Finding Success in a Data Guided Business
C-suite executives who do business based on gut instinct once had their day, but they're becoming dinosaurs in an era of big data. Today's successful businesses don't rely on emotional hunches to make strategic decisions. Instead, they look at the numbers. Data-guided businesses are using technology to unlock the hidden value of their information, using it to glean new insights, and to plan their next moves.
Data has become a mission-critical asset because there's so much more of it today. Market analyst IDC estimates that society created 33 Zettabytes (ZB) in 2018, and expects this figure to reach 175 ZB by 2025. That's a lot of information: 175 ZB of data would create a stack of Blu-Ray disks tall enough to reach to the moon 23 times.
Companies have access to a wide range of data sources, ranging from customer relationship sales systems to machine vision equipment on the production floor. Using artificial intelligence (AI) to supercharge the analytics process can help turn a company's data into actionable intelligence, and improved productivity. "We're starting to enable digital industries, like a digital wind farm, where you can leverage analytics to help the machines optimize themselves," says Vince Campisi, chief information officer at GE Software.
Becoming a Data-Guided Business
Becoming a data-guided business enables executives to make decisions based on real-world evidence.
GE Software's pursuit of the perfect supply chain solution, for example, underscores the benefit of harnessing massive amounts of data. "We've been able to take over 60 different silos of information related to direct-material purchasing, leverage analytics to look at new relationships, and use machine learning to identify tremendous amounts of efficiency in how we procure direct materials that go into our product," says Campisi.
Data analytics tools also provide companies with the ability to weigh their next move based on real-time information about everything from production patterns to customer behavior. Rogers Communications, for example, was so inspired by its use of machine learning to reduce customer complaints that it created an in-house analytics challenge. The goal is to motivate the company's business units to develop new decision-making tools for leveraging all of the company's customer service data.
Finally, basing their decisions on hard numbers prompts executives to mine their data for answers. Sometimes that means asking new questions. But, overall, the process helps decision-makers make choices based on careful evaluation of the data.
Most businesses would be excited at the prospect of more accurate, democratic decision-making, but, says Murli Buluswar, chief science officer at AIG, building a data-driven business sometimes means turning an entire culture around. "Initially, it largely ends up being imagination and inertia," he says.
There are also numerous technical challenges when it comes to digital transformation. One of most significant is unifying data from different sources into a single database. Companies have to invest in eliminating data silos in which critical information is fragmented throughout an organization. Improving access to a company's dataset helps transform important information into a more actionable asset.
It also is important to ensure that the capture, storage, and processing of big data conforms to the appropriate privacy standards. “One of the biggest challenges is around data privacy, and what is shared versus what is not shared," says Zoher Karu, vice president for global customer optimization and data at eBay.
Another hurdle in gaining data-driven insights is finding the right tools to process and visualize the data. "I hear about individual wins in certain applications," says Ruben Sigala, chief analytics officer at Caesars Entertainment." But having a more cohesive ecosystem, in which this is fully integrated, is something that I think we are all struggling with, in part because it's still very early days."
Beginning the Journey
Tackling the technical and cultural challenges inherent in becoming a data-guided company is an ongoing process, says Chris Penn, co-founder of Trust Insights, a data analytics company. "Becoming data-driven can take years," he says.
Penn says the journey to true data mastery often begins with resistance and ends when a company finally implements a new system. During the resistance stage, he says, organizations still don't understand the value of information. These companies are likely to still rely on guesswork, rather than data, when making decisions.
Businesses then migrate through the data-aware stage, Penn says, where they are begin to use data to optimize production and day-to-day operations. The ultimate goal, he adds, is to be a company that puts data at the center of everything it does.
Becoming a data-guided business requires more than just a few strategic changes and new technology. It means transforming organizational thinking and committing to harnessing the flow of data, from end-to-end. That's a tall order, but the results are what separates a digital-first company from the competition.
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