Learn, Unlearn, Relearn – Key to building a successful career in Analytics

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As futurist and philosopher Alvin Toffler once wrote: “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”

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Given ever-changing societal and professional demands, lifelong learning is recognized as a critical educational goal. Mr. Darwin once said, ”It is not the strongest of the species that survives, nor the most intelligent. It is the one that is the most adaptable to change.” With the advent of globalization, increasing influence of collaborative social technologies and increased mobilization, traditional boundaries tend to disappear and the global workforce pool becomes more skilled and ambulatory, which represents a challenge for people in specialized skill set zone to adapt faster to the changing market landscape to stay competitive. Analytics is definitely the most sought after space to be in, maturing way faster than what most of us could have imagined and as with any budding phenomenon, it becomes imperative for the talent pool to STAY RELEVANT! The ability to adapt to these frequent changes and proactively make changes to your career is what will make a crucial difference to where you find yourself even just five years from now.

Much has changed since then, including the rules for getting ahead. To succeed today you must be in a constant state of adaptation – continually unlearning old ‘rules’ and relearning new ones. That requires continually questioning assumptions about how things work, challenging old paradigms, and ‘relearning’ what is now relevant in your job, your industry, your career and your life.

Agility to learn and grasp new things is the new normal. When the rules of the game are changing fast, nimbleness and the attitude to let go of the old rules and learning new ones is no more a matter of choice but a critical ingredient to sustaining in this highly competitive world. Constantly learning and upgrading your is the key to unlocking your change proficiency, to stay abreast with what’s contemporary and succeeding in an ambiguous, unpredictable and constantly evolving environment. Quite possibly there may be countless things you may end up unlearn in your job.

Not so long ago, Analytics was all about BI/Reporting and to put it simply, the purview was restricted performance monitory and more centric just to the IT business. From a business standpoint, slowly yet steadily Analytics is spreading it wings and becoming more pervasive across other industries (beyond banking and insurance) or other business functions (marketing, sales, HR, legal et al) it becomes imperative for the Analytics practitioners to have a thorough understanding of what they are dealing with in this new Analytics era.

From a functional standpoint, we see the Analytics stack maturing from performance reporting to descriptive, to predictive, to prescriptive analytics today. And when we talk about the typical skills needed to tame these new beasts, it’s a different ball game altogether, not to mention the complexity dimension being supplemented by the data deluge, known to many as Big Data. The question we should be asking ourselves is whether we are equipped sufficiently enough to wade through this sea change and are we in sync with what’s happening on the industry side. Are we equipped well enough and loaded with the requisite skills and sufficient knowledge to survive and succeed in a brave new data-enlightened era? Analytics is no more restricted just to number crunchers and seeks more of inter disciplinary skills cutting across Computer Science, Mathematics, Statistics and Business knowhow, and the much touted buzzword in the industry “data modelling” generally associated with data scientists.

Per se, the key dimensions to mull upon during the learn-unlearn-relearn process are:

  • Communication: How do I ingest data and express ideas/insights for easy consumption by the target audience?
  • Social Reasoning: What are other peoples’ impressions on this? Am I using the right assumptions and are the insights making logical sense in purview of the context?
  • Empirical Reasoning: How do I prove the finding? Are there any statistical research papers/journals etc which back up the stated results?
  • Quantitative Reasoning: How do I measure, compare, or represent it in a meaningful form?
  • Personal Qualities: What personal traits do I bring to this process? Am I equipped with the requisite knowledge/skills to master the situation? Are there any gaps & how to fill in those?

In context of Analytics, learn, unlearn & relearn process would mean:

  • Rethinking Focus and Attention
    • How does our Analysis change with the advent of Digital Phenomenon, omni-channel data in structured/unstructured formats
    • Narrowing down our attention to “data which matters”
    • Learning and practicing new concepts and understanding varied roles in Analytics industry today (Data Assimilators, Data Modelers, Data Visualizers)
  • Participative Attitude
    • Breaking beyond siloes to get exposure various flavors of Analytics
      • Domain Standpoint: Industry-specific data & challenges
      • Function Standpoint: Marketing, HR, Sales, Legal et al
      • Analytics Sub-segments: Data Assimilation or modeling or visualization
    • Getting exposed to platforms like Kaggle to get hands dirty on some open challenges
    • Liaising with Business domain SME’s to get a better handle on a given Industry
  • Information Design
    • How is information conveyed differently, effectively, and beautifully in diverse digital forms?
    • Aesthetics form a key part of digital communication. How do we understand and practice the elements of good design as part of our communication and interactive practices?
  • Narrative, Storytelling
    • How do narrative elements shape the information we wish to convey, helping it to be more comprehensible and actionable?
    • How do we connect the dots and infuse domain vocabulary to make it more relevant?
    • Getting a better understanding of the newer visualization tools at disposal (Qlikview, microstrategy, tableaur, RStudio et al)
  • Business Knowhow
    • Understanding the current trends shaping the industry
    • Uncovering and making a point-of-view on the latest challenges where Analytics has an applicability
    • Getting a hang of newer domain-specific analytics capabilities brewing up

 

Learning is the easiest part, an ongoing phenomenon, where you know what it takes to do the job, both hard & soft skills, and over time get trained to acquire them. Numerous reading material is available on the internet & plethora of academic institutions & training institutes help in getting those requisite skills. Some traits required to do the job well might be inherent to one’s intrinsic nature & may be easier to grasp, others a bit harder due to how our mind is structurally wired inside. E.g. an eye for connecting dots in the data & coming up with hidden insights may be natural to a chosen few but others can acquire that over time with diligent practicing and getting hands-on experience on some projects or even shadowing experts in this space to unravel how their mind works. The most difficult phase is to UNLEARN, where you are attached to some previous experiences and it becomes difficult to forget about your past, your capabilities, your experience to start afresh and new thoughts to RELEARN something new.  It can be as simple as being used to a certain tool/technology, may be excel to quickly run some statistics, to transitioning to Rev R which equips you better to do same in certain regard & has a well-evolved community of data modelers and statisticians. Initial learning curve maybe high but it still benefits in the longer run. It could also mean to certain structural issues of one’s used to doing certain things in a peculiar way which no longer may be optimal any more. Realizing the fact that Analytics is still a nascent industry, with umpteen tools/technologies/platforms sprouting up fast enough, it’s imperative to keep pace with the changing times & stay tuned to what’s contemporary in the market. Adaptability is the key to UNLEARN and RELEARN phase.

People who find opportunities in a changing environment are those who are actively looking for them. The choice is simple: act or be acted upon. Since change is the only constant you can truly rely upon, learning to navigate and adapt to it is not just important to your survival, it’s essential for you to thrive in the bigger game of life. Unarguable, dramatic changes are constantly shaping the business world. Business in such bizarre settings requires shooting on moving targets. The need of the hour is to constantly rejuvenate businesses for enduring strategic advantage mandates an out-and-out adoption of the learn-unlearn-relearn relevant techniques symbolized by flexibility, agility, steadfastness and tactfulness. It requires a gradual and steady process of transformation & overhauling your thinking process. It requires challenging old assumptions and creating newer layers of assumptions. Are you up for the change and ready to scale new heights?

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2 thoughts on “Learn, Unlearn, Relearn – Key to building a successful career in Analytics

  1. Natarajan Chandrasekhar

    Sameer,

    I found this article very relevant.

    Especially for someone like me, with 12 yr of experience in traditional IT services, aspiring to be part of the dynamic & evolving analytics game.

    Could connect well with your key message: Learn – Unlearn – Relearn
    It resonates well with the ancient Chinese proverb “Empty your cup”.

    Regards
    Natarajan Chandrasekhar

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