Making Data Work

Enabling Digital Transformation, Empowering People and Advancing Organisational Success

Edosa Odaro

• Publisher: Auerbach Publications
• Year: 2022
• eBook ISBN: 9781000566253
• Edition: 1
• Topic: Computer Science
• Subtopic: Business Strategy
• Index: Computer Science

In this book, Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption—fear. Fear of the unknown, fear of the intangible, fear of the investment needed and, yes, fear of losing your job to a machine. With his talent for distilling clarity from complexity, Edosa tackles this and many other challenges.

— Tim Carmichael, Chief Data Officer, Chalhoub Group

This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data, information and knowledge across organisations. Yet, rather than being stuck with endless polarising debates such as breaking down silos, it shifts focus back towards the ultimate "to what end."

— Jacky Wright, Chief Digital Officer (CDO), Microsoft US

If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book.

— Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank

A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when—at the end of a critical investment in an artificial intelligence project that had been meant to save money—it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer's production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance.

Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.

Part I Stakes Beyond Borders Encountering Implications of Data Challenges on a Global Scale

1 A Crossfire of Consternation

DOI: 10.1201/9781003278276-2

The hustle and bustle on the London subway platform was what you would expect during a week-day rush hour. Anxious commuters pushed their way forward as trains came and went, allowing only two or three passengers to squeeze their way into the already full compartments at a time. I let myself be carried along with the bodies crowding around me, deep in thought about the day’s meeting with bankers and financial regulators. Although both sides were eager to map out a way forward from the Lehman Brothers crash that had tipped the entire global financial industry into chaos – and both saw data and analytics as key to stabilising the situation, consensus seemed a far way off when it came to implementing concrete strategies.

Still reeling from the clash I had witnessed in the boardroom of BBG, a global banking organisation where I worked as head of data, I looked around me with new appreciation for the increasingly data-driven world we were living in.

Never before had I considered that data could be so critically important for the functioning of the global banking sector, which was worth over 90 trillion dollars, as well as our day-to-day lives and livelihoods that were intrinsically dependent on the effective functioning of the financial system.

Could data really help to get us out of this mess? I wondered as I pulled my coat closer around me and waited for the next train to arrive. I couldn’t quite land on an answer, as my brain was still foggy from a sleepless night, which had come to an abrupt end with the ringing of my alarm at 5:45 a.m.

There had been no shortage of thoughts floating through my mind while I lay awake, with a piece of research about brains I had recently picked up prominent among them. Contemporary science suggests that our brains are the single largest data stores in the world. I had been particularly intrigued to learn that while the neurons – the brain cells primarily responsible for storage, processing and transportation of information – have sufficient capacity to store our movie needs for the next couple of years, the synapses, which are the bridges that facilitate the connections between these neurons, enable an exponential increase in this capacity. They allow our brains to store over 300 years of continuous Netflix video streaming. The Stanford University study did, however, go on to suggest that most of our stored memories lie in a passive and dormant state with only a handful of the most striking events occupying prominence in the front of our minds.

One such indelible memory came from the meeting that was sandwiched between that sleepless night and my journey home.

I had been standing by the boardroom window of one of the world’s largest financial institutions with Fred, one of its most powerful senior executive leaders.

“Most ordinary people, like you and me, are in no doubt that we are not built to last forever,” he said without shifting his gaze from the incredible panoramic view across Canary Wharf, the City of London and the entire Financial District. “Most of us also consider that we would rather predetermine how our financial matters are resolved when we are no more. We take it upon ourselves to write a will.”

As he slowly turned towards me, he continued, “Yet large global organisations like ours – who employ hundreds of thousands of people and manage the finances of millions more – have never stopped to consider what might happen if they ceased to be a going concern.”

It was an incredible analogy to make. Indeed, the big question was how a global meltdown of that scale had been allowed to happen.

Financial crises were not a novel occurrence. For centuries, history has been shaped by economic cycles in which busts followed booms. Records place the earliest notable crisis during the Emperor Tiberius’ frugal rule of the Roman Empire in the 1st century, when he gained fame for employing sophisticated quantitative easing measures to restore order and bring the economy to a point of recovery. There was also the Credit Crisis of 1772. It was triggered by a run-on a bank in London and soon spread across the United Kingdom and into Europe. The 1997 Asian Crisis originated in Thailand, from where it engulfed the rest of the East Asian Tiger economies of Thailand, Indonesia, Malaysia, Singapore, Hong Kong and South Korea.

However, the Great Depression is perhaps the most notable event on record. Starting on “Black Thursday,” the 24th of October in 1929, it lasted over ten years, led to a worldwide economic depression, forced unemployment rates up to 25 per cent, and slashed the U.S. GDP by 50 per cent.

Yet the Great Recession of 2007 was distinctly different. Triggered by the sudden collapse of the U.S. subprime housing bubble and accelerated by the shocking demise of Lehman Brothers, one of the oldest and largest investment banking corporations in the world, it had already led to global stock markets descending into free fall, job cuts being announced in the thousands and unprecedented government bailout packages being released in the billions and trillions.

Given the devastating effects of financial crises on global political economies, national governments and policymakers have long been motivated to pursue policy measures to ensure financial stability. The goal for implementing such policy measures – together with associated mechanisms and tools – was to avoid or reduce the potentially cataclysmic economic consequences of financial volatility. Central banks serve such a purpose – to maintain a stable financial system and mitigate risks of a systemic failure across the financial landscape.

Most national governments establish such financial structures not only to provide an appropriate level of oversight – to ensure that monetary transactions travel securely through the system and are effectively settled at their intended destinations – but also to avert any risk of liquidity exiguity, especially in the event of a financial crisis.

However, despite the abundance of structures and efforts that global economies dedicate to mitigating such risks, I found that nothing could galvanise action like an imminent or an actual failure. Beyond the Great Recession, which seemed to consume our entire attention at its peak, I noticed that an intrinsic relationship between failure and action was by no means limited to the financial sector or the world of work. Instead, it was evident in our everyday lives, in the big as well as the small.

A recent example of this comes from the coronavirus pandemic. There were extensive risk analyses and warnings – including an impassioned TED Talk by Bill Gates – that stressed the need for being prepared and for employing early mitigation measures to avoid the most devastating outcomes. However, most governments and organisations across the globe only took decisive action when a failure was imminent – and when data indicated that the pandemic was at their doorstep.

My journey towards understanding what it takes to make data work took a notable leap forward when I investigated what went wrong in the financial crisis when I pondered how Lehman Brothers could have evaded all the controls of the collection of central banks across the globe. Beyond understanding the connection between failure and action, I was keen to unpick how we can leverage data insights not only for mitigation but also to prevent detrimental events.

It was difficult to imagine how an organisation of the size and scale of Lehman Brothers could actually operate without the sort of basic provisions that most people make to predetermine the resolution of their financial affairs. Explicitly articulated wills, trusts and insurances are typical tools individuals employ, yet it seemed that such planning was left wanting for some of the largest organisations in the world. Contemplated more broadly, it wasn’t just the survival of an individual organisation that was at stake. Instead, its complex financial affairs were suboptimally encoded so that a complicated and difficult-to-untangle maze was left behind.

The news was awash with headlines suggesting that, going forward, financial institutions should be compelled to publicly disclose their ability to pay up and address any liabilities they might have should they come to a situation of inevitable failure where they would need to be wound down. “U.K. banks will have to publish ‘living wills’ to ensure ‘orderly failure,’” one headline declared. It was clear that the Bank of England and other financial regulators across the globe were very concerned about the implications of the failure of large banks for the broader economy. They were desperate to reduce the chances of the kinds of bailouts the taxpayer had been compelled to fund.

As our conversation in BBG’s boardroom progressed, Fred was keen to go beyond disclosure and delve deeper into the broader role of data.

“What is your view?” he asked.

Are you here to convince me that data or AI are the answer, that data can be the ultimate mitigant for future financial systemic failures? And what we need is to funnel all our data into a super-sized Hadoop data lake?

“There is no doubt that data has to play a huge role, and advancements in artificial intelligence would only act to radically increase the utility achievable from data,” I said. “But I think the situation is a lot more nuanced than simply getting access to more data.”

I pointed out that there had been a lot of attention on data by global financial rule-setters in the past. A recent example was the Basel II Framework, which was already in force at the point of the crash. It placed data at the heart of its market discipline reforms – and its three pillars stressed the critical importance of information disclosure to the well-being of the financial system.

“Yes,” Fred said, acknowledging that such regulatory controls and associated data strategies had failed to sufficiently mitigate the risks of systemic failure.

His response made it clear that he was not convinced that data and analytics were sufficient for mitigating the risks of future failures. He was adamant that both the United Kingdom and global authorities should provide credible explanations and rationale for the relevance of any new data or automation strategies.

“There can be little doubt that some of these asks would be inappropriate, unhelpful and unfit for purpose,” Fred said as his frustration was starting to affect his typically calm demeanour. “Another concern is with the viability of some of these requests. The scale and volume of data we are talking about are sometimes absolutely staggering.

“How do you take the data of over 13 million customers, and that’s just current account holders; how do you then take hundreds of millions of individual derivatives and turn that into something meaningful for the regulatory authorities?” Fred asked

But there is likely to be an additional twist. If we are in effect unable to produce the right data in the right way to the right robustness, then that could actually send a message to the authorities that we have further barriers to resolution. This could potentially strengthen the authorities’ view that more activities related to structuring the bank are needed.

He was alluding to a prevalent concern across the banking sector that central banks and their financial regulatory counterparts were convinced that one of the key changes that had to be made was a simplification of the structure of the world’s largest banks. The thinking was that by forcing a restructuring along more historically traditional lines – where the high-street, retail and consumer banking parts were kept completely separate from investment banking or similar functions that were perceived to be more risky – would limit the risk of taxpayers having to prop up failing financial institutions.

Perhaps we now live in an environment where we have to accept that as a requirement for building a successful bank – or part of building a successful bank – we have to make sure we can be successful in its resolution,

he said. “So going forward, we’ll have to look both ways – we effectively have to consider both ‘life’ and ‘life after death’ – and that is difficult for a bank to do.”

Though I did not disagree with Fred’s assessment – that while data and analytics were important, they had previously failed to be the silver bullets for mitigating historical failures – I could not help but think that he was missing something much broader. I had no doubt that such a complex issue required a much more comprehensive perspective. I explained that I thought the bigger issue was not to do with the data or analytics existing in a single organisation or even within individual subordinate organisational business units – but that it was vitally important to consider the much broader implications of visibility and flow across the entire system. In some ways, this was analogous to the scientific findings about our brains: while each neuron is like the internal data stored within a single firm’s system, it is the synapses, which form the bridges that facilitate the connections and flows between firms and the systems that lie within their internal boundaries. I wanted to help Fred see how the effectiveness of this interconnectivity was essential not only for the prosperity of individual organisations but for the integrity of the entire system.

I think regardless of how much information is gathered, how accurate and timely it is, or how much insight can be gained from it, if it is all locked in silos, then we can have a situation where the entire organisation and even the entire system is effectively blind to such information,

I said.

We had been in conversation for over 45 minutes. We talked about many pertinent issues, with some focus on the triggers that had made organisations across the entire financial industry increasingly susceptible to falling victim to Lehman-like tragedies. It was evident that Fred was less than impressed with what he considered the knee-jerk reaction of regulators.

“What we need to realize is that the failure of banks is now on the agenda,” he said.

Rather than seeing it as an exception that might happen, it should now be looked at as something that can – and perhaps will – happen. And so, rather than focusing only on avoiding the inevitable, efforts should also be expanded to considering how we reduce the impacts of such failures whenever they happen.

This seemed a rather shocking admission, especially coming from a senior executive at one of the world’s leading global banks – with a market capitalisation of over 20 billion dollars and total assets far exceeding the trillion-dollar mark.

What made this discussion even more intriguing was the prevalent perspective that there were some banks and financial institutions that regulators and central governments could not allow to fail. I had recently come across this controversy when I found myself caught in the crossfire between a financial regulatory team and a room full of senior banking executives.

The discussion was getting heated when the regulators pushed for a significant increase in data disclosures. They repeatedly stressed the need for the authorities to have more information – to be better prepared for an orderly resolution in the event of a future Lehman-like collapse.

A particularly passionate exchange happened between James, who led the regulatory team, and Sarah, a senior executive with over 25 years of experience with BBG’s investment banking vertical.

“Look, this idea that some firms are in effect too big to fail has to be corrected,” James declared. He went on to explain the regulatory position – that the taxpayer could not be expected to bail out insolvent firms without limits. And this was ample justification for the significant disclosure demands the regulators presented.

“I do not think this position is really tenable at this point,” Sarah said.

I don’t know if I’m the only one who sees this, but we are in a very precarious situation with the global economy at the moment, and letting another Lehman happen now, where would that leave us? We have the U.K. in recession. We have a huge amount of debt across the Eurozone. We have a lack of growth in most of the Eurozone countries. We have austerity measures across the board. So, in my view, we are in it: we are already in a ‘too big to fail’ situation.

With great confidence, Sarah continued her rant – challenging the authority’s strategy – for a few minutes. She was adamant that collecting more data – on the pretext that this would allow for an orderly resolution – was not a viable option. In her view, the economic outfall was going to be felt for another ten years at a minimum – and was inevitably going to look like an...

Table of contents

• Cover Page
• Half Title Page
• Endorsement Page
• Title Page
• Copyright Page
• Dedication
• Contents
• Endorsements for Making Data Work
• Acknowledgements
• Author
• Introduction
• Part I Stakes Beyond Borders: Encountering Implications of Data Challenges on a Global Scale
• Part II In the Heat of Frustration: A Deep Dive into the Implications of Organisation-Wide Data Obstacles
• Part III A Path Towards Resolution: Exploring Experiential Solutions for Achieving Effective Mindset Shifts
• Part IV Bringing It All Together: Exposing Recombinant Evolutions of Technical Solutions and Their Practical Applications
• Appendix: Some Key Terms Explained
• Index