BSH: Exploring the cutting-edge capabilities of Gen AI and machine learning for corporate decision-making
Explore BSH’s inspirational journey with SAP and PwC
Leading global manufacturer of home appliances BSH Hausgeräte GmbH (BSH) was keen to understand how it could leverage the latest AI advancements and tools – including SAP Analytics Cloud and SAP Datasphere solutions – to generate tangible insights for its sales and management teams to drive business profitability and growth.
| Industry | Region | Company Size | Partner |
| Consumer Products | Munich, Germany | 60,000 employees | PwC Germany |
data-driven insights to optimize business performance
usability with contextual business data stories
innovative use cases delivered as proof of concept in 6 months
Head of Governance, Methods and Systems, BSH Hausgeräte GmbH
Understanding what really drives the business
BSH Hausgeräte GmbH (BSH) is known around the world for its premium brands of home appliances, for example Bosch, Siemens, and Neff. With 60,000 employees, BSH is part of the Bosch Group and generates an annual turnover of €14.8 billion.
As a global business, to effectively manage performance and profitability, BSH needs a detailed understanding of the underlying factors and relationships that drive its margins and growth. The company wanted to verify the potential value-add of leading-edge technologies for continuously identifying patterns across product groups, customers, and markets to improve and optimize business decisions.
“We want to move from time-consuming, static (monthly) reports to continuously updated, compact, and relevant data stories,” says Heiko Schletz, Head of Governance, Methods and Systems at BSH Hausgeräte GmbH. “The idea is that these data stories will automatically adjust their relevance filters, can offer actionable insights, and will even give valuable hints on how to boost profitability.”
BSH decided to partner with SAP and PwC Germany to evaluate what would be possible if they were to look at their data and business development opportunities with fresh eyes. Could they use Gen AI and machine learning to help controllers and business analysts, relieving them from time-consuming tasks such as going through financial reports, finding relevant figures, and calculating scenarios that impact business performance?
The goal was to use data that BSH already had for generating and delivering new insights in a format that provides relevant contextual information and is easy to understand, at the touch of a button.
Head of Governance, Methods and Systems, BSH Hausgeräte GmbH
Combining AI technologies with expertise and a business data fabric
To develop its proof of concept (POC), BSH collaborated with SAP and PwC Germany on an analytics widget that gives controlling teams access to Gen AI, using SAP Analytics Cloud and SAP AI Launchpad. The result of this approach are new, cutting-edge user experiences. The analytics widget leverages data from the business data fabric based on the SAP Datasphere solution, a key capability in SAP Business Data Cloud, and enriches the business metrics using the SAP AI Core infrastructure and the Generative AI Hub in SAP AI Core.
The SAP solution provides full lifecycle management of AI scenarios with a secure and trusted platform. By simplifying the orchestration of models and providing tools for prompt engineering, the platform accelerates the development of intelligent applications.
The inspirational showcase at BSH relies on key business metrics stored in an SAP Business Warehouse application, using data from six different SAP ERP applications, stretching across the whole global value chain, from production to final customer sales.
The team built the new analytics widget using SAP Business Technology Platform and the flexible integration features of SAP HANA Cloud to connect the company’s business data to a Jupyter Notebook, a standard tool for data scientists. After generating new insights using native features of the SAP HANA Predictive Analysis Library such as regression and clustering algorithms, the solution then adds the results to SAP Datasphere.
Business analysts can easily access these new actionable insights right within their standard working environment. The team connected SAP Analytics Cloud to a large language foundation model to interpret and explain the new insights, using the right level of abstraction and terminology to help business analysts quickly make sense of the data.
“We have achieved a lot together with SAP and PwC Germany in just six months,” says Heiko Schletz. “Key to our successful POC was open and honest communication between all partners, plus a lot of passion to try something completely new. By building a standardized analytics platform with integrated Gen AI capabilities, we can now provide business analysts with quick access to key financial data. Crucially, we are going one step further to enrich the insights by explaining the findings and ideas in executive summaries, making the data-driven optimizations identified by machine learning easy to understand for everyone.”
Head of Governance, Methods and Systems, BSH Hausgeräte GmbH
Bringing Gen AI benefits to real business users
As a first step, BSH, SAP, and PwC Germany successfully developed four practical use cases for business analysts. The new charts and metrics focus on identifying the current business performance, for example by identifying and highlighting the most relevant margin influencers across products, customers, and regions, or finding promising product line-up strategies to optimize product portfolios for specific client clusters. Looking ahead, the solution will also suggest price adjustments to maximize profits across product groups and geographies by leveraging observed and modeled price elasticities.
“In a fast-paced environment, quick access to and interpretation of financial data is essential for business success,” confirms Heiko Schletz. “Using SAP technologies, we have built a widget that uses statistics and machine learning algorithms to generate key performance indicators. Gen AI then augments the raw metrics and complex insights with business context and explains the business impact of the findings in natural language through compact management summaries.”
Using the new, dynamic data stories and management summaries, which instantly reflect changes in the market situation and financial data, BSH would gain the ability to move away step by step from very static forecasts and business plans towards contiously updated business journey maps. These will give up-to-date hints, helping decision-makers to confidently steer the organization into a more adaptive, more profitable future.
“Managers for product families, factories, or plants are always pressed for time,” explains Heiko Schletz. “Having to read through a detailed multi-page financial report package takes time and is cumbersome. It is difficult for an individual manager to distill the most relevant figures and trends within seconds. Business analysts spend a lot of time creating pivot tables and designing spreadsheets and presentations. Our idea was to see if machine learning could provide relevant insights in milliseconds, instead of days. Additionally, our AI solution can uncover useful patterns across countries and products. For example, it might suggest trying out combinations of products and prices in one market that have already performed particularly well in other markets. This means that with our AI solution from SAP and PwC, we can learn much faster from our data and experience, respond more rapidly to trends, and achieve better outcomes.”
As a next step in the move from showcase to real-life operation, BSH would like to integrate additional information from unstructured data sources, such as PDF documents or public data on the internet about market development or other relevant details that impact overall business performance.
Head of Governance, Methods and Systems, BSH Hausgeräte GmbH
Transforming the business with SAP S/4HANA
Looking beyond its collaboration with SAP and PwC Germany, BSH is currently also working to consolidate and simplify its business application landscape, creating the necessary reliable data foundation (“lego bricks”) needed to fully leverage the power of analytics and AI. The company is moving from six separate ERP solutions to a single, global SAP S/4HANA environment that covers all subsidiaries and geographies. “During our migration to SAP S/4HANA, we are also constantly evolving and adjusting our data and analytics platforms,” says Heiko Schletz. “Step by step, we’re getting closer to our vision. Over the next three years, eight teams and more than 100 people will continue to work on rolling out our new SAP S/4HANA standard solution to all our businesses.”
In the future, the company plans to use SAP Analytics Cloud as a central portal for all data-centric tasks, including reporting, analyzing, evaluating opportunities and risks, and predictive forecasting and planning. By implementing SAP S/4HANA, SAP Datasphere, and SAP Analytics Cloud, BSH aims to eliminate manual, repetitive data management and consolidation tasks. Its ultimate goal is to give key decision-makers all the latest figures instantly, relevantly, and reliably, anytime they want, as often as they need. “At the end of our migration and consolidation, we want to be able to complete period-end closing on a country level and on the group value-chain-level in parallel at the same time, without delays,” concludes Heiko Schletz.
Featured partner
PwC Germany is a leading professional services company specialized in consulting, auditing, and business transformation. With 20 offices and over 15,000 people, PwC Germany achieves annual revenues of €3 billion. Focusing on innovation and digital products, PwC delivers practical Gen AI applications by bringing together business, experience, and technology.