How Data Science and Analytics can Support Corporate Strategy in Turbulent Times
Shilpa Yelamaneni, Director of Data Science & Advanced Analytics, Ecolab
Shilpa Yelamaneni, Director of Data Science & Advanced Analytics, Ecolab
In a turbulent economy like that ushered in by COVID-19, business leaders urgently need the right tools to enable swift reaction and pragmatic business decision-making, whether in survival mode or opportunistic mode. The pandemic has posed both challenges and opportunities in many dimensions by shifting industries, transforming supply chains, creating new market demands, requiring widespread work-from-home, and the forced adoption of digital capabilities. In this article, I will be highlighting the key pain points which organizations can address by leveraging the discipline of strategic analytics to stay in front of the crisis and benefit from the opportunities it brings.
Strategic analytics is a function dedicated to supporting the research and analysis of a company’s internal and external operating environment. It can both assess current corporate and business strategies and help formulate new ones.
While strategic analytics enables executives to formulate new corporate strategies, traditional analytics (encompassing data science, advanced analytics, and BI) is used to manage business performance objectives and help innovate products and services. Strategic analytics is even more important in the context of the current pandemic. In the digital-led recovery, these capabilities can help identify unique value propositions and competitive threats in newly developing ecosystems, based on growing data and AI possibilities.
Strategic analytics can help organizations weather COVID-19 in many ways, but three key aspects demonstrate its value in the processes of reimagining the future, redefining core competencies, and creating sustainable business models.
Creating a Sense-and-Respond Decision Support Model
Sensing and responding to shifting market conditions in a timely manner and with the right business priorities is critical for corporate executives, who have to review information frequently to drive operational efficiencies, business acquisitions, and diversification of products and services, as well as gauge competitive forces and assess new technology/digital investments.
The sense-and-respond decision support model, using a firm’s internal and external drivers, is essential for:• identifying new correlations and external business drivers such as economic shifts, trends, and competitive changes;
• assessing current operational efficiencies and the performance of products and services;
• projecting business trends in conjunction with industries and markets;
• detecting performance outliers in internally and externally available data and
• automatically alerting or responding to ecosystem partners and stakeholders.
Enabling the Test-and-Learn Strategic Approach
Businesses grappling with the post-COVID ‘new normal’ are exploring creative changes to their business models, such as contactless services in food and hospitality, distance learning at academic institutions, home-sharing services among hotels, and many more. As companies deploy new strategies and business models in unpredictable times, they need a sustainable way to test, learn, change, and continuously adapt in a dynamic environment.
Strategic analytics can help facilitate the test-and-learn process of new business models, ventures, and expansions by:
• measuring performance, potential cannibalization, and market responses by using internal data, external customer data sets, social data, and sentiment analysis;
• simulating demand and market responses from consumer behavior modeling, new market entry analysis, and operations analysis for early indications of success; and can
• automate the test-and-learn process through proper upfront instrumentation in detailed business processes.
Supporting Businesses to Survive and Thrive
Given the digital-led recovery from COVID-19 and resulting rapid digital transformation across all industries, the new business environment will have even more digital signals and data to help continuously reinvent products and services. For example, consumer preferences will be increasingly captured through contactless services, enabling continuous improvement of existing products and the emergence of new eco-systems.
Strategic analytics can help growing businesses thrive by
• avoiding over reliance on discrete sources of advice on new/current businesses;
• providing actionable insights. The information needed is often as unique as the problem itself, requiring a combination of research, and current performance metrics and strategies. The underlying skills are often dispersed throughout an organization;
• helping simulate the impact of ongoing business decisions using digital twins and additionally capturing the responses of other AI ML solutions in the ecosystem;
• improving time to decision making by facilitating executive alignment, preventing translation gaps, and minimizing the administrative burden. The analysis would be consistently sourced from a single point of contact.
Acknowledging the importance of strategic analytics is a critical step towards creating an agile model of business operation. More than ever, businesses need to closely analyze the opportunities and threats presented by macro-economic, societal, and industry-wide shifts. When strategic analysis is undermined, companies not only struggle to survive, but can quickly be extinguished by competitive and market forces. While the objective is not simply to establish yet another department, the main goal is to create a dedicated focus that is not derailed by day-to-day reactive analysis at the expense of key strategic decisions. Strategic analytics must be aligned with corporate strategy, finance, and industry insight functions that are well positioned to influence strategy through a deeper understanding of corporate / organizational decisions.
