COVID-19 has accelerated the adoption of digital technology. We caught up with a few of our colleagues to find out where they're seeing the most notable changes.
1. Broader—and better—virtual connections
Rodney Zemmel, senior partner and global co-leader of McKinsey Digital, New York
Before COVID-19, we saw huge adoption of digital in B2C organizations but less so in B2B selling. The conventional wisdom had been that in B2C, there’s only one customer who’s making the buying decision and the journey is pretty straightforward. B2B selling, meanwhile, required a longer, more complex buying-decision process that benefited from the value of relationships and an in-person sales process.
But with the rise of video-conference and related digital platforms over the last few months, we’ve seen that digital is just as effective for B2B selling. We’ve found that B2B customers are happy to receive information virtually—especially when that information is supported by advanced analytics, which can give the customer even more insights into what their organization needs—and when they need it.
Another example I’m excited about is the rise of virtual health. Remote healthcare isn’t new, but it had been pretty niche prior to COVID-19. But with the confluence of technology developments, changes in customer behavior, and changing regulations—from the practice of medicine across state lines to how healthcare gets paid for—virtual health has enormous potential to increase healthcare access for people.
2. Smarter ways to assess—and address—risk
Jan Shelly Brown, associate partner, New Jersey
I work with clients on large agile and digital transformations. These have accelerated since the pandemic, and I’ve been excited by the ways digital can improve how we manage risk and compliance, particularly in more regulated industries such as banking and insurance. In banking in particular, we find that most organizations are still using legacy, check-the-box risk and compliance tools to assess the risk of a new product or feature.
We have a digital tool called Agile Risk Watchtower, which offers an approach to manage risk in the context of your product. For example, if you’re a bank developing a mobile app, and your user needs to update personal information, the tool helps you manage—as you’re building out that feature—the potential risk concerns and suggested ways to mitigate them. All of these risks and steps to mitigate are cataloged for teams to see, adding transparency and eliminating the need for disparate discussions or delays in simply having to relay the information from one team to the next.
3. The rise and rise of e-commerce
Anand Swaminathan, senior partner and leader of McKinsey Digital Asia, Singapore
The biggest digital trend I have seen of late in my client work is the shift to buying everything online. I see it in my personal life, too. Just a few years ago, my family and I would purchase about half of everything we needed from an online channel. Today, it’s more like 95 percent.
That’s a huge shift, and it’s playing out in how we search for products, how many different e-commerce services and retailers we use, and how we have shifted our loyalty from certain retailers to others who have better selection, better pricing, better search, and better payment experience. This is a trend that is likely here to stay for a long time—and will have tremendous impact on everything from product design and offerings, supply chains, or the creation of digital-only businesses.
4. More effective outbreak tracking
Jessica Lamb, partner, Philadelphia
I’m really inspired by the impact of digital on simulation models. This type of model has been around for decades to model disease epidemiology, but digital capabilities have enabled us to bring in larger volumes of data and substantially more compute power, so we can model even more scenarios in a faster way than ever before. For example, we can now have a disease simulation model that’s able to include new data inputs from almost every country, sometimes at the region or county level, that updates every week.
Thanks to digital technology, these models are easily sent to the right stakeholders simultaneously, so that everyone benefits from the research in a way that’s applicable to them. Together, these capabilities allow us to give clients more scenarios to inform the tough decisions they have to make.
5. Better customer experiences
Gabriela Platinetty, expert associate partner, Sao Paulo
We’ve seen a rise in the number of brands using social messaging apps as a channel for conversational marketing, or a personalized version of chatbot communication, in large part because of how COVID-19 forced people around the world to shelter in place. Increasingly, these apps are a place for brands to have one-to-one conversations in real-time with their customers via direct messaging.
I am very surprised by how fast marketers have adopted these apps for business—and by how quickly customers are able to solve challenges on them. During the pandemic, I was able to see a doctor, get groceries, and do several other tasks over an app, and have questions answered online. I think we’ll see more and more everyday experiences move online, which could allow more people access to these—and faster.
6. More ethical AI models
Chris Anagnostopoulos, senior principal scientist, QuantumBlack, London
Today, data science and AI models are being used to make decisions that have long-lasting impact on people’s lives, ranging from university admissions and loan approvals to medical decision-support. We need to ensure that AI systems follow ethical guidelines that serve to anticipate, and minimize, potential harm. This manifests itself along several dimensions—prominent among which are the right to privacy and the duty not to discriminate based on attributes such as race, gender, sexual orientation or religion.
Given the market’s voracious appetite for AI-powered products and services within a booming digital technology, we see a huge need for investment in a multi-disciplinary approach to fairness-aware, privacy-respecting, explainable and responsible AI—one where ethical considerations are treated as design principles, rather than afterthoughts. The time is now to develop technology, best practices, and the right culture to ensure that the AI systems of tomorrow will catalyze societal transformations that are strongly aligned with well-defined human values.