In our digital world, it’s critical for life sciences companies to invest in technologies like SAP Analytics Cloud to navigate data and drive new business decisions with speed and efficiency. In this industry, increasingly  larger quantities of data can be analyzed for decision-making and innovative leadership. To improve efficiency and understand demand in a competitive landscape, life sciences companies must continuously use this data to predict and adapt to future outcomes.

Analytics-based optimization also helps companies save time, money, and resources. Choosing the right suite of analytics tools is part of an overall data and analytics strategy; it takes time and will vary by organization maturity and overall business goals but is crucial to enabling companies to be data-driven.  This blog will cover one analytics tool that is gaining traction, especially amongst companies that use SAP as their ERP system – SAP Analytics Cloud.

SAP Analytics Cloud centralizes data from many sources and systems for predictive analytics and modern visualization. The platform solution enables a single process that allows stakeholders from all levels within a company to collaborate and aggregate data, solving the age-old issue of data access being a bottleneck of skills or resources. Findings can be quickly summarized through modern visualization options and dashboards, and shared between teams.

Especially in this ”new normal”, where demand for PPE and medical devices is extremely disrupted by COVID-19, companies should be utilizing all available data and analytics capabilities to  increase agility and flexibility.  Conducting high-demand assessments at a large scale despite unusual or limited data will help stabilize medical supply chains and inventory levels and guide decision-making for analysts who haven’t dealt with this type of disruption before. Reporting and analytics conducted through SAP Analytics Cloud can adjust for these large, rapid demand changes. Overall, life sciences companies, especially those operating in pharmaceuticals and medical devices, should invest in tools like SAP Analytics Cloud to access a platform for business insights, remote collaboration, and forecasting.

The Benefits of SAP Analytics Cloud for Life Sciences Companies

Predictive Analytics

One of the most exciting uses for SAP Analytics Cloud right now is its predictive analytics capabilities through Smart Predict. This can benefit all types of decision makers due to its easy-to-use interface which requires no coding skills or behind-the-scenes knowledge about how the models are built. Model outputs can be incorporated directly into dashboards and reporting to augment analytics with projected values. Smart Predict supports classification to predict an either-or value, regression to predict a specific number, and time-series to support typical forecasting scenarios.

SAP Analytics Cloud also helps with planning and predictions for circumstances such as demand increases for consumables and diagnostics, production capacity, inventory visibility for products like PPE and devices, and workforce constraints. Users can obtain a deep look into data and build simulations to understand performance at every business level, forming strategy plans and monitoring models for proactive performance and adjustment.

Business Insights

Moving away from older and less sophisticated reporting solutions, SAP Analytics Cloud provides automated analytics and insights based on machine learning and statistics. Built-in analysis tools like the value-driver tree enables users to quickly answer questions and make decisions based on performance metrics drawn from live data. Instantly, this modernized tool improves the experience for users and provides insights on KPIs in real time through dashboards and other interactive visualization methods. This can be used for budgeting, risk analysis, and many other planning purposes.

Remote Collaboration

Tools that facilitate and simplify collaboration are becoming more important in the life sciences industry,  especially with a transition to remote work. For example:

• Manufacturers need to communicate with researchers and suppliers to speed up approvals.
• Biologics and vaccines companies are collaborating with regulatory agencies.

In some cases, competitors are working together to produce pandemic solutions for the greater good.

SAP Analytics Cloud provides tools to help users share information and gain input across their organization,  supporting fast information exchange from systems with many features through AI-driven data visualization based in the cloud. Visualizations and simulations can be shared with other users in the organization so employees can gain clarification or better insights as they collaborate using the same business data. Companies can easily connect multiple systems through a single solution, best promoting clarity and trust of business information and data across teams.

Use Cases Better Suited for Other Tools

Custom Technical Solutions

SAP Analytics Cloud is the future of SAP analytics and reporting and provides excellent visualization capabilities for companies with broad use of SAP tools and rich in business analysts. Use cases requiring deep, advanced analytics may be better solved using other tools. For teams that have the skillsets for more technical solutions, integrating with more powerful analytical platforms or coding solutions will provide data scientists better control in building custom solutions. There are many useful analytical techniques beyond the current SAC offering that your analysts and data scientists may need to use.

Explainability and Accountability

While SAP Analytics Cloud does have good reporting on key indicators that drive a predicted value and accuracy metrics that users can compare across model runs, there is limited ability to see which algorithms and hyperparameter tuning is being used. This can pose an issue in certain use cases in regulated industries where each prediction needs to be explainable.

Data Preparation

It’s a regular data science adage that preparing the data takes up 80% of the time spent on a predictive analytics project. Handling data quality issues and outliers, combining or creating different attributes, and selecting which data are the most impactful in modeling are all examples of data preparation. Currently, SAC only supports light data preparation like changing data types, fixing/replacing values, and including or excluding certain columns. More rigorous data preparation can be addressed by coding languages or other data science platforms, and there are also tools that specialize in data preparation alone.

The benefits and capabilities of SAP Analytics Cloud are tremendous for life sciences companies. While it won’t solve every ad hoc analyst question, it will save time and money by providing comprehensive, rapid data analysis and reporting - especially relevant to senior leadership. If SAP Analytics Cloud seems to be a good fit for your business, Clarkston can help you with integration and implementation.

Contributions by Nathan Keliher and Courtney Loughran.