In Navigating Change in Crisis, we explore how individuals and companies are adapting to a “new normal” in order to keep essential services functioning. We provide actionable advice around how organizations, and ultimately the builders of data and analytic apps, are adapting to meet these changes. These insights aim to help you and your team navigate these unprecedented times.

Twelve years ago, in the throes of the 2008 economic recession, British Airways was cutting costs across the organization. One area they refused to cut, however, was their business intelligence program. BA claimed that a continued investment in analytics during the crisis was a critical factor to streamlining marketing activities and thwarting fraudulent bookings when their business was especially fragile. They understood the need to maintain momentum in their analytics program in the face of an overwhelming crisis.

In the midst of the COVID-19 crisis, maintaining momentum is vital and the art of decision-making imperative. Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. Three clear opportunities are ripe to collect, analyze, and act on data:

  1. Maximize revenues:  Identify drivers to increase sales by evaluating existing customers and processes.
  2. Drive efficiencies:  Identify underperforming departments and programs and determine where to reduce expenses. Use analytics to correlate and compare your operations, performance management, and financial analysis.
  3. Predict:  Lastly, look to forecast trends in supply and demand and track fast-moving changes in leading indicators.

To foster the art of the possible, below are examples of how regular businesses use analytics to maximize customer revenue, reduce costs, forecast outcomes, and drive efficiency. 

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Integrate data to understand revenue drivers

BraunAbility is the market leader in wheelchair accessible vehicles and commercial lifts, where teams use analytics to unveil some surprising truths about revenue drivers. They had always offered discounts on different products to their customers but they never had a way to segment and attribute discounting down to sales impact.

With smart dashboards and KPIs, the BraunAbility team is able to tie discount data from marketing platforms to sales results in order to more effectively measure the impact of any discount. These insights drive production, but more importantly, they allow business leaders to make informed decisions that improve profit margins.

Efficiently focus resources

SkullCandy, a leading manufacturer of headsets, wanted to predict return rates on new products to help focus resources and deliver better products. Using a combination of Sisense, Big Squid, and AWS Comprehend, they identified key themes and customer sentiment from customer reviews and warranty claims. With this in hand, they were able to associate product features with general sentiments to better forecast returns and improve product designs to minimize returns before going to market.

Create transparency, reduce overhead 

Pomerleau is a leading Canadian construction company using data and analytics to make their project management processes transparent. Bolstered by a powerful analytics platform, they are able to connect multiple systems so that project managers can pivot from a quick project view to a drill-down into the details of complex projects to identify how and where money is being spent. 

For example, when a client complained that their project was behind schedule, a project manager was able to pull up their Change Item report to show the client that he’d put in 30 change requests in a 30-day period. With the power to demonstrate how each request impacted the overall process, the team was able to accurately assess the real problem at hand.

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Automate, track, and predict positive outcomes

Premium Retail uses analytics to enable leading brands to measure sales performance, observe trends, and track execution. With a solid data strategy, the team is able to tie together retail data and sales performance, analyzing billions of rows of data from nearly a dozen different retail data sources. Best of all, data preparation is 70% automated. Access to a unified performance picture enables their retail customers to make near-real-time time decisions on product placements, ensure compliance, and benchmark performance against stores and competitors.

At RetailZoom, a team of data scientists supplies supermarkets and FMCG companies with predictive models that incorporate transactional and demographic data to determine the size and scope of promotional activities.

Insights over instinct

We’ve seen how important data-based decision making is to helping companies thrive in challenging conditions. But any company, no matter how big, can err when its leaders don’t use data to drive their actions. Some companies hit hardest by the COVID-19 outbreak have been Tesla and the travel industry as a whole.

Tesla is facing challenges due to the time it took for them to allow teams to switch to remote work vs coming to the office. While it’s impossible for manufacturing workers to complete their work off-site, the electric car maker has cut its on-site staff from roughly 10,000 to 2,500 after a confrontation with the Alameda County Sheriff’s office. Having a data and analytics system that’s able to analyze jobs roles and recommend which can be shifted to remote and which personnel are critical to have on-site can help accelerate decision making when situations like the COVID-19 outbreak occur and need a rapid response. 

Lastly, the travel industry will be out billions of dollars of revenue due to passengers opting not to fly or possibly being forbidden from entering or exiting their countries, depending on local conditions. Airlines have immense amounts of data at their disposal and when the novel coronavirus first emerged, the right analytics and BI platform could have helped them begin planning for contingencies around severely reduced air travel sooner.

A better future, thanks to insights

These are just a few examples of the range of problems suited to smart analytical solutions, as well as what happens when leaders fail to leverage insights from data and make decisions based on other criteria. In times of economic turbulence, doubling down on analytics can provide more certainty which becomes increasingly important.  At Sisense, we know successful analytical programs and thinking are essential to survive these times of crisis. 


Evan Castle is Head of Market Intelligence & Strategy at Sisense. He currently leads the Business Intelligence and Analytics Business. He has over a decade of experience leading advanced analytics intiatives from ecommerce to financial services at Fortune 100s like CapitalOne.  He holds a BSc in Computers and MSc in Management from the Londons School of Economics

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