent analysts struggle to keep pace with moving market conditions, business context, and rapid evolution of new-age tools and techniques. Businesses are experiencing many models that fail in short times, sluggish innovation in usage of data, and limited upside for investing in trained analysts; not to mention the huge impact of “knowledge attrition” when talent moves/attrites. This knowledge attrition is not so much as a lack of knowledge management tools, as is the know-how associated with an analytical thought-process and approach, with the departure of talent.

An ideal scenario to address the above would have been direct leverage of analytics talent for businesses to experience value from the practice and its ability to significantly impact the business metrics. A synergistic confluence can be created between aspiring/existing analysts and the businesses as the consumer of their intellectual prowess and data-led predictability patterns. Analysts are inherent problem solvers, and they thrive on solving challenges that lead to asymptotic convergence of solutions, through iterative approaches of scientific decisioning. This coupled with a high degree of “Contextuality” can be created via a heuristic platform to all self-motivated learners, students and professionals alike, to learn and solve real business problems using traditional as well as new-age analytical techniques, and generate incremental value to businesses, thereby making them data savvy and insight hungry. The age-old game of“treasure hunt” via riddles/puzzles that ultimately lead to a “treasure”, is testimony to this fact, and can be simulated in a unique way in the field of “Contextual Analytics”. If successful, this can provide a high degree of “experiential learning”. Herein lies the genesis of Analyttica TreasureHunt? (ATH). The name “TreasureHunt” is an ode to this favorite childhood game, which helped many learn one simple fact of life – there is nothing more rewarding than “learning by doing”, versus purely “learning by instruction”.

Embarking on a highly challenging but fulfilling journey, and immersing itself into full-time technology enabled platform development, encompassing people, expertise, experience, success and failure, Analyttica is proud to introduce an “experience” that can transform the ability of analysts to evolve themselves into impact-generating levers for the businesses; and businesses in-turn can view analytics as the indispensable inputs to critical decisions. Analyttica believes that this is the most advanced heuristic platform, fueled with powerful machine learning algorithms and AI, that helps one become an “exponentially better analyst”, faster. Organizations will benefit hugely in terms of knowledge immersion and retention by permanently capturing the “thought processes” of analysts via their “approaches”, as much as their “analytical outputs”. This is a tremendous help in ensuring successful audits and compliance as well for all organisations.

ATH learns how one learns, makes one’s learning curve steeper, and makes concept retention and recall simple, all the while ensuring that one operates in a simulated business environment with real data. ATH focuses on three key elements – Learn by Doing, Apply via Experience, and Solve Real Problems immediately. ATH has the potential to transform the landscape of data science learning and application in a business context. The analyst then becomes a strategic asset to the business, because he/she is “sculpted” to driving strategic business impact.

Analyttica TreasureHunt? can be a true partner in this transformational journey of analytics and of businesses! Learn.Apply.Solve! Enjoy the Journey!