Accelerate your data agenda during COVID-19 and beyond

The data agenda before COVID-19

In my conversations with various organizations in 2019 and early 2020, much of the data agenda was on the “defensive” and “control”: looking at data from an operational standpoint, with focus on risk and regulatory programs, data management and privacy. This has been the case since I’ve started reviewing systems and processes during the mid-2000s. 

While data has long been a component of the company’s blueprint (also known as enterprise architecture), its front and center face is maintaining data confidentiality, integrity and availability (and more recently, privacy). However, we’ve also seen the adoption of the “offensive” and “growth” agenda for data, although varying widely in the Philippines. Terms such as “innovation”, “data monetization” and “advanced analytics” come to consciousness, with other technological advances that are highly dependent on quality data. 

Organizations, through the years, have crafted their data agenda to suit the times and their respective needs. But external events have a way of shaking things up. A significant disruptor and driver of the data agenda in recent memory was the 2009 global financial crisis, where the top need for data was for identifying and assessing risks (especially for financial markets) and respective exposure. 

For banks, this brought about regulatory guidance in the form of Basel Committee on Banking Supervision’s (BCBS) standard number 239 (Principles for effective risk data aggregation and risk reporting), adopted in various versions across different jurisdictions. While not necessarily the same, COVID-19 drives us to rethink our business, digital and data agenda for survival and recovery.

COVID-19 disrupting and shifting the data agenda

As we ushered in 2020, we have identified top data trends across key industries:

• Financial services: refreshing data and customer policies to align to emerging global data, AI and privacy regulations; moving from an agency model to an “insight consultancy” for individuals and businesses

• Government, public service and healthcare: prioritizing the adoption of digital and data through grants and tools

• Energy, utilities and resources: pricing and operational optimization 

• Retail and manufacturing: reducing procurement leakage and stockouts via increased supply chain visibility

• Education and tourism: shifting to virtual, digital and e-learning in process; increased competition for tourist spend, combined with desire for personalized travel experiences

But as the pandemic panned out, we have seen its impact on these industries, as well as the significant dependency on quality data. We are on a daily lookout for COVID-19 statistics on new cases and recoveries, their location/concentration and potential for contagion‒that should signal healthcare response and government policy directives, especially our moves through varying degrees of community quarantine. 

Economic data on the impact of lockdowns on vulnerable sectors (i.e. MSMEs) and the population are significant inputs to economic recovery and stimulus measures. 

Banks have maintained strong capital and liquidity buffers, but are on the lookout for early signs of credit defaults, key exposures and concentration while implementing programs to support businesses and individual clients. Organizations are gathering new and updated employee information to cover health, location, travel and personal conditions--for use towards employee support, updated remote working arrangements and contact tracing.

The focus on data during crisis planning and response has been highlighted in our 2019 PwC Global Crisis Survey. It notes that “In a world of split-second virality, incorrect, insufficient, or misleading information (or even correct information spread at the wrong time or in the wrong way) can increase your exposure and amplify the crisis.” 

One of the three bedrocks of successful crisis management is a fact-based approach, anchored on the availability and timely access to complete, accurate and valid data. 87% of respondents agree on the importance of establishing facts accurately, yet there’s plenty of work to be done. Nearly four in ten report that they didn’t actually have the facts to mount an effective response.

Call to action: data agenda to generate revenue and optimize cost

Crafting a new and more responsive data agenda now is a tricky balancing act. While working hard to keep the lights on and recover, we also need to prepare for the post-pandemic world and a peripheral vision on the opportunities ahead. And in the midst of all in-the-moment tactical and strategic decision-making, we cannot discount the criticality of data and our data agenda.

We direct our efforts to manage the cost of operating through uncertainty, while identifying and capitalizing on recoveries in market activity. Here are a few questions we can reflect on for each outcome:

• Revenue generation:

  • How fast will the market return to specific products, services, and channels?

  • What are the changing competitive dynamics and how do we evaluate multiple scenarios across macro and micro economic drivers?

  • How do we target customers/segments to increase returning market share while optimizing our channel and spend decisions?

  • How do we identify customers that will be more valuable to us in the long run as we evaluate incentives?

  • How do we determine product pricing and profitability across different segments, geographies and distribution channels to manage the variance in market recovery?

• Cost optimization:

  • How do we identify the right customer feedback and insights as we manage changing servicing models?

  • How do we manage our financial and operational performance under changing business demands and resource constraints?

  • What levers do we have to reduce cost in the short, mid and long term?

  • How do we reduce heavy reliance on IT by giving users the ability to easily access their own data, through self service?

  • How do we determine capital requirements under different macro and micro economic drivers?

  • How do we forecast credit risk projections across portfolios and recover delinquent and default credits?

Underpinning revenue generation and cost optimization, organizations focus on  pivoting towards five strategic areas:

• Data platform deployment and governance: Organizations have long been challenged with disparate, siloed and varying data platforms that require multiple approaches to manage and protect. Much more in the remote working environment, organizations realize the benefits of cloud-based data platforms, allowing more flexibility to access and integrate data use cases (i.e. operational and financial reporting). Organizations need to consider architectural, governance and current capabilities to make implementation and transition successful. 

• Data monetization and ecosystem development: To draw out more value and insights from organizational and customer data (a wealth of them already in our data platforms), companies are looking at generating revenue from data-as-a-service, derived metrics, better customer profiling and data sharing through data exchanges and ecosystems. With careful consideration of data privacy, emerging technology solutions coupled with robust, governed and scalable data exchange execution can yield benefits.
  
• Leadership data analytics capability uplift: As we expect leaders to adopt a more data-driven decision-making perspective, capability-building programs must be rolled out to equip management with both behavioral and technical skills to embed the data agenda in day-to-day business.
  
• Data strategy and management refresh: Whether the organization is in the middle of implementing an established data strategy, or in the process of preparing one, the circumstances are pushing a rethink of the data agenda. Effective data strategies encompass access, quality, literacy, use, management and security of data assets. Protection/compliance and reducing friction should be balanced in order to more rapidly realize business outcomes.
  
• Data ethics and culture, and responsible AI: As the volume of data continues to expand exponentially, promoting responsible data culture and practices in human behavior and also in training artificial intelligence becomes more important. Responsible data ethics and culture can help minimize unethical and unlawful practices, such as inherent bias, which may not be apparent when models are being developed or trained.
  

How can we then start the data agenda and build on our current state? To enable organizations to quickly assess strengths and gaps in their data maturity compared to industry peers or aspirational organizations, PwC and Carnegie Mellon University developed the Data Maturity Assessment. The tool allows organizations to understand their current data strengths and weaknesses across six dimensions: Business decisions & analytics; Data information; Technology & infrastructure; Organization & governance; Process & integration; and Culture & talent. Insights from different business areas enable a holistic and objective assessment, and a benchmark against other firms in the same industry or geography. This provides a good foundation to craft the data agenda for revenue generation and cost optimization.

We see that crafting the data agenda doesn’t need to make it exclusive to either the “control/defensive” or “growth/offensive” perspective. It needs to integrate both. If we want to take control of our data agenda for the now and the future, decide and take actions fast‒through high quality data that can be virtually and rapidly accessed and converted into actionable insights.

* This article is based on PwC South East Asia Consulting Data & Analytics Perspective: Reimagining data amidst a changing global climate, an unpublished PwC insights document (2020).