Published: April 3, 2020
Authors of this Market Insight report: Matt Aslett, Krishna Roy, Paige Bartley, Csilla Zsigri, James Curtis, Nick Patience and Jeremy Korn
The outbreak is causing enterprises in all industries to rethink their priorities. This is likely to have significant implications for the business intelligence and analytics sector, which our surveys have shown to be the highest priority technology for two consecutive years. Even as companies in the industries most affected by coronavirus cut back on non-essential spending with a view to staying afloat, analytics is arguably more valuable than ever in shaping the strategic decision-making that will ensure their long-term survival, while businesses in other industries and governments alike are turning to analytics to understand how best to respond to the challenges posed by the current disruption.
The 451 Take
Data and Analytics: Priority #1
While 57% of respondents were expecting increased strain on their internal IT resources (at the time the survey was conducted), interestingly, 34% of respondents were expecting to spend more on IT resources and assets in response to the outbreak – and the proportion of respondents expecting to increase their spending on IT actually doubled while the survey was in progress, from 20% of respondents on March 10/11 to 40% of respondents on March 18/19.
Some of the key areas for increased spending include employee communication/collaboration technologies, mobile devices, network capacity and security software, as enterprises adjust to a workforce that is predominantly being required to work from home.
Another potential area for investment, or at the very least increased usage and activity, is data and analytics tools, which respondents to 451 Research's VotE Digital Pulse: Budgets and Outlook survey rated as the highest priority technology for 2019, having previously selected business intelligence/analytics as the highest priority for 2018.
Additionally, 53% of VotE Digital Pulse: Budgets and Outlook 2020 respondents also named data and analytics tools and platforms as the technology with the greatest game-changing potential for their organization over the next three years, placing it ahead of machine learning/artificial intelligence, containers/container management, software-defined infrastructure and serverless computing.
The results also indicate that there is a clear correlation between high and low levels of digital transformation readiness and high and low levels of data-driven decision-making as 94% of digital transformation leaders agree that their organization's data platform/analytics initiatives have been successful, compared with 62% of digital transformation laggards.
Reacting to Disruption
The coronavirus crisis is causing enterprises to rethink almost everything, but the importance of analytics is not, and should not, be one of those things. The key benefits of being more-data driven include improving existing or developing new products and services, followed by lowering costs and enhancing customer service and engagement. Those benefits remain, although their importance will differ for organizations depending on the level of impact of coronavirus.
Companies in this category are having to cut non-essential spending, which would include spending on new business intelligence and analytics projects. However, these companies also need to analyze the potential impact of COVID-19 on their ability to develop contingencies to either survive as they are or evolve rapidly to address emerging opportunities, and they will be leveraging existing business intelligence and analytics resources to do so.
Enterprises in industry sectors that are less negatively affected by COVID-19 (such as financial services, grocery, online retail, utilities, telecommunications and manufacturing)
In these sectors, there is a case to be made for the increased use of analytics software and services to understand evolving customer behavior, supply chain changes and workforce planning. Retail provides some clear examples of how enterprises currently need analytics more than ever to understand and respond to previously unforeseeable changes in customer (as well as supply chain and workforce) behavior.
In the UK, the John Lewis Partnership premeditated government advice by shutting all its department stores and redeploying employees to its online business and Waitrose grocery stores. Decisions of this magnitude cannot be made without analyzing the requirements and implications.
Meanwhile in the US, Walmart's EVP of corporate affairs disclosed recently that the company is seeing increasing sales of 'tops' (such as work shirts) but not 'bottoms' (such as trousers or skirts) as people's clothing requirements adjust to the need for fewer in-person and more online meetings. Again, this has implications for customer engagement and supply chain strategies that need to be fully analyzed.
A Case for Acceleration
Analytics products that have a real-time focus will become more important because rapid, erratic and unpredictable conditions call for up-to-the-minute analysis and the use of technology that can help improve trust in data and other assets and remove inefficiencies from business processes/interactions will also become more important.
Additionally, while the outcome of analytics processes is naturally often the focus of attention, the foundational role of data management and governance should also be considered. In the VotE: Data & Analytics, 2H19 survey, 72% of respondents agreed that data governance is seen as an enabler of business value rather than a cost center at their organization. While businesses shouldn't slow down their investments in analytics, those investments will ultimately have low return on investment if underlying data management practices and technology are not robust.
Most enterprises will be wary of investing in new analytics products and services at this time and can be expected to leverage existing investments in analytics products and services to respond to these evolving requirements; however, the need for rapid responses to changing requirements might also see demand for shorter-term contracts and experimental projects that enable access to specific functionality to provide the business with what it needs now.
In the longer term, we expect accelerated investment by leading-edge companies in new data and analytics projects as travel and work restrictions begin to be relaxed and business shows signs of returning to normal, while forward-thinking companies will already be investing in AI-driven data science modeling to assess when that might be.
Industry Sectors that are at the Front Line of Responding to the Coronavirus Pandemic (such as government, education, healthcare, pharmaceuticals and research)
That accelerated investment is already underway for organizations at the front line, where we are seeing not only increased use of data and analytics but also investment in new data and analytics projects to understand and model infection patterns, develop vaccines and treatments, and understand the ramifications.
A prime example is the UK's NHS, which has announced a new initiative through its NHSX transformation program to create a new single COVID-19 data platform designed to combine all relevant data from across the NHS, social care and partner organizations to drive dashboards aimed at providing government decision-makers with real-time data on the spread of the virus and the capacity of the healthcare system to cope.
Many of these accelerated investments will be necessarily short term, and the NHS project is specifically designed to last only until the outbreak is contained, with agreements in place with the suppliers (Microsoft, Google, Palantir, Amazon Web Services and Faculty.ai) to destroy or return the data as the current emergency abates. However, there is also a commitment to learn lessons from the project that can result in long-term improvements to data collection, aggregation and analysis.
Similarly, as life eventually begins to return to some form of normality, ongoing long-term investment in analytics and modeling projects can be expected from both businesses and government and healthcare agencies alike as they look to prepare for and mitigate against the potential for similar scenarios in the future.
Nick Patience is 451 Research’s lead analyst for AI and machine learning, an area he has been researching since 2001. He is part of the company’s Data, AI & Analytics research channel but also works across the entire research team to uncover and understand use cases for machine learning.
Jeremy Korn is an Associate Analyst for the Data, AI & Analytics Channel at 451 Research, where he covers artificial intelligence and machine learning in the enterprise. In particular, he focuses on the legal and ethical challenges raised by these emerging technologies. In addition, Jeremy helps lead the Voice of the Enterprise: AI and Machine Learning survey, which provides qualitative insights into AI adoption, use cases and infrastructure.
Rachel Dunning is a Research Associate at 451 Research. Prior to joining 451 Research, she graduated from Fitchburg State University Magna Cum Laude with a BS in Cognitive Psychology and Economics. While attending school, she gained exposure to research methodology and data analytics through her involvement in several academic research projects. She is conversationally fluent in German.