Navigating Turbulence — How Data Innovation Rescued Businesses from Global Turmoil

Navigating Turbulence — How Data Innovation Rescued Businesses from Global Turmoil

In the dynamic global business landscape, crises serve as powerful drivers for organizational adaptability and innovation. This article delves into the years 2017–2019, marked by fuel market crises and the innovative data-driven solutions implemented in response.

We analyze the business impact of each crisis, highlighting pioneering data-driven solutions. The second section of the article provides a structured analysis of crisis scenarios, depicting the intricate relationships between crisis narratives, business challenges, and deployed solutions.

The MIT CISR Data Monetization Framework is explored, encompassing three approaches: Improving, Wrapping, and Selling.

  1. “Improving” delivers financial value indirectly by improving processes and work tasks with data, thus reducing the cost of goods sold or reducing overhead costs.

  2. “Wrapping” delivers financial value indirectly by bundling core products with analytics features and experiences, thus increasing the product value proposition.

  3. “Selling” involves the direct conversion of data or information solutions into revenue.

In the upcoming sections, we explore each crisis, examining the unique challenges and the transformative data-driven solutions. This journey unveils the impact of data on businesses, offering a comprehensive understanding of how challenges shape and evolve industries. Each chapter will be followed by concise insights into the prioritized business domain.

Crisis scenarios, business challenges, and data solutions

1. The fuel volatility crisis — 2017-2018

Crisis scenarios

The fuel crisis spanning 2017-2018 triggered by volatile oil prices, supply disruptions, and geopolitical tensions, had far-reaching consequences on global economies. The Organization of the Petroleum Exporting Countries’ (OPEC's) production cuts, coupled with the U.S. sanctions on oil-producing nations, exacerbated the situation.

While the oil-importing countries reaped benefits, the oil exporters had to diversify their economies. Fortunately, by late 2018, oil prices began to recover.

Business challenges

  • Shift from ad hoc "Excel-based company management" to a unified reporting system

  • Persistent issues with incomplete, delayed, and inaccurate data

  • Lack of cohesive logic connecting data from diverse departments and IT systems

  • Data discrepancies hindered mission-critical decision-making

  • Clear overarching objective despite challenges with annual growth exceeding 30%

Data solutions

  • Compounded complexity due to fragmented IT systems and the absence of centralized master data 

  • Objective: Develop ETL (Extract, Transform, Load) system for comprehensive management reporting

  • Phases include data collection, addressing consistency, and quality challenges

  • Data transformation focuses on processing and structuring for in-depth analysis, requiring integrity and uniformity

  • Utilization of Microsoft stack, integrating Power BI for visualization and reporting

  • The final step involves crafting user-friendly dashboards and reports with an emphasis on data security, access control, and meaningful information presentation

  • Continuous monitoring and data updates are crucial for sustaining the relevance and precision of management reporting

  • CFO played a pivotal role as the visionary driving innovation in the business domain.

All these steps made it possible to realize the main goal – Improvement (in accordance with the IWS Framework). Resulting metrics – can be seen in the diagram in Chapter 3.

2. Global political turmoil and macroeconomic instability: Brexit, Trump impeachment, and the onset of COVID-19 — 2019

Crisis scenarios

In 2019, Europe found itself entangled in a web of global political upheaval and macroeconomic instability, with a particular spotlight on the challenges within fuel markets. Brexit tensions strained the relations between the EU and the UK.

Adding to this turbulent mix, Trump's impeachment inquiry intensified transatlantic tensions and reshaped the political landscape of Europe. In the midst of these multifaceted challenges, there was a pressing need to prioritize prompt customer payments and robust governance.

Business challenges

  • Management recognizes the vital role of fast and efficient customer payments.
    Strategic development of internal financial technology and data products tailored for fuel markets

  • The necessity to respond rapidly to dynamic changes in customer behavior and payments

  • Critical pivot during the turbulent 2019 for resilience amid market uncertainty

  • Necessity to democratize data access for quicker decision-making at lower levels

Data solutions

  • Stages include refining existing products and establishing performance metrics

  • The transition from Scrum to Waterfall methodology to refine the basic system

  • Precise handling of data collection and processing for secure financial transactions

  • Focus on solving data security and processing speed challenges

  • Increased role of the analytical department for quick data access based on employee levels

  • Reduced data request processing time from six business days to one day

  • Efficiency gains significantly enhance operational flexibility across company divisions

  • The Chief Controlling Officer (CCO) demonstrated expertise in managing payment and liquidity during the crisis

Benefits of data-driven solutions

If we use the IWS framework described above, we can see the following picture. With the data-based products I described in the section above, we have the following distribution.

In the third article, I will articulate the comprehensive impact on the EBITDA indicator, presenting the conclusive figures that underscore the discernible influence on our business, as per our perspective.

About the Author:

Andrii Vasyliev is Chief Data and Analytics Officer at E100. With over 12 years of experience, his achievements include building data platforms from scratch, implementing principles of data governance and management, and creating data-driven products that add significant value to organizations.

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