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How to do Business Analytics in times of pandemic? What to prioritize?

Last updated : July 22, 2020
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How to do Business Analytics in times of pandemic? What to prioritize?

The changes in people’s behavior since the pandemic began, as well as the new ways to interrelate in non-face-to-face communication, have had a major impact in the way companies operate, disturbing sales, logistics, production processes and the organization as a whole, and, of course, shifting priorities, budgets and project portfolios.
In this highly uncertain environment, companies need to visualize their current business situation, while answering questions that had never been made before in order to act based upon the data and make fast decisions. The new reality must be understood, and for this it is necessary to undertake discovery and exploration processes that can solve the new problems in different ways.
Today, the need for immediacy runs the show. Speedy data analysis and tool generation so the business can make good timely decisions is fundamental, and this is not possible with traditional project development practices.

In short, we are observing that our clients need quick results to contribute to the business as fast as possible, with smaller budgets than those they had before the crisis. In this scenario, our recommendations for data analysis project developments during 2020 are the following:

  • Priorities: Focus efforts on limited subjects, with concrete results, in cycles that last only a few weeks, and then broaden and escalate. Uncertainty calls for the possibility of iteration, conversation, hypothesis formulation, and fast results measurement. Adopt therefore an evolutive approach that allows for experimentation, iteration and results appraisal to provide insights to the business and propose new indicators.
    Consider introducing technologies and partners that can work faster and deliver more frequently. Prioritize initiatives continuously instead of holding on to long-term planning to assign resources more efficiently.
  • Cost management: Prioritize those projects that allow an earlier return on investment, either because they may lower costs or generate more sales. On the infrastructure level, since budgets have been constrained, public clouds are an excellent alternative to consider, for they offer the possibility of paying per use, avoiding thus large investments in infrastructure, as well as agility to access new environments and tools. We talk about this in the article “If you have SAP solutions, have you considered using BI on public clouds?”.
  • Methodology:Agile methodologies become essential in these challenging times, for they promote experimentation and innovation, to later escalate based on demand. Methodologies such as Kanban, Scrum, and others, allow fast deliveries and short iterations (weeks); use them to build inexpensive prototypes quickly (hours), engaging the business areas to validate them continuously.
  • Data structure: As we discussed in the article “Strategy for analytical solutions in companies using SAP®”, the traditional Business Intelligence (BI) approach is primarily based on data warehouse, data marts, reports and dashboards. These solutions analyze what has happened (ex post), while current advanced Analytics approaches are oriented towards prediction and prescription and consider the use of data lakes.
    We suggest using a data pipeline that allows data integration from multiple sources, with the possibility of applying structured and non-structured data analysis, depending on the business’ needs. Use a Data Lake to integrate different sources incrementally.
  • If you already have a data warehouse (e.g. BW), consider new ways of dealing with projects, integrating some cloud components, both for the economy and speediness when building new environments.
  • Evaluate using artificial intelligence (AI): Even though it does not apply to all businesses, the need to find patterns may be supported by AI tools to test the new normality. A certain volume of data and density are needed, since predictive and prescriptive models require history and current times are still displaying uncertain behaviors, so much experimentation is necessary. AI may be deployed in the cloud and the results later integrated into the data warehouse, for a comprehensive management.
    • New datasets that include de pandemic period are required. The previous AI models must be retrained given the high distortions of data.
    • Consider also geographical information due to the impact of quarantines by zones

At Novis we have adjusted our consulting approach to help our clients in navigating this new environment as follows:

  • We work with the participation of the concerned business areas, the IT area, and the company’s senior management to understand their troubles.
  • We do a situation diagnostic for a new scenario, evincing functional breaches.
  • We establish the base line: which technologies are available, where is the data.
  • We propose the best route, considering the specific existing restrictions for each case.
  • We compile existing opportunities and prioritize initiatives according to the business impact or urgency.
  • We develop proof of concept tests quickly (days) before committing budgets. We can quickly set up low-cost environments in the cloud.


Our SAP®, AWS®, Google Cloud Platform® and Azure® certifications endorse that we have the expertise required to work in this new scenario. We can help you find actionable solutions in the short term. We invite you to contact us to discuss your current situation and what you want to resolve.

Authors:  Andrés Teixidó, Digital Innovation and Analytics Assistant;  Gilda Valderrama, Marketing Manager and Novis Bulletin editor.