Published: June 5, 2020


Many enterprises have historically put significant time and effort into initiatives to identify a 'single version of the truth.' There are distinct advantages to be had in agreeing on a single definition and value for key business metrics and performance indicators. However, not everything can be defined with such certainty, especially when it comes to predicting the future. The extreme levels of uncertainty resulting from the COVID-19 pandemic have highlighted that attempting to definitively predict what will happen next is a fool's errand. While understanding of the potential value of data to strategic decision-making has never been greater, there is also an understanding that historical data models and assumptions likely cannot be applied to analyzing whatever the post-coronavirus 'new normal' will be. Analytics may be more vital than ever, but the level of uncertainty demands scenario-based approaches to analysis that reflect multiple potential outcomes.

The 451 Take

Given the unprecedented nature of current socioeconomic conditions, attempting to predict the future with any degree of certainty based on historical data and models is likely to be futile. While companies trying to adjust their strategies would like certainty, it simply isn't something that can be delivered by analytics projects given that historical models and assumptions no longer apply. Agility and pragmatism will be key. While the value of data and analytics is better understood than ever, we also see a greater acceptance that uncertainty needs to be embraced rather than avoided. Enterprises should focus on scenario analysis and planning and prepare to make rapid decisions as the situation evolves.


Great Expectations

In early April, we advised that, amid coronavirus uncertainty, analytics should remain an enterprise priority. The various conversations we have had with enterprises and vendors in the data and analytics space since then have reinforced that perspective. Enterprises are naturally rethinking their priorities in response to the coronavirus pandemic, and in some cases, budgets might be allocated elsewhere. However, we have seen an acceleration in the recognition of the importance of data and analytics, particularly among senior executives.

For example, 451 Research recently took part in a virtual roundtable event involving chief data officers and senior data executives from companies in the retail, automotive and financial services industries. While the number of participants was (deliberately) small, we were still struck by the level of similarity being experienced by the participants in relation to their data and analytics initiatives.

Senior managers are now more aware (or aware earlier) of the value of data and analytics projects as they look to understand what steps need to be taken to improve operational efficiency and adjust to evolving workforce, customer and supply chain requirements. It is clear that analytics and data-driven decision-making holds the key to emerging prepared for whatever comes next as the current lockdown conditions are relaxed. The strategic importance of analytics projects being undertaken has therefore been elevated, even if budgets have not necessarily also grown.

Spending Impact

While we have no doubt about the perceived value of analytics amid coronavirus, one of the key questions we have been grappling with is what impact it will have on data and analytics budgets and, therefore, revenue. The messages we have been receiving are mixed, but there are indications that the data and analytics market could be relatively resilient.

451 Research recently hosted a webinar with members of the 451 Alliance and took the opportunity to conduct a quick poll on the impact of COVID-19 on their data and analytics projects. While the number of participants was not statistically relevant, again the responses were anecdotally interesting. Less than 6% of respondents indicated that they were decreasing analytics projects and diverting budget elsewhere, while almost three times that number stated that they were actually increasing spending on analytics initiatives.

For the majority of respondents, however, budgets are remaining steady: Just under 30% indicated that they are seeing an increased number of analytics projects, but without additional budget, while a little less than half of all respondents stated that coronavirus had not significantly impacted their analytics initiatives.

Embracing Uncertainty

As noted, one way in which analytics projects are potentially being impacted by COVID-19 is related to the paucity of relevant data, especially in relation to what happens as lockdown measures are relaxed. Given the unprecedented nature of the impact of coronavirus, it is almost impossible for a retailer, for example, to try and predict the impact on customer behavior, since historical data models are likely no longer relevant, and no data currently exists with which to create new models.

In response, analytics teams have two primary choices: Make use of whatever relevant data they can lay their hands on and prepare to adjust responses as new data becomes available, or embrace uncertainty by turning to scenario analysis. These are by no means mutually exclusive, and indeed we see companies attempting to do both – collecting whatever data they can to try and estimate plans for the future, while also accepting that those estimates need to be based on a variety of potential scenarios.

Scenario analysis requires a cultural and cognitive shift away from trying to predict a definitive outcome with a degree of certainty and toward analysis that embraces uncertainty. It requires imagining multiple potential futures based on a variety of assumptions and preparing accordingly. The analysis can be revisited, and both the imagined scenarios and related assumptions can be narrowed over time as new data becomes available.

451 Research is not just advocating for scenario analysis but is also adopting the approach to augment our market revenue and growth forecasts with alternative economic- and market-specific assumptions. As a result of which, we are providing a range of outcomes for the various market segments we cover based on assumptions of mild, moderate, extended moderate, and severe economic downturn.

The results of this scenario analysis have already been published for the IT management-as-a-service, cloud security, and infrastructure-as-a-service sectors. Similar analysis for data platforms, data management, and data science and analytics will be published in the coming weeks.

Matt Aslett
Research Vice President

Matt Aslett is a Research Vice President with responsibility for 451 Research’s Data, AI and Analytics Channel. Matt's own primary area of focus currently includes distributed data management, data catalogs, business intelligence and analytics, data science management, and enterprise knowledge graphs.

Jeremy Korn
Associate Analyst

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
Research Associate

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.

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