Machine Learning

Preparing for the next disruption: 10 analytics trends for 2022

From AI and curiosity to supply chains and diseases, SAS experts look at the year ahead

What will 2022 bring? Will the same issues that plagued us in 2021 continue? And can businesses and governments use technology such as artificial intelligence (AI), machine learning, data models and advanced analytics to address these challenges?

SAS, the leader in analytics, asked its experts in health care, retail, government, fraud, data ethics and more. Here are their predictions for the trends we all will face this year:

Curiosity becomes a coveted job skill
“Curiosity helps businesses address critical challenges – from improving job satisfaction to creating more innovative workplaces. Curiosity will be the most sought-after job skill in 2022 because curious employees help improve overall retention, even during the Great Resignation.” [See the SAS Curiosity@Work report, which surveyed managers globally across industries.]
– Jay Upchurch, CIO

COVID rewrites AI models
“The pandemic upended expected business trajectories and exposed weaknesses in machine learning systems dependent on historical data and reasonably predictable patterns. This identified an acute need to bolster investments in traditional analytics teams and techniques for rapid data discovery and hypothesizing. Synthetic data generation will play a major role in helping businesses respond to continued dynamic markets and uncertainty in 2022.”
– Brett Wujek, Principal Product Manager for Analytics

Fraudsters exploit supply chain woes
“While supply-chain fraud is nothing new, it will be a major challenge globally in 2022 as the ongoing pandemic continues to disrupt everything. Businesses have deemphasized risk management for supply chains in their haste to find alternative supply sources. Fraudsters and criminal rings won’t miss the opportunity to exploit this situation. Supply chain analytics will drive transformation as organizations strike the balance between continuity and survival on one hand, and risk management and fighting fraud on the other.
– Stu Bradley, Senior VP of Fraud and Security Intelligence

Demand signals help rescue the supply chain
“In retail, expect more low inventories, high demand and ‘out-of-stocks’ well into 2022. Staffing shortages – from store associates to stockers to truck drivers – will be another challenge in 2022; consumers should prepare for longer in-store wait times. Overall, the retailers that succeed in 2022’s new normal will deftly use analytics to capture and read supply-chain information and consumer-demand signals, then rapidly respond to supply-chain glitches and changing customer preferences.”
– Dan Mitchell, Director of Global Retail Practice

Analytics anticipate disease outbreaks
“We need to move from finding what is already there to anticipating what happens next. We know disease exists, where it comes from and how it evolves, but we don’t know when those changes will occur. We must continue to employ analytics to answer those questions, which is critical to identifying future threats to human health.”
– Meg Schaeffer, Epidemiologist

COVID puts data at the center of clinical research
“Much has been said about COVID-19’s long-term effects on clinical trials and research, often due to it becoming more decentralized. The real game changer, however, is the crucial role of regulatory-grade analytics to speed up patient enrollment, ensure an intact clinical medicine supply chain, and generate clinically meaningful research and personalized results from the influx of structured and unstructured information. Since clinicians are relying increasingly on remote information in addition to that generated in the doctor’s office, we will continue to see more reliance on digital health analytics and AI.”
– Mark Lambrecht, Director of EMEA & APAC Health and Life Sciences Practice

Livestock monitoring halts disease spread
“Disease outbreaks in the livestock industry persist. This will likely lead to opportunities for livestock monitoring solutions to gain more adoption to combat the spread of new diseases through heat stress, floods and droughts in the coming years. And while COVID-19 has reduced the demand for animal products, especially across hotel and catering businesses, new initiatives favoring animal health and welfare will require similar monitoring solutions.”
– Sarah Myers, Senior Product Marketing Manager for Horizon Industries and Segments

AI and data literacy fight disinformation
“Studies show that false news may be more likely to reach people than the truth. The future will require a combination of analytics and AI running in the background of popular platforms to help provide visibility into the truth. However, powerful algorithms aren’t enough. We need to continue to build media and data literacy skills that will help everyone detect truth from fiction.”
– Jen Sabourin, Senior Software Developer, Corporate Social Innovation and Brand

Data visibility advances public trust
“Governments will be forced to tackle structural changes needed to better use data in three ways: Government must source data at a level of granularity that matches the decisions that need to be made for citizens, deal with privacy concerns around detailed personal information and increase the speed at which data can be shared. Workforce investments and legislative action are needed to drive these changes.”
– Tara Holland, Government Industry Principal for Public Sector Marketing

AI ethics standards begin to coalesce
“I anticipate increased focus on AI frameworks and standards driven by regulatory/legislative bodies and, importantly, by industry as well. While it’s not likely we’ll have de facto standards in the United States, companies in other parts of the world like the European Union and Southeast Asia will begin to coalesce around common approaches to AI.”
– Reggie Townsend, Director of Data Ethics Practice

For more such updates and perspectives around Digital Innovation, IoT, Data Infrastructure, AI & Cybersecurity, go to AI-Techpark.com.

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