Q&A with James Lee, Managing Director and Head of Financial Services, Analytics and Cloud Transformation at PwC

Media 7 | August 16, 2021

James Lee, Managing Director and Head of Financial Services, Analytics and Cloud Transformation at PwC, is a well-recognized management consulting leader and senior technology executive specializing in advising global financial services organizations on “cloud-first, data-driven” digital transformation with data and analytics, AI, and intelligent automation. He has over 20 years of strategy consulting and technology operation experience in North America, Asia, and Europe that spanned across various industries including insurance, banking, asset and wealth management, private equity, and telecommunications.

In my opinion, the most forward-thinking digital leaders usually excel at constantly instilling a digital-first mindset into their workforce and encouraging employees to cherish every “fail fast” lesson learned opportunity.



MEDIA 7: Can you please take us through your 20 years of strategy consulting and technology operation professional experience? Where did your career begin?
JAMES LEE:
My pleasure. I started my career as a software developer in Asia (after graduating with an engineering degree in Hong Kong) and then spent the next 20 years in North America in various management consulting and digital executive roles. For the past decade, I have been working at PwC with a sheer focus on growing multi-competency teams to assist our global financial services clients with driving data-driven innovations and operationalizing high-impact digital transformations. From a consulting career perspective, it has definitely been a rewarding experience over the years as I was fortunate enough to participate in many large-scale transformations with companies across the globe and met a lot of amazing people along the journey. As a trained engineer with years of strategy consulting experience in the financial services world, I found my diverse background (culture, academics, work, international exposure) has given me a balanced perspective in approaching corporate digital challenges by helping organizations better leverage the power of cloud, analytics and automation within the context of their business.


M7: What is PwC’s new global strategy, The New Equation, about? How does it address some of the major challenges in the world today?
JL:
The New Equation is our new PwC global strategy that responds to fundamental changes in the world, including technological disruption, climate change, fractured geopolitics, social tension, and the continuing effects of the COVID-19 pandemic. It focuses on two interconnected needs clients face in the coming years:

Build Trust - to meet rising expectations of transparency and stakeholder engagement and

Deliver Sustained Outcomes - with an integrated and multidisciplinary approach that combine expertise in strategy, digital, data & cloud services, people & organization, ESG, cybersecurity, and AI.

Our firm will be making over US$12 billion investment over the next 5 years ($3 billion will be in the Asia Pacific to further expand business in this high growth region) with initial commitments including new ESG Centres of Excellence, Leadership Institutes, accelerated deployment of emerging technologies and increased investment to support audit quality and advisory capacity. As a result, we will be creating over 100,000 new jobs so it is definitely an exciting time to be in the professional services industry.


There have been increasingly pressing needs about ESG(especially the “E”) as evidenced by the recent United Nations IPCC report that the earth climate crisis is unequivocally caused by human activities.



M7: What are some of the successful digital and sustainable transformation strategies that you have implemented through your work at PwC?
JL:
For this question, I think it is very important to define what success means for a digital transformation journey and the answer certainly varies for different organizations. Yet from my years of experience helping global firms strategize and operationalize their digital transformation programs, there are a few key success factors in common and will continue to be crucial:

A top-down approach with clear and measurable goals: Digital transformation is not just another big project but instead a multi-year corporate journey that requires all management teams and staff to stick together to go through the ups and downs associated with the changes. Every successful digital transformation starts with a strongly supportive board with laser-focused strategic vision and an experienced, highly collaborative squad(s) that masters delivery execution with disciplined change management, outcomes-driven budgeting model, and agile-based implementation governance.

‘Employees-Led’, ‘Customer-Focused’, ‘Technology-Enabled’: I know it sounds a bit generic but these are golden rules/guiding principles a digital executive could always rely on to make sensible decisions during ambiguous situations in a transformation. Is this budget decision going to help to upskill our staff to promote the digital-first culture? Which 2 out of these 10 proposed digital servicing ideas will provide the most ‘distinctive’ customer experience? Does this seemingly cheaper or convenient technology option align with our “cloud-first, API-connected” strategy?

“Communicate, Celebrate and Communicate again”: ‘Transformation Fatigue’ is one of the biggest threats for any digital transformation. Over the years, I found the smartest digital leaders were always the ones who mastered the art of active communications and agile goal-based celebrations to continuously instill positive momentum to the organization throughout the transformation journey.

‘Data-driven’: Regardless of AI, IoT, or intelligent automation, data is the fuel that powers any high-speed digital transformation train. A solid enterprise data strategy and a secure cloud data platform are fundamental to every successful digital transformation.

‘Digital (& Sustainable) Transformation’: As ESG is gaining more attention in the boardroom, I am seeing more and more corporate digital innovators leveraging emerging technologies to try to improve their ESG outcomes. From the early digital age of automating manual, paper-based processes with RPA and OCR technologies to more recently using AI, 5G, and augmented reality to facilitate remote work to minimize air travel (oil fuel is a major source of carbon emission), I can foresee a growing trend that companies will increasingly integrate ESG factors into their digital transformation agenda to drive sustainability benefits.


M7: What do you see as the most noticeable change right now happening in the workforce, encouraged by the rise of digital technologies?
JL:
This is a great question. I was recently invited to speak at a global digital banking summit with a few fellow C-level panelists and it is interesting that we all shared similar observations regarding some of the implications for the workforce:

The importance of “Thinking Digital, not just Being Digital”: Digital technologies bring inevitable changes to operation as well as a business model but still many companies didn’t do enough to evolve their corporate culture and business processes (“Excel is still my best friend regardless!”) after having invested millions in technology infrastructure. In my opinion, the most forward-thinking digital leaders usually excel at constantly instilling a digital-first mindset into their workforce and encouraging employees to cherish every “fail fast” lesson learned opportunity.

Upskilling in data literacy and risk governance awareness: For most companies, the primary objectives of digital transformation are to improve customer experience or time to market for products and services. While capitalizing on these benefits as part of what I called the offensive aspects of a transformation, corporations should not overlook the flip side of the coin which are the defensive duties to mitigate risks associated with the use of emerging technologies. Are your AI algorithms making decisions that align with your company’s values? How is your brand affected if you cannot explain how AI systems work to your customers and regulators? Do customers trust you with their data and did you provide adequate customer data protection training to your workforce? These are all legitimate questions that require business leaders to revisit their risk management plan and formulate an upskilling strategy for the workforce (e.g. curriculum to improve overall data and analytics literacy as well as risk governance awareness).


In this ever-changing digital world, we always emphasize to our clients the importance of upskilling so you can probably imagine most of us are vivid lifelong learners ourselves too.



M7: James, I understand you had a lot of experience helping financial services institutions with their ESG data management, analytics, and reporting needs. Would you be able to share your perspective in this space given this is such a hot topic in the industry?
JL:
Certainly. There have been increasingly pressing needs about ESG(especially the “E”) as evidenced by the recent United Nations IPCC report that the earth climate crisis is unequivocally caused by human activities. It is a sad reality but it could get worse if the slim chance remaining to stave off heating above 1.5C is not immediately addressed. It definitely requires stronger global collaborations and I think the financial services industry (as an allocator of capital) will continue to play a pivotal role in the following areas:

Sustainable Finance – promote sustainable economy through prioritizing financing decisions such as sustainability-linked loans, green bonds or carbon tax optimization,

Responsible Investment – promote ESG through thematic investing to achieve better risk-adjusted returns and value creation,

Climate Risk Analysis – mitigate climate-related operational risks (physical, transition) and achieve eco-efficiency by reducing the carbon footprint (e.g. through climate risk scenario analysis) and better managing other environmental risks (water, land, waste),

Resilient Supply Chain – transform supply chain with ESG considerations to enhance operational resilience.

From a data and AI strategy perspective, there are a few key ESG trends that I believe will continue to drive the acceleration of digital transformation in the financial services industry:

Mandatory ESG disclosure: While EU regulators were early movers in leading climate disclosures, other international financial hubs (e.g. Hong Kong Stock Exchange, London Stock Exchange) have already followed the footsteps to demand TCFD disclosures for listed companies. In addition, SEC has repeatedly expressed a new, heightened focus on disclosures about climate change. I think this compliance-driven wave will push more companies to revamp their data and reporting infrastructure to cope with the complexity of the 4Vs (volume/variety/veracity/velocity) associated with ESG data. For example, many companies are currently still using manual processes to collect internal ESG data (water consumption, carbon emissions, workforce demographics) and these data sources are usually scattered in disparate databases in various formats. Adding to the complexity of data collection is the need to bring in relevant (and material) external data sources and alternative datasets for ESG analysis.

Correlation of non-financial KPIs and financial performance: It is not uncommon these days CFOs are asked by an investor on an earning call about their firm‘s climate risk exposure or progress in diversity and inclusion. Indeed many ESG materiality assessments indicated that there are correlations between non-financial KPIs and the financial performance of a company. Given that ESG data has to be ‘Investor grade’ and audit-ready for disclosure purposes, I believe more companies will begin to incorporate ESG data and analytics into their digital finance transformation agenda by centralizing data on a cloud data lake coupled with an agile data governance process to enhance both data access and data quality.

Continuous monitoring of ESG performance: I think it is important to point out that the ultimate goal of ESG should not be just a series of sustainability reports for PR purposes. But rather an ability for companies to measure and report ESG progress in a timely manner and for investors and other stakeholders to be able to verify it with data. As I mentioned earlier, with the tightened regulatory requirements and increased complexity of ESG data, I think companies will continue to invest in emerging technologies to address the following ESG data and reporting challenges:

-      Ensure accuracy, agility, and data integrity of the relevant metrics.

-      Reduce the time and cost to prepare ESG disclosures.

-      Improve ESG industry ranking by actively monitoring sustainability KPIs to drive actionable insights.

This is an immense topic that I have a lot of passion about and can easily talk about for another hour with a beer (chuckles). If you are interested in learning more about potential ESG data and AI use cases pertaining to different sectors in financial services (insurance, asset and wealth management, banking, and capital market), I have published a few blog articles that you can easily find in my LinkedIn profile.


M7: This is the last question but it is an important one for our readers. Knowing what you know now, what advice would you give to the young people who are aspiring to pursue a successful management consulting career in digital transformation?
JL:
I would summarize into 4 key traits which I personally found are important for every management consultant: 

Listening: Management consulting is all about problem-solving for our clients. Regardless of how many world-class strategy frameworks or talented digital/data/cloud individuals a top-tier consulting firm possesses, these are all irrelevant if we don’t listen effectively to the unique challenges faced by each of our clients. Indeed the ultimate responsibility of our digital consulting practitioners is to help clients analyze their problems through active listening and then tailor a ‘fit for purpose’ digital solution approach through our global network of experienced professionals, strategic technology alliances, and intellectual assets.

Proactiveness: Management Consulting is a people business or more precisely a team sport that involves multiple stakeholders in the ecosystem: customers, employees, alliance partners, regulators, industry analysts, etc. I found almost every successful digital consulting leader has a highly proactive attitude and they never shies away from taking initiatives in their approach for innovations, stakeholders management, and professional networking,

Lifelong Learning: In this ever-changing digital world, we always emphasize to our clients the importance of upskilling so you can probably imagine most of us are vivid lifelong learners ourselves too. This trait usually goes side by side with ‘curiosity’ and I think, both are key characteristics for any individual who wants to pursue a sustainable management consulting career.

Empathy: This is my favorite one. As I mentioned before, management consulting is a professional team sport and stress management is an inevitable part of our work life. Throughout my global consulting career, I have assembled many cultural-diverse, multi-competency teams to cope with countless stressful client situations. I found ‘Empathy’ was always my best companion in those situations (for both clients and teams) and it was amazing that every time we were able to emerge as a more united and inclusive team with ever-stronger and trusted client relationships.

ABOUT PWC

With offices in 155 countries and more than 285,000 people, PwC is one of the leading professional services networks in the world that provides assurance, tax, and advisory services.

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Stardog Joins Databricks Partner Connect

Stardog | September 26, 2022

Stardog, the leading Enterprise Knowledge Graph platform provider, today announced it had joined Databricks Partner Connect, which lets Databricks customers integrate with select partners directly from within their Databricks workspace. Stardog is the first Databricks partner to deliver a knowledge-graph-powered semantic layer. Now with just a few clicks, data analysts, data engineers, and data scientists can model, explore, access, and infer new insights for analytics, AI, and data fabric needs — a seamless end-to-end user experience without the burden of moving or copying data. Together, Stardog's availability on Databricks Partner Connect enables joint customers to: Easily define and reuse relevant business concepts and relationships as a semantic data model meaningful to multiple use cases. Link and query data in and outside of the Databricks Lakehouse Platform to provide just-in-time cross-domain analytics for richer insights. Ask and answer questions across a diverse set of connected data domains to fuel new business insights without the need for specialized skills. "Data-driven enterprises are increasingly looking to build more context around their data and deliver a flexible semantic layer on top of their Databricks Lakehouse. "Stardog's Enterprise Knowledge Graph offers a rich semantic layer that complements and enriches a customer's lakehouse and we are excited to partner with them to bring these capabilities to Databricks Partner Connect." Roger Murff, VP of Technology Partners at Databricks A commissioned Forrester Consulting Total Economic Impact™ study concluded that a composite organization using Stardog's Enterprise Knowledge Graph platform realized a 320 percent return on investment over three years driven by $3.8 million in improved productivity of data scientists and engineers from faster analytics development, $2.6 million in infrastructure savings from avoided copying and moving data, and $2.4 million in incremental profits from enhanced quantity, quality, and speed of insights. "Our mission at Stardog is to help companies unite their data to unleash insight faster than ever before," said Kendall Clark, Founder and CEO at Stardog. "Databricks Partner Connect enables Stardog to deliver a seamless experience for Databricks customers to quickly add a semantic layer to their lakehouse, unlock insights in their data, and discover more value-impacting analytics use cases." About Stardog Stardog is the ultimate semantic data layer to get better insight faster. Organizations like Boehringer Ingelheim, Schneider Electric, and NASA rely on the Stardog Enterprise Knowledge Graph to accelerate insights from data lakes, data warehouses, or any enterprise data source.

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