One practice many retailers and distributors have adopted is Algo retailing. The ultimate goal of Algo retailing is to blend machine learning and AI with the human element of data reporting to seamlessly integrate retail data across their supply chain to unlock value, improve their business's performance, and generate higher profits.
Since the pandemic's impact has sent shockwaves through the human elements of retail businesses, many retailers now wonder how they can further integrate AI into their practices to mitigate their losses and maximize profits. This is why the retail data science experts at Proxima 360 have created a new retail-focused AI tool, Adivino.
Issues With Traditional Ad-Hoc Reporting
Even before the COVID-19 pandemic, retail business owners, managers, and employees were limited in their ability to find cohesive solutions that balanced machine learning and analytics with human elements of data reporting, which traditionally involves human workers building sales forecasts and inventory orders off spreadsheets and reports from previous years. Analyzing and mapping trends in consumer behavior, such as which items sold best during certain times of the year and who to, help provide a clearer picture of what sales forecasts might look like in upcoming months.
Time is money - and this process consumes much of it. Human error is also an issue: if an employee entered incorrect information into a spreadsheet, it could skew future reports for months or years, meaning workers must devote even more time to analyzing old reports to adjust their current sales forecasts.
In the post-COVID retail world, traditional reporting processes have become even more complicated. Retailers who had forecasted for March-December 2020 saw their projections voided from the pandemic. Suddenly, there was no way to tell how retailers could project their inventories or finances for the remainder of 2020 without encompassing multiple new factors in their data, but doing so meant retailers were even further limited in the bandwidth of their human capital.
A Dynamic Data Solution
Adivino was created to address the challenges brought about by traditional ad-hoc data reporting in retail and new issues caused by the onset of COVID-19. Adivino utilizes AI that allows human workers to identify these issues as variables within the software. Adivino then creates algorithms based on those variables, allowing it to learn different projected scenarios which might impact the numerical values of a spreadsheet's report and create predictive forecasting models that would require minimal adjustment by employees.
Adivino would enable retail businesses and employees to do away with traditional cumbersome data reporting. Instead of scanning through outdated spreadsheets for accuracy or adjustments, build algorithms on different scenarios from scratch, revamp those algorithms by hand whenever the scenarios they were built for are no longer applicable, analyze the data, construct a forecasting report, and potentially spend $10,000-20,000 to reactively correct data on an inaccurate report, Adivino's AI is able to eliminate this expensive cycle with near-full autonomy.
Blending Art and Science
The team behind Adivino created the software as an interactive alternative to traditional data analytics and forecast reporting that is cost-effective and user-friendly, allowing retailers to more effectively react to changes they need to make in their data projections - without the need for extensive training of human workers to familiarize themselves with the program.
Adivino's applicability isn't limited to only retailers, however. Any business that sells commercial goods or services could utilize Adivino's tool to maximize their resources and bandwidth in order to better handle large inventories in their supply chain or generate more accurate sales forecasts in a faster and more efficient way. With all this taken into consideration, it's little surprise that the team behind Adivino named it for the Spanish word for "fortune-teller."
