With SAP’s ever-growing host of offerings and tightening hold on the ERP market, data leaders already know that getting the most out of their ERP analytics workloads is essential for driving decision-making, enhancing operational efficiency, and maintaining a competitive edge.
With the emergence of innovative approaches to SAP analytics built on migrating workloads to a centralized cloud platform like the Snowflake AI Data Cloud, your competitors are already starting to unlock their data’s potential and transform insights into actionable strategies. Those businesses paralyzed by a new SAP purchase and lacking a vision for the best way forward, however, face a growing need for a pragmatic roadmap to ERP integration
This blog will explore a structured four-phase approach to ERP integration that will ensure you can fully capitalize on the power of your analytics capabilities.
Phase 1: Planning, Governance, & Discovery
The first phase of your ERP analytics journey centers around meticulous planning, governance, and discovery. Begin by selecting technology and service partners with a proven track record in ERP cloud analytics implementations, and ensure they comprehend your industry’s specific challenges and compliance needs.
Develop a best-fit architectural plan that aligns with your business goals and integrates seamlessly with existing systems, while remaining scalable for future demands. Involve stakeholders from IT, business units, and executive leadership to ensure robust support for both current and long-term strategic objectives.
You’ll also want to conduct a comprehensive inventory of all data assets across your organization, including legacy ERP systems and external data sources. This discovery process is crucial for identifying potential data quality issues, shaping your data migration strategies, and helping you to avoid stopgap, “swivel chair” analytics once your integration is complete. Establish a data governance framework that outlines policies, procedures, roles, and responsibilities for data management to ensure data integrity and compliance with regulatory standards.
This phase should also incorporate organizational change management, focusing on communication, training, and support structures to help staff adapt to new systems and processes.
Phase 2: Prioritization, Alignment, & Execution
In the second phase, focus on prioritizing analytics projects that align most closely with your organization’s strategic goals. This ensures that resources are allocated effectively to projects with the highest impact. Developing a comprehensive blueprint is essential, detailing technical specifications, data models, integration points, and user interfaces. This blueprint acts as a roadmap for development and implementation, providing clarity and consistency for all stakeholders.
At the same time, align global data domains by establishing common data definitions, formats, and governance standards to achieve accurate and reliable analytics. This alignment supports effective global reporting and provides a unified view of performance, enhancing decision-making capabilities.
Finally, execute your strategy by involving and supporting all regions and business units during the rollout of the ERP cloud analytics solution. A phased execution approach with strong change management measures in place will minimize disruptions while ensuring each segment of the organization transitions smoothly. Utilize regular feedback loops and agile methodologies to make iterative improvements based on real-world use and emerging needs.
Phase 3: Measurement & Calibration
To determine the overall success of your ERP integration, you’ll need to develop comprehensive Key Performance Indicator (KPI) models aligned with your strategic objectives to benchmark the effectiveness of your ERP analytics system. Regularly review these KPIs to ensure they remain relevant and aligned with your business goals, allowing for adaptation to changing conditions.
From there, you’re ready to enrich your analytical capabilities by integrating data from non-ERP sources such as market data, social media, and customer feedback. This expanded data ecosystem provides a holistic view of the business environment, enhancing decision-making processes. Plan the integration meticulously to maintain data accuracy and consistency, ensuring seamless interoperability between different systems and data formats.
Collaboration with key business partners is essential during this phase. Work closely with suppliers, distributors, and technology providers to ensure efficient data exchange that benefits all parties. Such collaborative relationships can enhance supply chain efficiencies and drive joint analytics efforts.
Returning to the first aspect of this phase, it is essential that you continuously monitor the performance of your ERP cloud analytics implementation against established KPIs, even after the initial integration process has concluded. This ongoing evaluation will help identify areas for improvement and success, fostering a culture of continuous improvement within the organization.
Phase 4: Enterprise Analytics & AI Capabilities
In the fourth phase, the focus shifts to integrating advanced analytics and AI capabilities within your ERP system. Begin by establishing effective data program management to align all data-related activities with strategic objectives. Governance practices, data standards, and robust data quality and security measures will form the backbone of your analytics functions.
It is also recommended that you create an Enterprise Analytics Council to bring together key stakeholders from various departments. This council will drive the analytics agenda, resolve data conflicts, and foster a culture of data-driven decision-making across the organization. Involvement of diverse perspectives ensures comprehensive solutions that cater to the varied needs of the business.
Developing and publishing an enterprise data catalog is also crucial in this phase. This catalog will serve as a centralized reference for available data sets, their sources, usage policies, and relevant metadata, making organizational data more discoverable and usable. Design extensible models that can easily adapt or expand as business needs evolve and new data sources are integrated. These models will provide scalability and flexibility in analytics, allowing for quick responses to new opportunities or challenges.
With the data fundamentals in place, you can begin to explore AI and machine learning techniques to elevate your data analysis capabilities. AI and ML can automate complex tasks, uncover hidden patterns, and enhance decision-making processes, thereby driving operational efficiencies and fostering innovation. Just remember—clean, well-governed data is fundamental to AI success.
Accelerating ERP Analytics in Snowflake with Hakkōda
Leveraging ERP analytics effectively can transform how businesses operate, making data-driven decisions a core part of their strategy. At Hakkoda, we understand the intricacies involved in integrating ERP systems with other vital data sources using a centralized data platform like the Snowflake AI Data Cloud.
In addition to guiding our clients from the early planning stages of their SAP modernization efforts all the way to unlocking advanced forecasting and AI toolsets in the cloud, we are also forever on the lookout for new, better ways of shortening time to value on customers’ Snowflake investments. To that end, our SAP migration processes are a powerful new way to expedite the ERP integration process, ensuring a seamless integration that automates time-consuming manual processes and helps you unlock 360-degree enterprise analytics faster than ever before.
By following our structured four-phase approach, organizations can address every critical aspect of ERP analytics implementation—from initial planning and governance to the adoption of AI and machine learning. This comprehensive strategy not only mitigates risks but also ensures scalability, flexibility, and continuous improvement. Together with a trusted data partner and equipped with the latest and greatest accelerator IP, the time has come for the anxieties and frustrations of a locked-in SAP investment to be put to bed at last.
Ready to turn your SAP investment into the analytics engine that will launch your business forward? Talk to one of our ERP experts today.
