SAP Analytics Cloud (SAC): Implementation

Introduction

Creating a compelling and actionable dashboard is essential for data-driven decision-making. SAP Analytics Cloud (SAC) offers robust tools for data visualisation and analytics, enabling organisations to extract valuable insights from complex datasets. As part of our ongoing implementation project JAITRA, PMTS recommended the following best practices for designing dashboards using SAP Analytics Cloud to maximise their impact and usability.

What is SAP Analytics Cloud?

SAP Analytics Cloud (SAC) is a cloud-based analytics solution that combines business intelligence (BI), planning, and predictive analytics in a single platform. It is designed to help organizations analyse data, make informed decisions, and plan for the future by providing comprehensive tools for data visualization, reporting, and analysis. SAC leverages the power of machine learning and artificial intelligence to deliver smart insights and streamline the analytics process.

Implementation Considerations:

  • Managing Multiple Companies: Implementing SAP Analytics Cloud across multiple companies requires a unified approach to ensure consistent data reporting and analysis. This was challenging due to varying business processes and data structures within each company.
  • Operating Across Multiple Countries: Different countries have unique regulatory requirements, currencies, and languages. Ensuring that the SAP Analytics Cloud solution accommodates these differences while providing a seamless user experience was crucial for global operations.
  • Integrating a Heterogeneous Environment: Companies often have diverse landscapes with various ERP systems, databases, offline/manual data and third-party applications. Harmonizing these systems to work together within SAP Analytics Cloud demands robust integration strategies.
  • Handling Unstructured Data: In today’s digital age, businesses generate vast amounts of unstructured data from sources like social media, emails, and IoT devices. Effectively incorporating this unstructured data into SAP Analytics Cloud for comprehensive analytics and insights is a significant challenge

Key Features of SAC:

1. Business Intelligence (BI):

  • Interactive Dashboards and Reports: Create visually appealing, interactive dashboards and reports to monitor key performance indicators (KPIs) and track business performance in real-time.
  • Data Visualization: Utilize a wide range of charts, graphs, and maps to visualize data effectively, helping users quickly grasp complex information.
  • Ad-hoc Analysis: Perform on-the-fly analysis and explore data without the need for predefined queries or reports.

2. Planning:

  • Collaborative Planning: Enable teams to work together on planning, budgeting, and forecasting processes. Collaborate in real-time to ensure alignment and accuracy.
  • Financial Planning and Analysis (FP&A): Perform detailed financial planning, scenario analysis, and what-if simulations to understand potential impacts and outcomes.
  • Integrated Planning: Seamlessly integrate planning processes with BI capabilities, allowing for a unified view of performance metrics and financial plans.

3. Predictive Analytics:

  • Machine Learning Algorithms: Leverage built-in machine learning algorithms to uncover hidden patterns, trends, and correlations in your data.
  • Predictive Modelling: Create predictive models to forecast future outcomes, enabling proactive decision-making.
  • Smart Insights and Smart Discovery: Use these tools to automatically generate insights and identify key influencers for specific KPIs, saving time and improving decision-making accuracy.

     4. Data Connectivity and Integration:

  • Wide Range of Data Sources: Connect to various data sources, including SAP and non-SAP systems, cloud databases, on-premise databases, and third-party applications.
  • Live Data Connections: Access real-time data from your connected sources without needing to replicate or move the data.
  • Data Blending: Combine data from multiple sources to create a comprehensive view and gain deeper insights.

     5. Governance and Security:

  • Role-Based Access Control: Define user roles and permissions to ensure data security and control over who can access and modify data.
  • Data Privacy and Compliance: Ensure compliance with data privacy regulations and maintain data security with robust encryption and security measures.
  • Audit Trails: Maintain detailed logs of user activities for auditing and compliance purposes.

6. Performance and Scalability:

  • In-Memory Computing: Leverage SAP HANA’s in-memory computing capabilities for fast data processing and real-time analytics.
  • Scalability: Handle large volumes of data and scale your analytics capabilities as your business grows.

How SAP Analytics Cloud Works ?

SAC operates entirely in the cloud, making it accessible from anywhere with an internet connection. It integrates with a wide range of data sources, including SAP and non-SAP systems, allowing users to consolidate data from multiple sources into a single platform. SAC’s intuitive interface enables users to create and share insights without needing extensive technical expertise.

Best Practices for Dashboard Design in SAC

1. Providing Context for the Data

To effectively measure performance, it is crucial to provide context to the visualised data. This can be achieved by:

  • Including Historical Data: Compare current metrics with past data to highlight trends. Displaying historical data alongside current metrics helps users understand the trajectory of key performance indicators (KPIs) and make more informed decisions.
  • Utilising Reference Lines: Add fixed or dynamic reference lines to emphasise important values. Reference lines can mark targets, averages, or other significant thresholds, guiding users to quickly assess performance relative to these benchmarks.
  • Applying thresholds and conditional formatting: highlight specific data points that require attention, enhancing the visualisation’s clarity and usefulness. Use colour coding and conditional formatting to draw attention to critical values that exceed or fall below predefined thresholds.

2. Leveraging SAC Smart Insights & Smart Discovery

SAP Analytics Cloud’s Smart Insights and Smart Discovery tools harness machine learning to uncover hidden insights within your data:

  • Smart Insights: Analyse entire visualisations or individual data points to identify top contributors to a value or variance. This tool helps users quickly understand the factors driving specific outcomes without delving into complex analysis manually.
  • Smart Discovery: Quickly identify correlations and key influencers for specific KPIs, saving time and improving decision-making accuracy. By automating the discovery of relationships and patterns in data, Smart Discovery empowers users to make data-driven decisions with greater confidence.

3. Embracing mobile support with responsive pages

Ensure your dashboards are accessible and user-friendly across different devices by using responsive pages:

  • Tile-based Design: Create responsive pages with tiles that adjust content based on screen size, optimising the viewing experience. This design approach ensures that dashboards are visually appealing and functional whether viewed on a desktop, tablet, or mobile device.
  • Customisation Options: Personalise dashboards for various devices, including mobile and tablet-friendly layouts. Tailoring the layout for different screen sizes improves the user experience and ensures that key information is easily accessible on any device.

4. The 5-second rule

Dashboards should deliver key information within five seconds. Achieve this by:

  • Highlighting Key Trends: Use thresholds to emphasise critical data trends. This approach helps users quickly grasp the most important insights without sifting through excessive information.
  • Simplifying Initial Views: Display only the most important metrics initially, with options for users to explore further. A clean, focused initial view prevents information overload and guides users to deeper analysis as needed.
  • Utilising Filters: Apply story and page filters to manage data display, preventing overcrowding. Filters allow users to customise their view, focusing on relevant data subsets and enhancing the dashboard’s usability.

5. Enhancing Interactivity in Charts

Interactive dashboards allow users to explore data in depth.

  • Drilldowns and Linked Analysis: Enable drilldowns in charts and crosstabs for interactive filtering. This functionality lets users navigate through layers of data, uncovering detailed insights from high-level summaries.
  • Hyperlinks and Custom Widgets: Add hyperlinks to images and shapes for navigating to additional story pages or external resources. Use custom widgets for more control over visualisations, creating a more engaging and interactive user experience.
  • Measure and Dimension Switching: Provide input controls to switch between different measures and dimensions easily. This flexibility allows users to dynamically adjust their view of the data, exploring various perspectives without creating multiple dashboards.

How can we help?

Following recommended techniques for dashboard design during the implementation phase guarantees that the visualisations are very functional and appealing. Key tactics to improve the impact and usability of your dashboards include giving meaning to the data, utilising smart insights, adopting mobile support, following the 5-second rule, and improving interactivity.

To sum up, SAP Analytics Cloud is an essential resource for every company trying to improve its data analytics capabilities. Adopt SAC to get the most out of your data, give your staff useful insights, and give yourself a competitive edge in the data-driven world of today. At PMTS, we’re dedicated to helping you along the way with SAP Analytics Cloud and making sure the installation is impactful and seamless.