Challenges: Defining the Data Problem
In the highly competitive food manufacturing industry, fast and accurate forecasting gives a competitive edge. Doing so enables organizations to analyze market share across regions and measure the impact their strategies have. Ottogi knew this, but their previous demand forecasting capabilities faced some challenges.
First, putting all the essential data from the various sources needed for forecasting together was a highly manual process. This led to inaccuracies and out-of-date information, making the forecasts less valuable. Forecasts were done monthly, but Ottogi wanted instant insights due to the fast-changing nature of the business. To fix this, they needed a robust platform for data modeling and a central access layer.
Another challenge was getting data into the hands of business users. Not only did the data need to be accurate and up to date, it needed to be accessible and simple to derive insights from. These insights need to be shared across the entire organization, and not siloed within any one department or line of business. To achieve this, Ottogi needed an analytics solution that was both business-friendly and could foster collaboration, providing users with an accurate 360-degree view of the business.
For Ottogi, SAP HANA Cloud provided the powerful data management capabilities needed to improve their forecasting, while SAP Analytics Cloud offered the BI insights that business users desired.
SAP HANA Cloud brought together all the data needed for forecasting into a single access layer. This data included market research data from Nielsen, point of sales information, and large amounts of data from their SAP BW/4HANA on-premise system. Now, all this data connects without the slow manual processes of the past.
With all this data connected in one place, Ottogi was able to innovate with the data modeling needed for accurate forecasts. Using the high-performance transaction and analytical capabilities of SAP HANA Cloud, they built a powerful model with machine learning to improve the accuracy of the forecasts. Ottogi used the SAP HANA Cloud Predictive Analysis Library. This function library provides algorithms for a variety of machine learning use cases, such as classification, regression, time series forecasting, and more. With accurate predictions, Ottogi minimizes business risk while maximizing profit opportunities.
Using SAP Analytics Cloud Stories, Ottogi easily created customized dashboards to monitor forecasting and derive important insights. These dashboards were based on the algorithms they implemented. With these dashboards in place, the company could be sure all stakeholders were referring to one single source of truth to base decisions on. This meant no more confusion among different lines of business referring to different versions of data. Additionally, in-context collaboration features such as discussion, commenting, sharing, and bookmarking made it simple for users to keep everyone in the loop.
These new predictive capabilities give Ottogi an advantage. With Ottogi able to get accurate demand forecasting results every week, they will be able better judge the impact of their sales and marketing strategies. The forecasts are now more accurate and utilize all relevant data, which helps make data-backed decisions from the insights they gain. Now, Ottogi gains the information needed to analyze their portfolio of food products.
This was all made possible by SAP HANA Cloud and SAP Analytics Cloud, the data management and analytics solutions of SAP Business Technology Platform.
Best of all, these improved forecasting abilities are just the beginning for Ottogi. This new data landscape provides the blueprint for future innovation. With their data management handled by SAP HANA Cloud and the analytics capabilities of SAP Analytics Cloud, Ottogi plans to roll out more analytics use cases in the future.
Ottogi joined the SAP HANA Cloud Early Adopter Care program to turn their use case into a reality. Join today to get expert help.