Go Big with Data, or Go …Out of Business?

As a CPA focused on the world of biofuels, it has become abundantly clear that energy will, sooner rather than later, be interconnected with massive computing power, data collection and storage capabilities—and will change how we all do business.
By Donna Funk | August 17, 2018

About a year ago, I remember reading an excerpt by Bill Gates—founder of Microsoft and one of the wealthiest citizens on the planet—advising college graduates on the fields he would explore if he were starting out in the world today. In essence, he advised considering these three areas: artificial intelligence (AI), energy and biosciences. 

His interest in energy was not surprising as he stated that making clean, affordable and reliable energy will be essential for fighting poverty and climate change. Regarding AI, Gates remarked, “We have only begun to tap into all the ways it will make people’s lives more productive and creative.” What a simple explanation for something so wildly complex and underdeveloped, I thought.

With so many news headlines circling on a daily basis regarding “future possibilities” of AI, the Internet of Things and data management, it’s easy to dismiss these topics and file them away in the “not now” pile. But as flashy as the promises of applying AI technologies might be, if you look closely, it’s already starting to take shape—and the foundation is being laid out right before our very eyes. 

We Are All Witnesses
The International Data Corp. forecast in a report that the amount of data being generated in the digital universe will grow to 44 zettabytes by 2020—that’s 44 trillion gigabytes! One can’t help but marvel at the speed in which the big data adoption is already changing industry landscapes and operations. We are able to collect and analyze more data than ever before. But to stay competitive as the data growth continues to explode, it will be imperative to derive maximum value from the data captured.

As a certified public accountant focused on the world of biofuels, it has become abundantly clear that energy will, sooner rather than later, be interconnected with massive computing power, data collection and storage capabilities—and will ultimately change how we all do business from virtually every standpoint.

Even accountants are changing the way we gather, analyze and provide data. Moving away from traditional financial data reporting and the reliable spreadsheets, we are gathering more data from many sources and using technology to support assumptions and draw conclusions. We are emerging as advisors with more and varied data for predictive financial and operational analytics. 

The Big Data Algorithm
The business algorithm for data management is quite simple: The ability to extract broader types of data can ensure that a business becomes more agile.  Big data provides real-time information to enrich usability. Usability drives more meaningful business decisions.

Biodiesel companies that adopt a data management system are able to govern big data and build solutions to:

• Improve return on investment through environmental and cost of production analysis (as well as understand changing market conditions) to determine whether yields might be profitable and achievable.

• Improve production efficiency through remote monitoring and analysis, and avoid environmental and safety issues.

• Secure cost-effective and timely supply chain and logistics management through timely deliveries and optimal production facilities.

• Expand market analysis of current pricing and trends to determine production, optimization and expansion strategies.

While extensive amounts of data can be used to create more streamlined supply chains or performance optimization, none of this can happen without data management systems. Businesses must know how to gather, use and analyze data to optimize production and pass product traceability data further along the supply chain. 

Data Management Best Practices
Implementing data management systems is prescriptive and unique for each biodiesel organization. The importance of protecting the quality and security of your data will be imperative for its management. When adopting and managing big data collection systems, there are several recommended best practices to which organizations should adhere. First, audit what data is being collected, through what means and measures, and how it is processed and stored. Next, establish consistent data definitions to streamline data collection and storage. Set business objectives and goals to store and analyze only necessary data. Implement data governance procedures related to data management, access, usage and security. Lastly, distribute verification responsibilities to ensure policies are being followed and educate on procedures. Poor-quality data can be very costly; IBM estimated that the cost of poor-quality data was $3.1 trillion in 2016 alone.

Big data has taken the world by storm and is helping businesses prepare data and conduct predictive analysis so that biodiesel companies can overcome future challenges easily. While having tremendous amounts of data will not necessarily give you a competitive advantage, it will help you extract actionable information, which can impact how quickly and easily you can analyze business decisions.

Author: Donna Funk
CPA and Principal, K·Coe Isom

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