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3 data and analytics trends that will dominate 2022

Visibility into the supply chain, precise data product valuation, and data leveraging for sustainability and optimization will all be crucial in 2022.



Data analytics is an ever-changing field. Organizations appeared to be continuing to invest extensively in analytics to help their digital transformations early in 2020. The COVID-19 pandemic has proven to be a significant disruptor.


Early in the pandemic, it appeared that firms would put data and analytics improvements on hold in order to focus on more critical issues, such as supporting a remote workforce. Organizations, on the other hand, have increased their adoption of data and analytics capabilities, as well as AI, in many circumstances. According to a KPMG survey released in July 2020, the pandemic prompted 67 percent of respondents to accelerate their digital transformation strategy, with 63 percent boosting their digital transformation budget.


Since then, nothing has slowed down. According to Fortune Business Insights, the global big data analytics market will increase at a CAGR of 13.2 percent from 2021 to 2028, reaching $549.7 billion.


IT leaders should keep the following three closely related developments in mind as they focus on data analytics and AI in 2022 and beyond.


It’s all about the supply chain


The worldwide supply chain has been severely strained by the pandemic. Ships have been waiting for hours to enter ports, distribution facilities have been stacked with containers, and some stores have been left with empty shelves. Supply chain analytics are quickly becoming a necessary part of doing business for many firms.



"Most organizations simply focus on a single level of the supply chain: who are the suppliers and how can we get some alternative suppliers," says Doug Laney, West Monroe's innovation fellow of data and analytics strategy. "I believe that in order to predict price indices, more firms will begin to look into multilevel supply chain visibility." "It's not just my suppliers; it's my suppliers' suppliers' suppliers' suppliers, and so on."


Laney claims that firms can acquire a lot of data to gain such visibility, such as data from their website, monitoring LinkedIn for turnover, social media for pricing and availability issues, and so on.


Understanding the supply chain, according to Mike Giresi, chief digital officer of Molex, is currently a major pain point.


"On so many levels, supply chain right now is a big challenge," he says. "We're attempting to harness data, AI, and machine learning — we're attempting to do a variety of things there to give us a competitive advantage in terms of how we offer our supply chain capability."


Organizations will assign real value to their data


"A chief data officer's greatest success is when they've productized or commercialized their data in some way," Laney explains. "A lot of companies are starting to recognize this."


According to Laney, a former senior VP analyst at Gartner, CDOs were 3.5 times more likely to succeed in their post when they met data monetization initiatives, vs only 1.7 times more probable when they proved ROI on their BI or data analytics efforts.


Investors place a higher value on companies that commercialize or productize their data, according to Gartner. Indeed, the value of a company's data, he claims, is becoming increasingly crucial in M&A activity.


"We discovered that businesses that handle data as an asset have a market to book value ratio nearly twice as high as the market average. Companies that sell data goods or data derivatives have a market to book value ratio of 3x, according to Laney. "Investors want companies that are more data smart, data driven, or data product oriented."


Companies are taking substantial steps in 2022 to assign value to their data and use that value to generate income. It's not only about selling data; it's also about figuring out how to incorporate data into an existing product or service, or even how to use data internally to generate measurable value streams for the company.


Collibra data scientist Alexandre t'Kint and European Centre for Clinical Research Training automation developer Sarvenaz Rahmati recently released a blog post about the process they established to estimate the worth of a Collibra data product. To evaluate the data product's net value, they added the cost of the resources utilized by the data product (including development, maintenance, and licenses) to the income earned by the data product. The calculation was complicated since the data product in question was a support tool for Collibra's sales engineers rather than a revenue generator.


The process, according to t'Kint and Rahmati, can help companies figure out which data products will provide them the most bang for their buck and assess whether the data team's resources are being used effectively.


Disney Advertising Sales is an example of a business that recognizes the value of its data and uses it to interact with customers. It uses a data clean room to give advertising customers access to its audience graph.


Sustainability is key


In 2021, corporate leadership became more aware of environmental, social, and governance (ESG) challenges, and this trend is expected to continue in 2022.



Paige Morse, a process industry sustainability and strategy expert, has joined Aspen Technology as director of industry marketing, focusing on the company's chemicals and energy divisions. AspenTech is a software and service provider for the process industries that arose from a collaboration between the Massachusetts Institute of Technology (MIT) and the United States Department of Energy. She was named the company's sustainability lead in August 2021.


"This new post was created only this summer with a sustainability focus," Morse explains. "I believe we've seen the value of sustainability."


For sustainability, AspenTech is advancing the use of simulation and digital twins. Early on, she explains, simulation was used to assist consumers consider multiple options, such as alternate approaches to a chemical process. What happens if the process is carried out at a different temperature or with a different separation technique?


"It was mostly about cost and profitability," adds Morse. "How can I make this procedure more efficient?"


Customers, on the other hand, are becoming increasingly concerned about efficiency.


She explains, "We used to quantify efficiency in dollars or euros." "But now we're saying we should look at it in terms of CO2 averted, waste avoided, and feedstock not lost in the process," she says.


Jabil, a manufacturing services company, has been working on its Factory of the Future program for years. The Factory of the Future initiative aims to optimize and future-proof the company's more than 100 operations in more than 20 nations. Factory optimization and sustainability, according to May Yap, senior vice president and global CIO of Jabil, go hand in hand.


"When we started the Factory of the Future program, we didn't have a fancy name for it." "It was dubbed IT factory optimization," recalls Yap. "Once we've digitalized something in the manufacturing, we'll be able to see it." When we can visualize it, we can consider how to improve the factory's procedures."


The effort, among other things, leverages predictive analytics and telemetry data to optimize shop floor operations and eliminate downtime and waste in order to increase manufacturing efficiencies.


Source: CIO.com

 

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