If you’re an e-commerce, the COVID-19 crisis must have hit you hard. š
Navigating constantly changing lockdown regulations while monitoring the supply chain and ensuring the safety of your employees can be a nightmare for any business owner.
Is there a way to respond better to the crisis with the help of data science?
Last week at our live webinar series, we spoke with data leaders from BigBasket who managed to do just thatāuse data and analytics to power their crisis response strategy and plan of action.
Needless to say, it was a power-packed session with tons of actionable insights. What else do you expect from India’s largest online grocery store? š
As we spoke to Mani, Head of Analytics at BigBasket, and Pushkarini, a Data & Analytics Manager, there were five takeaways on crisis response that stood out the most.
1. Keep your data teams small and nimble
The core analytics team at BigBasket only has eight humans of data…
… just eight people responsible for supporting retail and supply chain operations, business requirements, marketing and sales analytics for the entire company across 25 cities in India.
Howās that even possible? š±
The analytics team focuses on DAI (Definitive Actionable Insights) or business problems. We outsource everything else, such as data cleaning or maintaining large data warehouses, to our engineering and technology partners.
Pushkarini Kulkarni, Data & Analytics Manager at BigBasket
So obviously, our next question was a no-brainerāhow do you build such teams? And that brings us to takeaway #2.
2. Focus on four elements to build high-quality data teams just like BigBasket
When building high-quality data teams, there are four important elementsāpeople, process, technology and culture.
Mani, Head of Analytics at BigBasket
Most of BigBasketās analytics team is young, freshly graduated from engineering schools in Bengaluru.
While hiring, the managers at BigBasket like Mani look for people with the right mix of talent and attitude. Everything else like skills or technologies can be taught.
Another key element is process. BigBasket attempts to document and automate as many processes as possible to avoid human intervention. This avoids miscommunication and improves agility.
As with all data teams, the folks at BigBasket also use a bunch of tools and technologies, which can quickly get chaotic. Thatās why they emphasize on ensuring that these systems talk to each otherātheyāre interoperable.
Last but not least, culture! Mani recommends prioritizing building a culture that values impact and is hypothesis-driven as opposed to merely coolness.
Powerful stuff! šŖ
With that, the conversation switched gears to address the elephant in the room (well, virtual Zoom room)āresponding to the deadly COVID-19 crisis. š¦
3. Be smart and agile with your response
Almost overnight, the entire nation went on lockdown and with little information on whatās next, people went on a panic-buying spree. šāāļø
BigBasket saw an exponential surge in traffic on its website and app, requiring the team to make some bold decisions.
Deciding to prioritize delivering essentials and focusing on the loyal customers, BigBasket:
- Disabled all non-essentials and new registrations
- Accepted only prepaid orders and disabled the cash on delivery feature
- Initiated refunds/cancellations for its new customers
These decisions bought some time that allowed the team to scale its infrastructure (within 2 days) and prepare for what came next.
We introduced a priority slot feature for our loyal customers and reserved a certain delivery capacity for them.
Pushkarini Kulkarni, Data & Analytics Manager at BigBasket
Next, the company quickly strengthened sanitation at its warehouses and made provisions for thermal scanning, masks and gloves and training in contactless delivery.
And now comes the smart responseāmost BigBasket customers are from Tier-1 cities like Bengaluru and they lived in apartment complexes.
So, BigBasket consolidated all orders from one apartment complex in one goāone shipment, one time slot, one delivery associate. This significantly reduced workforce constraints and helped continue business operations.
And that brings us to the dreaded next stepāadapting to a new normal. š·
4. Make week-on-week plans instead of monthly or quarterly plans
Thereās no cheat sheet for businesses to follow when dealing with an unprecedented crisis like COVID-19. That makes it harder for any team, including the data team, to make long-term plans, especially since regulations, laws and even pandemic responses are still evolving.Ā š
BigBasket would analyze the weekly data to understand and interpret the situation. Using the weekly insights, the company would chart its course for the next week.Ā
What role did data science play in helping the company adjust to a new normal? š¤
We ran āwhat ifā scenariosāwhat if we increase the delivery slots, what if we introduce more trucks over bikes for last-mile deliveries, what if we start delivering more perishable items… These simulations helped us make accurate predictions for the business team.
Pushkarini Kulkarni, Data & Analytics Manager at BigBasket
Moral of the story? Stay agile, make week-on-week plans and run data-driven simulations before making any business decisions. š
5. Put customer experience above reducing costs
Towards the end, we asked the data leaders if they had some actionable tips for other data team leaders in similar situations.
The responseāeven in crisis, customer experience is key. š„
So, look back and analyze high-impact campaigns with maximum ROI. Build data science models to predict the outcome of these campaigns in current times, which will help streamline budget and cashflow. Only make investments in outcomes that you can predict.
To cut costs, BigBasket recommends looking for low-impact campaigns or revenue slippages in the supply chain.
What weāve shared is just the tip of the iceberg. So in case you missed the live session, check out the recording here.
Running low on data? We’ve got you covered. š
You can switch to listening to the podcast version of the webinar on Spotify.
