Digital Strategy in Covid-19 Crisis p2 by Space Dreamer.

Learning at the pace of crisis

Moving boldly doesn’t mean moving thoughtlessly, however. Bold action and the ability to learn are highly interrelated. The real-time ability to learn during a crisis is in fact the one ingredient that can turbocharge your ability to scale quickly.

Find a new cadence

In situations of extreme uncertainty, leadership teams need to learn quickly what is and is not working and why. This requires identifying and learning about unknown elements as quickly as they appear. Prior to the crisis, leading companies had already been increasing the cadence of their learning as part of a quickened organizational metabolism (Exhibit 3). Companies can look to their example as they work to adapt to change more rapidly during crisis times—and beyond.



Four areas of intervention can help companies learn more quickly during the crisis and the next normal that follows.

Quicken your data reviews

Start by evaluating the frequency with which you review the available data. You should be reviewing multiple sources of data on a weekly (or more frequent) basis to evaluate the shifting needs of your customers and business partners—as well as your own performance. Look to your crisis nerve center as a single source of truth for newly emerging data about your employees, your customers, your channel partners, your supply chains, and the ecosystems in which your company participates. Then turn to secure file-sharing technologies like Box and Zoom to remotely share and discuss insights from this faster pace of data review.

Focus on technology

The abrupt shift to virtual operations and interactions, both inside and outside your organization, also provides an opportunity to accelerate your pace of learning about, and adoption of, technologies with which your organization might have only begun to experiment. As experimentation scales, so does learning. The rapid shift to digital can also reveal potential trouble spots with your organization’s current technology stack, giving you a sneak preview of how well your technology “endowment” is likely to perform going forward. Here are some factors to keep an eye on as you more quickly learn about and adopt new technologies:

 — Data security. Are you experiencing breaches as you move to remote working and data sharing?

 — Scalability. Where are the breaks and crashes happening as 100 percent of your interactions with customers, employees, and business partners go virtual?

 — Usability. Right now customers and business partners often have little choice but to access your products or services through your new digital offerings. Their options will expand as we move beyond the crisis. How well will your new offerings stand up? If your current usability is low, experiment to improve it now, while you still have a captive audience to partner with and learn from.

Test and learn

In normal times, experimentation might sometimes seem a risky game. Changing the working models to which employees, customers, or business partners are accustomed can seem to risk pushing them away, even when those experiments take aim at longer-term gains for all concerned. The COVID-19 crisis, however, has made experimentation both a necessity and an expectation.

Start with the customer-facing initiatives that, while more complex, offer a larger upside. Use automation and predictive analytics to quickly and effectively isolate difficulties. Look for opportunities to standardize what you’re learning to support scaling digital solutions across core business processes. Standardization can help accelerate projects by reducing confusion and creating common tools that broad groups of people can use.

Learning while scaling

As companies increase their rate of metabolic learning, they need to quickly translate what they’re learning into at-scale responses. Scaling what you learn is always an obstacle in a digital transformation. We’ve had plenty to say regarding scaling up analytics, scaling up quality, or innovating at speed and scale. Here we’ll simply highlight the role learning plays in your ability to scale your  digital initiatives.

While companies frequently pilot new digital initiatives with the intention of learning from them before they roll out broadly, these experiments and pilots, in normal times, only test one dimension at a time, like the conversion/engagement/satisfaction rates of individual customers, the unit economics of a single transaction, or the user experience of a given digital solution. Whether they want to or not, companies in crisis mode find themselves in a different type of pilot: one of digital programs at massive scale. The rapid transition to full scale in many types of digital operations and interfaces has brought with it many challenges (for example, building and delivering laptops in under two weeks to all employees to enable 100 percent of them for remote working versus the 10 percent that were previously remote). But it also brings opportunities. At the broadest level, these include the prospect for real-time learning about where value is going in your markets and industry, the chance to learn and feed back quickly what’s working in your operations and your agile organizational approach, and the opportunity to learn where it is you’re more or less able to move quickly—which can help inform where you might need to buy a business rather than build one.

Observing interaction effects

Since scaling quickly requires changing multiple parts of a business model or customer journey simultaneously, now is a valuable time to observe the interaction effects among multiple variables (Interaction effects occur when two or more independent variables interact with at least one dependent variable. The effect of all the    interactions together is often either substantially greater (or lesser) than the sum of the parts).  For example, healthcare providers are facing an increased demand for services (including mental health and other non-COVID-19 presentations) at the same time that their traditional channels are restricted, all in the context of strict privacy laws. This has caused many providers to rapidly test and adopt telehealth protocols that were often nonexistent in many medical offices before, and to navigate privacy compliance as well as patient receptivity to engaging in these new channels. Providers are learning which types of conditions and patient segments they can treat remotely, at the same time that they’re widely deploying new apps (such as Yale Medicine’s MyChart) to accelerate the digital medical treatment of their patients.

Similarly, when a retailer rolls out, within a week, a new app for country-wide, same-day delivery, it’s testing far more than one variability at a time, such as the customer take-up of that new channel. Because of the scale, it can learn about differences in adoption and profitability by region and store format. It can test whether its technology partners can scale across 1,000 stores. It can test whether its supplier base can adapt distribution to handle the new model. Shifting multiple variables simultaneously, however, also increases the degree of difficulty when it comes to interpreting the results—because you’re no longer isolating one variable at a time. Companies who have already invested in AI capabilities will find themselves significantly advantaged. Making further investments now—even if you’ve yet to get going— with continue to pay out postcrisis as well.

Simplify and focus

Given the degree of complexity created by scaled experimentation, organizations need to find ways to simplify and focus to avoid being overwhelmed. Some of that is done for them as the crisis closes many physical channels of distribution and makes others impossible to access. But further streamlining is required along the lines of what is working, what isn’t, and why. This is perhaps the first global crisis in which companies are in the position to collect and evaluate real-time data about their customers and what they are doing (or trying to do) during this time of forced virtualization. Pruning activities and offerings that are no longer viable while aggressively fixing issues that arise with your offerings will help increase the chance of keeping a higher share of customers in your lower-cost, digital channels once the crisis passes.

Don’t go it alone

Research indicates that people and organizations learn more quickly as a result of network effects. The more people or organizations that you add to a common solution space, in other words, the more quickly learning occurs—and the faster performance improves. Some argue that these network effects occur in a so-called collaboration curve.

At a time of crisis, changing needs drive rapid shifts in employee mindsets and behaviors that play out as a greater willingness to try new things. Consider how you can best support the ways your talented employees learn. One option is to build or tap into platform-based talent markets that help organizations reallocate their labor resources quickly when priorities and directions shift—and help talented employees increase their rate of learning. Be sure to look not just within the boundaries of your own company but across enterprises to include your channel partners, your vendors, and your suppliers. Chances are they will be more willing than ever to collaborate and share data and learnings to better ensure everyone’s collective survival.

It’s often the case in human affairs that the greatest lessons emerge from the most devastating times of crises. We believe that companies that can simultaneously attend to and rise above the critical and day-to-day demands of their crisis response can gain unique insights to both inform their response and help ensure that their digital future is more robust coming out of COVID-19 than it was coming in.

10.05.2020

Kadıköy, İstanbul – TURKEY

M. Temel AYGÜN, Ph. D. in Aerospace Eng

.https://www.linkedin.com/in/mehmet-temel-aygün-1066a514/

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