By Abrán Padilla
I’m in the business of nuts.
I have been for over a decade. While Big Data’s impact has been widely documented in industries such as healthcare, marketing and financial services, I’ve seen first-hand how ‘crunching’ data can impact how almonds and pistachios are processed, priced and sold.
The U.S. nut industry is big business. California’s almond industry is valued at $3.9 billion and provides more than 80 percent of global supply. California’s pistachio business makes up approximately 40 percent of the world’s supply and it’s growing. In a competitive industry such as ours, business decisions cannot be made on a hunch; we need evidence that only data-backed predictions can provide.
I work for Paramount Farms, the world’s largest grower and processor of almonds and pistachios, delivering approximately 400 million pounds of nuts a year globally. You may be familiar with one of our brands. As Director of Operations Finance, I ensure that we are producing the highest quality products for consumers, while running our operations efficiently and keeping costs down.
How? Through analytics.
With a background and MBA in finance and computer information systems, I recognized early on in my role at Paramount the potential of putting data to work by using analytical models. Among the benefits: forecasts that sparked fundamental change in how our businesses operated – such as improving production processes and inventory level accuracy.
At the same time, my company was shifting to a data-driven culture where Big Data is at the root of everything we do. So roughly one year ago, I decided it was time to up my game and pursue formal training in predictive analytics, a fast-emerging area of analytics in which structured and unstructured data is evaluated with mining, predictive modeling and “what-if” scenario analysis.
I researched several academic programs; however, I could not afford to leave my job to pursue a degree, so an online program was the best choice. From the start, Northwestern’s Masters in Predictive Analytics stood out for three reasons: institutional academic caliber, the chance to work with students from a range of industry backgrounds, and a high-quality focus on predictive analytics.
During the program, I learned from top-flight professors and worked with students from a diverse range of professional fields, from banking to food services. In terms of content, the courses taught us how to code, develop and diagnose predictive models, as well as “logistic regressions” that can identify the probability of an occurrence of an event — such as bankruptcy, illness or inventory losses – that could impact a business’ ability to succeed. We also gained and sharpened skills in such non-technical areas as interdisciplinary collaboration, applying analytics to business challenges and communicating data-driven findings to colleagues and senior level decision-makers.
Through the analytics technologies, concepts, and techniques I’ve been exposed to in Northwestern’s program, I now realize that – while I was already a champion for predictive analytics at Paramount Farms – there’s so much more that I can do to contribute and drive success.
One good example: for our almond byproduct business, there are numerous USDA variables we need to test and measure in order to identify the relevant attributes of the inventory before selling the product in the market. Before implementing analytical modeling, the annual revenues for byproduct sales totaled approximately $0.5 million. After developing an analytical approach to our byproduct sales, our revenues (on the same byproducts) totaled more than $13 million.
However, the next improvement occurred when we implemented predictive modeling techniques I learned at Northwestern to our analyses. With byproduct sales, we were able to take the 15 attributes associated with these goods and identify the variables that were statistically significant in order to accurately price the byproducts based on those variables. This technique is expected to yield an ROI of an additional $800,000 to $1 million in revenue.
In my experience, predictive analytics allows companies to take their data-driven decision-making to another level by helping firms to identify opportunities that are not obvious to non-analytics based firms—thus creating a competitive advantage for analytical companies.
I’m a true believer in the impact that big data and analytics skills can have for businesses, no matter what one’s industry or responsibilities may be. Indeed, as a business, agribusiness, and economics professor at TaftCollege and CaliforniaStateUniversity, Bakersfield, I discuss analytical modeling in my courses and will be introducing a new course for Winter 2014 focused on analytical modeling techniques for economics and agribusiness students at CSUB.
Whether you are a student considering your college path or a current business professional, it is in your best interest to seek out degrees and courses focusing on analytics skills. I can tell you first hand that, when business leaders see an analytics professional driving results via data-driven recommendations, they notice it, appreciate it, and reward it with trust and new opportunities.