Big data – amplified through sharp technical skills and new technologies – has become central to the success of both innovative startups and incumbent players alike. But has the burgeoning technological-revolution driven by artificial intelligence and big data effectively shaped executive management and leadership strategies? Has it trickled … to the top?
It’s safe to say that the recent technological tides shaping our consumer products, experiences and expectations have left organizations scrambling to develop digital/data strategies that will position themselves for the future. A vast proportion of this has translated into hiring additional skills – i.e. demonstrated by data scientists – all the while praying that the necessary transformations work themselves out.
The gap: the very data attributed with delivering exponential innovations must also disrupt traditional leadership practices. If at first product-driven tech companies can achieve unprecedented success despite despicable leadership, it’s certainly not for long (read: Uber’s reputation problem or Why Blockbuster failed). Big data must also inform corporate leadership such as monitoring the business landscape, setting priorities, managing objectives, measuring performance, organizing teams, and delivering winning results (at all levels).
The benefits of big data are not exclusive to data science
In 2012, the Harvard Business Review published a famous article called the “Data Scientist” whose central tenet continues to reverberate across industry today. If you’re struggling to recall exactly the details of the article, that’s perfectly understandable, and you’re very likely not alone. To quote one of the author’s himself, Tom Davenport, “Nobody remembers the title or much about the content of the article, but many remember the subtitle: “Sexiest Job of the 21st Century.”
Five years later The Economist published its own influential article of a similar theme but this time swapping the allure of attraction with an analogy for the lucrative: “The world’s most valuable resource is no longer oil, but data”. It was around this time in 2017 – mere months before the explosive events between Facebook and Cambridge Analytica would transpire – that most people took note of the role big data plays in everyday life. In fact, it was virtually impossible not to have some awareness (however vague) around the business of big data; the technological innovations that depend upon it and the corporate giants eager to harness it.
Eight years later and the world is in the midst of explosive growth in the demand for actionable big data (both as a commodity and skillset). The Data Scientist continues to be one of the highest paid and in-demand professions today; ambitious students are dreaming of innovative careers in data foregoing traditional definitions of success like “Investment Banker” or “Corporate Lawyer” (though I suspect these are still highly sought after jobs, they’re just not, let’s face it, as cool).
In sum: everyone and every company is transforming into the ‘data-driven enterprise’. It’s a catharsis that has no bounds and yet the signals around leadership’s own necessary transformation are less obvious. Perhaps this is unintentional, or an innocent oversight caused by hype and hyperbole around the gains promised by data science and big data.
Big data must also disrupt management practice and inform leadership
In the same HBR issue which published the famous “Data Scientist” article in 2012, HBR was already dedicating the central theme to “Getting Control of Big Data: How Vast Streams of Information are Changing the Art of Management” (Read: Big Data: The Management Revolution).
At the time, HBR was leading a conversation connecting two interdependent revolutions. The first: the latent potential inherent in data itself – discoverable only when patterns, correlations, and associative relationships are recognized, utilized and scaled, mostly by data scientists; and the second: the unavoidable role that data would play in managing and operating all levels of business from executive leadership to recalibrating the workforce.
Data scientists have become central to innovations spearheaded by the likes of Uber, Google and Facebook, but let’s also acknowledge they’re receiving a lion’s share of good publicity in what is really data-driven innovation coming from a community of practice known as “analytics”.
In truth, it’s the dynamic interplay between data scientists, data engineers, and business intelligence analysts making up analytical clusters across organizations which are vital to the success of business in the modern (digital) era.
The analytics community of practice and the rise of the Data Strategist
Global consultancy PwC reports that “Data scientists, data engineers and business analysts are among the most sought-after positions in America” and this really comes as no surprise. In fact, PwC is a little behind the times in this article failing to include the data analyst/business analyst hybrid of “data strategist.” The proliferation of this role is in line with the very thesis of this article and is quickly becoming a highly sought after talent set.
This is because leadership is blind without big data informing the very indicators it depends upon to manage effectively. Painting a portrait of the business and its operations in broad strokes is not sufficient either. Leaders need to capture the granular details – the “nitty gritty” – if they hope to get any actionable intelligence.
Never has data been so vital to leadership as it is today and this is where Key Performance Indicators make their grand entrance. The concept is archaic but its design and delivery has transformed. Big data now offers management diverse perspectives and insights that couldn’t possibly be delivered before were it not for data collection, processing, and visualization. The ability to signal shifting trends, drill deep into the data for new tactics, predict behaviour pivots or identify new opportunities are just a handful of worthy examples KPIs offer. It could be catastrophic to a company even at its height of success to miss the mark on any of these measures.
All this is largely because technology has equipped even the smallest startups with explosive leverage and opportunities to compete alongside giants. The margins for profit and marketshare are dwindling and as customers seek highly-tailored innovative new products and experiences, their loyalties are more flexible than ever before. And companies are feeling the pinch. Leadership can little afford any blindspots over the landscape in which it operates as well as being accountable to timely, transparent and responsive feedback on the success or failure of its strategy, initiatives or risks.
The benefit: KPIs (Key Performance Indicators) offer leadership at all levels clear, robust, and transparent performance measures against strategy and execution doubling down as a team/company’s early warning signs of both trouble and opportunity. KPIs are designed by leadership and informed by data.
Key performance indicators: their design, development and delivery
The same data that is pipelined into recommendation systems, predictive algorithms and customer segments can be repurposed and packaged to inform management on the successes or failures of its operations. At the same time, the stack of skills that define data engineers, data analysts and data scientists are predominant in the development and delivery of KPIs by data strategists or business intelligence analysts.
An important distinction to be made on KPIs is in their design. Rather than being largely determined through experimental methods such as statistical analysis championed by data scientists, KPIs are largely designed by leadership who communicate to data engineers, data analysts and data strategists exactly what it is they want to see. These requests are then translated into indicators (the KPIs) which are created in the data and serve to appropriately measure the performance of leadership-driven objectives and priorities. KPIs can also be provide aggregated or detailed views of customer behaviours giving product and management teams oversight into customer interactions with products and services, especially as these products and services are adapted for changing needs.
The breakout role of the Data Strategist is in their ability to best understand the needs of leadership (or even a client) and to communicate effectively amongst them. The data strategist – responsible for developing the KPIs and bringing them into reality – is positioned to understand the perspective of management while also anticipating the intention behind the KPI. Oftentimes data strategists must help design effective indicators because they have a clearer sense of technical constraints and opportunities in the data. Therefore, while KPIs are designed by management they’re generally a collaborative effort. This positions data strategists between both the data and the business offering ample opportunity for growth and development.
Developing KPIs requires a strong technical understanding of both the data and the engineering methods. Once a design has been established, a KPI is developed in much the same way as many other data-driven products. Although some KPIs fail to indicate any performance measures due to limited data, poor performing indicators, or bad quality data, to name a few of the potential issues, there is a natural process of trial and error around indicators before a KPI is established.
One of the most popular data sources behind KPIs are customer, digital or user-generated data. It seems these days that business can’t seem to collect enough information on their customers and their activities. On the one hand companies run the risk of privacy breaches and data hacks on personal information, on the other hand, failing to adapt to the preferences of consumers by collect enough data to create products and services they want, need, or get hooked on.
When designed correctly, updated frequently, and developed clearly, KPIs offer leadership valuable insight into the business – a potentially decisive factor in the success or failure of a team, product or company.