McKinsey studied the top 20% of companies that came out of the 2008 recession stronger and found that 2 important factors mattered: speed and discipline. With data, companies can respond faster as well as make better, more disciplined decisions.
The Eskwelabs team put together this article as a part of a series of insights on how companies can use data to bounce back. You can read a longer piece on this topic in a whitepaper on our website.
Here, we highlight 3 areas where businesses are facing the biggest challenges now and where we see opportunities for data to help with focus and prioritization:
- Supply chain
A Primer on How Businesses Can Leverage Data
First, a preamble on how business leaders can leverage data. Eskwelabs is an online data upskilling school for learners and teams, and we often get asked the question of “How can I leverage data more?” from businesses. Recently, we became the Data Science Development partner for the Asian Institute of Management’s Dado Banatao Incubator and found that entrepreneurs are also asking similar questions.
To start, we recommend business leaders to ask themselves, “What business challenges are we facing?” In the current post-COVID-19 economy, challenges revolve around disruptions in the workforce, supply chain, and ultimately, customer demand.
From this, businesses can dig deeper and ask further questions such as:
- “What decisions would we make if we had the answers?”
- “What data would we need to get the answers?”
- “How would we get that data?”
By asking this set of questions, we can focus on what data to collect, and derive the most relevant use case that matter to the business.
Regardless of which industry, our ways of working together have been disrupted by COVID-19. We wrote about the overall effect on the future of work from COVID-19 back in May in this article, but here we will focus on the ways data can help companies design a return-to-work strategy and provide guidance for those who will continue with remote work.
Tracking the health of employees by integrating public health data into people analytics dashboards is one way for companies to assess employee health and their potential to return to work. This data can inform businesses on which operations—based on their geographies—are safe to resume, and guide decision makers in identifying the risk factors of returning-to-work employees who may come into contact with high numbers of customers—such as in retail stores.
For teams that continue to work remotely, data on productivity and collaboration during this period can help business leaders assess whether or not a more permanent remote work set-up can be considered and for whom? For instance, business leaders can intentionally collect data on the productivity levels of employees during remote work, and assess how much of the workforce can perform remote work permanently and who must return to the office.
Finally, as the operating needs of businesses change, we can leverage data to perform better workforce planning. Data regarding the skills and competencies of staff would allow businesses to optimize roles and review whether or not new hires need to be made for new work that emerged from COVID-19. One example would be retail stores now needing less sales representatives but more e-commerce capabilities. Additionally, data on skills can answer the question of whether or not the business would benefit from hiring gig workers or freelancers to fill in short-term skill requirements.
Agile Supply Chain
During the crisis, there were frequent news stories of how grocery retailers experienced stock-outs due to panic buying behaviours. It’s also clear that those with supply-chain transparency prior to the pandemic—as well as predictive analytics in place to detect purchase-pattern changes—have done a better job of navigating during the actual crisis. Other sectors that experienced their own supply-chain difficulties during the COVID-19 crisis, can learn from this.
A large amount of data is generated across the supply chain but historically has been underutilized. Supply chain data like sales ratios, inventory turnover, and number of stock-outs can provide insights into past performance. While important, these alone are not actionable.
Supply chain visibility means accessing data relating to transactions and demand triggers, as well as the logistics movements in between. Using a digital tool that can create this end-to-end visibility can help optimize inventory especially as retailers move towards omni-channels. For instance, in the immediate term, most retailers are looking to make their previously physical offerings now accessible with minimal physical contact or virtually. These efforts might mean accessing new platforms and digital marketplaces, which can also create opportunities for more agile inventory management and demand prediction using data.
McKinsey assessed supply chain capabilities across 250 firms and plotted them on a scale of one to five. The research found that companies with more agile supply chain practices had higher service levels and inventory levels that were 23 days lower than their less agile peers. Similarly, research in Next Generation Supply Chains by PwC found that companies rated as supply chain leaders averaged 15.3 inventory turns per year, while less-agile companies achieved only 3.8 turns. Agility in inventory management will increasingly be driven by data.
Even before COVID-19, data and analytics was the leading customer experience (CX) trend, according to the CX Network. But now where digital channels are becoming the primary and, in some cases, the sole customer-engagement model, new opportunities are emerging for improved customer analytics.
As the economy bounces back, the demand recovery will be unpredictable and uneven across different geographies, products, and customer segments. A few sectors might experience stronger than usual demand, but most are experiencing demand lower than pre-crisis levels. Historical data and forecasting models are now of little use to predict where new pockets of demand will emerge from; therefore, different and faster ways of analyzing customer segments and behaviours are required.
This echos behaviours observed at top global companies which reported that “using multiple sources of customer data to assess unmet needs” as an activity has moved from monthly to weekly or faster due to COVID-19.
A Customer-centric analytics framework that granularly segments customers based on value, identifies root causes of potential churn, and enables staff to modify offers across products and functional areas weekly will be crucial in engaging customers in a more personalized way, especially as demand comes back. Eskwelabs plans to host an in-depth look into how customer analytics can be deployed for COVID-19 recovery. Companies are invited to share with us how they want to leverage customer analytics. You can reach out to our team here or comment on this article.
The Road to Recovery is Paved with Data
Recent data shows that we have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks. As the pandemic forces employees, supply chains, and customers into digital channels, it is now the right time for business leaders to shore up on analytic resources in priority domains like supply-chain optimization, or customer personalization.
The pandemic has shown us that rapid change and accelerated speed of going digital is both possible and pivotal for business survival. Some of the complex challenges won’t be solved overnight, but data can power better and faster decisions for business not just to survive but also to thrive in the new normal.
_The Eskwelabs team put together this article as a part of a series of insights on how companies can use data to bounce back. You can read a longer piece on this topic in a whitepaper, and sign-up for more insights from us here.