By Shammy Narayanan
With an enviable paycheck and proximity to the power centre, the life of a data leader may look glamorous, just as driving a dreamy sports car. For the onlookers, these cars are sinfully seductive with sleek designs, powerful engines, and luxurious interiors. However, while driving through Atlanta, the pothole capital of the US, you would know it’s not an endearing experience, but an enervating one. When it comes to Enterprise Data programs, more than 99% of budget is invested in products, licenses and tools. But what truly matters is people and process, which gets a meagre 1% attention. This imbalance tilts the balance leading to stress and setbacks. This blog is a redacted personal narrative on the struggles of a data leader and possible steps on how to navigate this complex maze.
Who Owns the Data: It’s easier for a camel to pass through the eye of a needle than to accurately pinpoint the data owner within a large enterprise. It’s a never-ending conundrum of who owns and cleans the data. Is it the application through which the data enters the system? Or is it the application that processes/consumes it? Since bad data is an indisputable indicator of the quality of applications, the data team invariably ends up policing, patrolling and pinpointing the hollowness in the design leading to strife and struggles. Good luck in adjudicating such ceaseless conflicts, as it will undoubtedly ruffle the feathers of influential application owners and put you on their “Watch-Out” radar.
Talent Retention: The most formidable challenge of any data leader is the relentless attempt to retain the best talent. Data skills are evolving, and attracting “In-Demand” skills demands a fresh approach to compensation and engagement. Trying to fit the traditional yesteryear’s talent model to attract future talents is like expecting “Penguins in the scorching desert ” If an organization continues in denial mode and expects a data leader to acquiesce and accept such a flawed strategy, then it needs to be prepared for a minimum of 2.5x attrition. Offering free coffee, throw-away goodies and sponsorship for quarterly team dinners in the name of engagement will not work miracles; they are like “Dipping a toe in the puddle and expecting to swim across the ocean.”
Empty Words and Hallow Promises: As data evolves, surrounding toolkits change equally. Whether it’s tools related to Data Catalog, Synthetic data, Data lineage, Security, or Data Quality, mom-and-pop shops are mushrooming every day, and so are the vendors who wield unbelievably compelling marketing spiels. This sales team are often a set of “Yes masters” who will mindlessly bet on their tool’s capability even to solve a nagging problem in your adjacent flat or your child’s homework. A “Theory-Only” leader can be easily hoodwinked and tempted to buy such products. That’s the genesis of the downfall; with no industry baseline and proven results, data leaders should be wickedly smart in intuitively understanding the product and cognitively evaluating it against the operating environment. When a tool fails, a tactically worded contract may still salvage a proportion of your invested dollars, but the business loss and your personal brand can never be redeemed. Remember, such a downfall is the fertile feeding broth for application leaders waiting to frown and quickly rebrand the tool failure as your personal failure. That’s the undeniably “friendly” office politics for you!
Beyond the Realm of Reality: Creating a revenue stream leveraging data is the dream of every CxO. While such lofty ambitions are admirable, it becomes daunting when it has to be accomplished the very next day. Get this, most organizations utilize less than one-third of the data available in-house. The primary goal should be to collate and derive value from the unused data first. Let us first learn to fly, then we can soar into the sky, but who bells the cat? A pragmatic response inevitably will draw executive wrath, so a data leader should know how to differentiate between “Hankering and Hallucination“, and effectively balance like a trapeze artist who can perform acrobatic maneuvers while suspended in the air, but at no point in time losing sight of the ground.
Revolving Doors: The vast majority of the Data Programs remains hidden in shadows, aching to materialize as envisioned within the confines of time. It’s a daring gamble worth millions, where the leaders of data bear the weight of blame for colossal setbacks. The life of a Chief Data Officer resembles a fleeting spectacle, akin to fireworks illuminating a moonlit night — a mesmerizing display that captivates with its brilliance, only to fade away all too soon.
Enumerated experiences are mere ripples of the vast ocean of challenges that engulf those who dare to lead with data. As time unfolds, the essence shifts from the realm of technology to the realm of intuition, where common sense becomes the guiding light. It is an intricate dance of deciphering the unspoken and adhering to the unwritten. This treacherous path, laden with hidden dangers, lacks a user manual to illuminate the way. Though it may inspire trepidation, it is the allure of unsolved enigmas and unguarded risks that renders this role attractive and lucrative. So, if your ambition lies in the realm of data leadership, it demands more than mastering ETL and transformation strategies; it necessitates a deep understanding of human psychology. With the wisdom of two decades engrained within me, I have yet to witness a leader emerge unscathed from this perilous Bermuda Triangle, for it is not solely the domain of technical prowess but an intertwining of fortitude and finesse.
Shammy Narayanan, is a Practice Head for Data and Analytics in a Healthcare organization, with 9x cloud certified he is deeply passionate about extracting value from the data and driving actionable insights. He can be reached at firstname.lastname@example.org