Application Development
In this new normal, companies need to rely on a modern approach to data operations in order to accelerate their journey to modern systems, launch digital experiences faster, and more.
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Retail has been one of the industries hardest-hit by the pandemic, forced en masse to go all-in online. For many, this dramatic increase in online shopping has made every day feel like Cyber Monday. And now, even as lockdown limitations are being lifted, and many retailers across the country reopen their doors for in-person shopping—it’s clear the consumer shift to online shopping shows no signs of slowing down or going back to normal.
Over the last three months, e-commerce sales grew more than 30% (even as total retail sales are in decline). Just this week, Walmart reported its biggest earnings surprise in 31 years as online sales nearly doubled during the coronavirus pandemic. Their investment into digital transformation and savvy use of data and tech have helped strengthen its online operations and better compete with digital-first players, like Amazon.
Retail businesses as well as CPG brands shifting to direct-to-consumer are working to provide personalized mobile and online shopping experiences to customers, along with improving inventory and supply chain logistics. And perhaps most critically, there is a need to address increased data security risks as a result of a largely at-home workforce.
In this new normal, companies need to rely on a modern approach to data operations in order to accelerate their journey to modern systems, launch digital experiences faster, and more.
In a typical enterprise, there are dozens of digital transformation projects blocked by data bottlenecks. While methodologies like DevOps are bringing speed and automation to software development, the inability to quickly deliver high-quality, compliant data becomes the limiting factor that impedes teams from pushing out new features and functionality in a seamless way.
That’s because companies are not applying that same DevOps logic to a crucial piece of the development puzzle: data. Digital transformation depends on data, and without fast, secure access to fresh data—delays in development and testing are inevitable.
Take CPG giant The Clorox Company, the 106-year-old brand making in-roads into DTC capabilities. Even before the COVID-19 crisis sent demand for products through the roof, the company knew it needed to modernize its data operations to adapt faster to changing shopping habits. Like many brands, Clorox was under a torrent of data. Managing this groundswell, and using data quickly, would become its biggest challenge to unlocking real digital transformation.
Clorox’s goal was to expand its footprint of retail partners from just 5 to 48 parties (no easy task) and modernize its SAP applications to support that expansion. At the time, provisioning a data environment for its global SAP system took 45 days, causing major project delays and leaving QA teams without consistent test data. Worse, a planned migration to a new data center threatened to cause weeks-long outages that were unacceptable for a business as large and important to consumers as Clorox.
So in 2017, Clorox adopted a DataOps platform that delivered compliant data faster to drive application upgrades—accelerating their journey to develop an ERP backbone that would support its digital initiatives. Within weeks its development teams were able to provision lightweight, compliant data at the speed and scale required to solve data migration challenges, avoid costly downtime, and move fast without breaking things.
With its newly virtualized data infrastructure, Clorox can now react quicker to customer demands, make swift operational adjustments, and more informed business decisions in response to changing consumer behavior.
Like Clorox, most companies today are swimming in colossal amounts of data. Data is often siloed across an organization, which poses problems for both product innovation and data security. Oftentimes, data resides across a number of disparate sources in multiple environments and different generations of technology, making it extremely difficult for individual teams to access the data needed to drive digital initiatives.
According to a new report from IDC, global businesses that are using a DataOps platform have seen an improved time to market, lower operational costs, and reduced business risk. In fact, on average organizations who have adopted a DataOps platform saw a 24% improvement in IT staff productivity and generated $5.3 million in value.
Another example that highlights data-driven innovation is American retailer REI. The company centered its entire Black Friday strategy for the past five years around an app-driven campaign: #OptOutside, continually focusing on building a strong community of adventurers and perfecting the REI shopping experience.
In the first year of the program alone, an estimated 1.4 million customers joined in the #OptOutside campaign. Creating a digital and in-store customer experience that aligns to REI’s brand means mastering the art of application development and testing. By leaning on a data platform to improve its data operations, REI was able to speed up app development, which ultimately amounted to improved customer experience and brand loyalty.
Going forward, innovation will continue to be driven by data agility. By ensuring that data is easily accessible—as well as compliant—CPG brands and retailers can rapidly respond to unexpected conditions while staying digitally relevant with customers. Data is a game-changer for retailers, but only if they can make that data available quickly, at the right time, to the right teams to test and iterate on new ideas.
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