TechRivo empowered an industry player in the healthcare market by creating customized software for their sales forecast.
Over the years, the pharmaceutical industry has shown problems on its value chain due to the inefficient allocation of resources. Such problems raise challenges for both the industry and the ecosystem that supports it. For pharma manufacturers, the unpredictability of drug consumption causes misalignments between supply and demand. For pharmacies and retailers, this problem directly affects their ROI. The excess stock of non-demanded products results in a loss mainly due to expired products. While the lack of stock in demanded products leads to loss of business opportunities and revenue.
On one hand, the healthcare and pharma industry is in need of technological disruption. In their Global AI Survey, McKinsey & Company concluded that the “Healthcare systems and services” and the “Pharma and medical products” are ranked on the bottom of the sectors with AI capability embedded. On the other hand, medicine consumption is predictable aggregating large amounts of data. Factors such as weather, seasons, viruses, pandemics, demography, and consumption trends strongly influence sales.
It is possible to identify market opportunities and reduce pharmaceutical waste by understanding the characteristics of the industry. Combining the data points provides an opportunity to impact pharma sales and consumption by offering a technology-driven solution.
With today’s technology, the development of customized software that can disrupt the market and empower radical competitive advantages is a reality. The availability of open-sourced data and the increased capacity to gather and process large quantities of information provide the solution for sales forecast problems.
The TechRivo team created a remarkable product to respond to the client’s problem. The product was structured as a platform powered by machine learning algorithms. The platform enhanced users with visual dashboards enabling sales forecast for the healthcare market. With this solution, the client now has access to valuable information, due to its granularity to specific times, locations, and market segments.
The way the system works is by extracting data from multiple data sources. The information extracted is then stored in the client’s database, allowing the platform to create forecasts. Finally, the platform transforms the predictive data into user-friendly dashboards.
The resulting dashboards are easily used within the company. Departments such as production, operations, and sales gather business insights and can better adjust the supply to the forecasted demand.
The forecasts generated can also empower the client’s core systems (ERP, CRM, etc.) through a REST API to avoid a decentralization of business information.
At TechRivo, we used NumPy, Pandas, and DASK libraries for the exploration and manipulation phases of the app development.
Additionally, we worked with Gradient boosting, KNN, ExtraTree, ARIMA, RandomForest, Lasso, and Neural Networks as the machine learning models.
Through the use of LIME and SHAP libraries, the platform was also able to provide explanations for the models’ results. This means that users have access to the weight of each data point for each prediction. This aspect is particularly useful to understand the market and better adapt business strategies.
Results of the Sales Forecast
As a result, TechRivo’s client raised their accuracy on prediction tasks in a significant percentage. They increased sales by marketing products with higher demand and, therefore, higher conversion rates. Pharmacies and retail stores reduced waste by lowering the stock on non-demanded products.
The prediction and availability of seasonally demanded products have immeasurable advantages. The smart allocation of resources to necessary products, not only benefits the client but also the environment by reducing wasted products.
Using a sales forecast platform had a disruptive and positive impact on the healthcare market. Industries like Fashion, Energy, Finance, Telecommunications, Transportation, and Agriculture can also benefit from sales forecasting.