Separator

Digital Transformation & Big Data Can Be A Big Problem Unless You Change Your Leadership Culture!

Separator
Ajay is an Entrepreneurial business leader & Leadership coach with 30 years of experience in large corporates & startups. His coaching and mentoring approach blends his CXO experience of large Corporations like HDFC, and Shopper Stop with founder experience of new age Digital Analytics organizations like Hansa Cequity. Ajay brings in his handson business leadership insights, with the curiosity and vision of a new age startup founder in his Coaching and Mentoring work.

Ajay is a Professional Certified Coach (PCC), accredited by the International Coaching Federation (ICF). His Leadership Coaching supports senior leaders to find their next breakthrough and equips them to ind a pattern in a random business world.

When I was the CMO at HDFC bank, we spoke reverentially about data in the terabytes. And today data volumes have multiplied at a breath-taking pace!

Now, IDC predicts that the “global datasphere” will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025.

In his book, “How to Create a Mind”, technologist Ray Kurzweil estimates that a human brain can recognize 100,000 patterns. But consumers are producing a huge amount of information by the minute & our minds may just not be fast enough. “Big data” is what they call this data deluge & it has become the sexiest word in business in a very short time. Big data & Digital transformation are at the heart of many large new investments that companies are making. Digital transformation is not a new concept, but it is notoriously difficult to implement.

Despite the constant talk about how data will transform companies, not enough attention is being given to the company culture needed to make such a transformation.

And most companies struggle to create a strong, data-driven culture.

The culture of an organization is anchored in the following four elements.
•Mindset
•People
•Processes
•Systems

These elements in combination are what make an organization work in its unique way. Cultural norms are deeply held beliefs about the way an organization should work. Each of the above parts gives us a hint on what the culture is all about. For example, the mindset at HDFC bank was very much data-focused. In my days at the bank, we had the famous 1:3 rule which guided us on every investment made within the bank-every Rupee had to give a 3 times return else the CFO would reject the proposal.

A decade ago, people didn’t use the words: Data, Big data, or Analytics as much as they do now! Today data is the new oil & everyone reminds you about this constantly! And yet too much of something can be an issue & individuals have to learn to manage this data deluge concerning data reliability & data privacy! Unless a customer-centric culture is deeply embedded in the company, this sensitivity towards customer privacy will not be there.

New companies like Tesla have surpassed legacy brands where leadership has resisted adapting to new cultural and technological realities. The data & trends are providing these legacy companies enough insight & they have access to this as much as Tesla does. What’s holding them back is that while their culture provides the foundation for organizational and industry stability, it is also the force that keeps their leaders anchored in old ways of doing business.

But new digital technologies coupled with consumers’ changing wants and needs disrupt legacy beliefs. Even 10 to 15 years ago leaders might have said that making things was much more critical as compared to matching buyers & sellers. That core belief has been shaken to its core, as subscription and platform models powered by data and AI began to fuel the most powerful companies in the world today Amazon (with Prime and its massive supplier network), Apple (with its iOS developer community), Facebook (with its billions of users), and Google (with its search and matching algorithms). So the culture of arrogance because you may be a market leader today will for sure be disastrous unless new leaders can emerge who can help legacy companies re-look at emerging technologies.

And now it is estimated that we already have around 50 billion devices wirelessly connected to the internet. At the same time, from 2012 to 2017, machine to machine traffic has grown an estimated 24 times, a compound annual growth rate of 89%. The majority of data will be collected passively through machine to machine transactions. Although still projected to grow rapidly, the overall proportion of data actively generated by individuals will decline. So a lot of data about us as customers will be passively collected without us even knowing about it. With their Android and iOS mobile operating systems, respectively, Google and Apple know the location of every customer's Wi-Fi-enabled phone far more location data than any other company could access.

The growth of IoT & connected devices will affect every walk of life. There is no doubt that this deluge of data can have huge positive implications for society, business & also the individual. Some of the societal benefits can have huge implications. As an example, strategically placed acoustic sensors that pick up gunshots have shown that previous assumptions on the level of gun activity in certain neighbourhoods were wrong. Police departments operated on the assumption that when shots were fired, 80% of the time someone called 911. This percentage could be as low as 20% of the time, a fact that was revealed when these sensors were able to pick up actual gunshots, providing local police with new information and insight. So this way of thinking about data is really about finding ways that improve the decision-making process in any company.

Today's businesses have the opportunity to work with all sorts of data: contact details, location information, purchasing history, social and professional contacts, browsing history and online behaviour, workouts, store visits, television preferences, and their personal views much of which is gathered in real time. big data is fundamentally allowing businesses to "mash-up" both structured and unstructured data, from a host of sources, sites and sensors.

And yet with so much data everywhere, the danger lies in trusting the data analysis implicitly without grasping its limitations and the possibly flawed judgments of the people who build predictive models.

And all this data is leading to huge privacy issues for all of us. Former US Vice President Dick Cheney modified his heart defibrillator to disable the wireless feature due to concerns that his device could be hacked remotely. In the final analysis, all of us need to be aware of Privacy, Reputation, and Identity in this Digital Age, where we are leaving exhausts of our data out there for many to see, analyse& act upon.

And this data deluge, for most companies, is like having sections of a jigsaw puzzle in different rooms, but the puzzle keeps growing without a “puzzle master” integrating all this. The analyst, like the “ringmaster”, is the “puzzle master” here & she needs to think very differently to do this. We don’t need more data we need the correct interrelationships between data to be established & then we need “Big execution commitment” to make the data matter, by bringing decisions closer to the front end of every business. But this needs a large change in the cultural fabric of a company.

Give some thought to the following attributes of company culture and whether they are barriers to change or enablers of change at your organization

Source: Northridge Group
While this does not mean that a company has to completely overhaul its culture. I feel it has huge implications in exploring newer ways of doing business. We should evaluate more flexible employment contracts & more intense partnerships with other companies as the first place to start making changes.

Not every company needs to manufacture or add value at each stage of the value chain.Apple has done this well by creating a large web of outsourced partnerships. The world is changing in another significant way companies are willing to share information have started to access data that is available publicly. Open data public information and shared data from private sources can help create $3 trillion a year of value according to Mckinsey. And some new age companies(e.g.: Uber) do this very well. We can call thisthe notion of "profitable data sharing". They do not hesitate to share data across partners to ensure their customers get a kick ass solution. But for this, you have to shift long held beliefs about "insourcing" everything.

Lanham Napier the CEO of Rackspace had this interesting comment:"Organizational culture has a strong impact on the efforts of an organization trying to adopt big data, machine learning, and network based business models to catch up with today's leading companies. The reinforcing loop culture is the foundation of that race. If leaders truly want to derive meaningful business benefits from analytics and platform models, they must proactively address their own core identities before trying to introduce large-scale transformation initiatives.

Most leaders simply don't want to put in the work and examine their core beliefs, and neither do their boards. The fear is that they will become destabilized".