As data’s importance in business grows, so do the pressures it exerts on modern organizations. In the wake of these demands—or Drivers, as outlined in SAPinsider’s DART (Drivers, Action, Requirements, Technologies) model—enterprises strive to turn data into value. As an IT leader or professional, leadership has likely tasked you to help the business overcome its data and analytics challenges so it can unlock the transformational power of growing data volumes.
However, the challenges of legacy SAP and non-SAP datasets have not gone away. The data management, security, governance, and analytics risks of migrating SAP S/4HANA environments to hybrid or cloud remain. When business Drivers related to greater data management, accessibility, and analytics intensify, how do you move forward with confidence?
In Part One of this blog series, we discussed the importance of tapping into your data estate’s hidden value, the DART model’s significance in understanding SAP data management strategy trends, and how business Drivers influence enterprise decision-making. Today, In Part Two, I’d like to highlight the importance of Actions: the specific strategies enterprises take to address existing business pressures.
By understanding the enterprise Drivers impacting most global enterprises—and the Actions these organizations prioritize to support them— you can build greater confidence around your SAP data management strategy. By leveraging the robust research methodology of SAPinsider and the deep experience and expertise of Pythian, you can harness key strategic insights to help unlock the transformational power of your data.
Business Actions within the DART model
Actions aren’t merely tasks or steps in a comprehensive data management approach: they are the collective efforts of processes, people, and technology to deliver business-centric solutions. Let’s touch on an example of Actions in the real world, as they can help you better understand what Actions you may have already taken on your data transformation journey.
In Part One, I highlighted the concept of business Drivers with Morse Hydraulics—a Pythian client who felt numerous business pressures, from the increased need for real-time data to the availability of company analytics and trends.
In this example, I’d like to highlight another Pythian client—a large global retailer—who faced the challenges of a rapidly shifting retail landscape. After the explosive growth of its ecommerce channel, the retailer found that its legacy ECC deployment was too inefficient. To keep up with incredible customer demand—over 20,000 orders a day—real-time insights into warehouse workloads and shipping data were essential to business deliverables, yet:
- The team manually tracked every data point on thousands of orders
- Analysts and decision-makers spent hours pulling immediately outdated reports
- The team viewed critical data in a legacy spreadsheet presentation layer
The amount of data collection continued to increase, and the reporting that took two hours to pull (and was immediately outdated) meant internal decision-makers did not have the most recent available information to inform their business strategies. As a result, the organization sought a partner with the experience and expertise to recommend a solution to enable real-time insights with greater agility.
Upon closer inspection, these business pressures are shared by Morse Hydraulics, and link to a number of the SAPinsider Driver survey results: teams are seeking real-time data for better decision making (46%), greater access and visibility to business-wide trends and analytics (32%), and want to better manage larger data volumes as they grow (21%).
Pythian worked with the retailer to develop an ETL process that sends their data to a warehouse in Google Cloud, then into Google’s BigQuery. The data is set up daily, near real-time feeds, creating easy-to-read shipping and warehousing Tableau dashboards where key business insights are delivered every fifteen minutes. As an Action, this translates to the ‘migrating to cloud databases and data warehouse,’ which thirty percent of enterprise respondents noted as a focus.
It is important to note that despite sharing similar business Drivers, the global retailer and Morse Hydraulics—at least for these specific elements of their data management strategy—did not share the same Actions. This serves as an intuitive example of how the DART model is not a prescriptive methodology but is instead a research framework that draws parallels between enterprise data management approaches.
In our experience, there simply aren’t one-size-fits-all data management strategies that will work optimally for every organization. Businesses within the same marketplace may share the same (or similar) Drivers and business pressures. Still, they may leverage completed actions depending on various factors—which are then supported by specific Requirements and Technologies.
The data: SAPinsider insights into SAP data management strategy
Enterprise data strategies depend solely upon the organization’s unique set of factors. For example, a greenfield migration to S/4HANA may prove immediately advantageous to one company while challenging and tedious for another.
Although every enterprise is on its own unique SAP data management journey, understanding the strategies global organizations prioritize can help improve internal alignment within your business. Below, we’ve expanded upon SAPinsider’s survey results to provide some compelling insights on how enterprises are taking steps to extract value from their unstructured, transactional, and trend data.
Architecting an enterprise-wide data strategy that includes both on-premise and cloud systems (50%)
In our line of business, few are arguing against cloud adoption. The benefits are vast, from simplifying workloads through automation to providing expansive business insights.
We cannot be blind to the very real risks, however. Uncertainty around legacy data stores, data governance, privacy, cloud costs, and access control are significant considerations for most businesses investigating a transition to hyperscale clouds like Google Cloud, Amazon Web Services (AWS), and Microsoft’s Azure.
This is why many organizations are moving on from the cloud-first vs. cloud-only debate in its entirety. Instead, they’re embracing ‘cloud also,’ acknowledging that as long as there is a holistic data strategy, it doesn’t matter if their data is on-prem, in the cloud, or a hybrid of both.
Deploying modern data integration, data orchestration, and data migration tools (37%)
We’ve noted that more organizations are considering hybrid environments for their SAP and non-SAP data. Although challenges abound for those with disparate silos (often a result of structured and unstructured legacy SAP data), data integration and orchestration solutions are becoming increasingly popular in practice. Only 11% of survey respondents are not considering a data orchestration solution and will not be pursuing one—the rest are already using one or plan to.
I do not foresee this Action trend changing as enterprises steadily adopt the cloud for an increasing number of use cases. In direct relation to the next point, if organizations can better extract and unite their disparate data, they will better serve stakeholders’ internal analytic data appetites—another reason enterprises are adopting data orchestration tools.
Creating a data archiving strategy to provide better analytical performance and reduce costs (32%)
This Action is tied directly to sky-rocketing data volumes as businesses collect more and more business intelligence, customer insights, and data related to accounting, productivity, and more. As a result, adequate data archiving protocols can alleviate the burden of higher cloud costs and database complexity without deleting potentially useful data entirely.
Migrating to cloud databases and data warehouses (30%)
Organizations are managing more databases as they look to support their numerous SAP and non-SAP applications. According to the SAPinsider report, the average number of respondent data warehouses is 26, indicating rising complexity. Organizations are expected to house structured and unstructured data and use data orchestration techniques to extract valuable analytics.
Implementing a centralized master data repository on SAP HANA (29%)
To remain competitive, enterprises are increasingly trying to have a unified view of all of their data across databases, data lakes, and data warehouses. Many organizations transitioning to SAP HANA are getting ahead of potential future headaches by streamlining their data infrastructure by consolidating these data repositories. However, resource-intensive and time-consuming, linking existing repositories and/or creating a master data repository can improve data quality and governance.
Takeaways: how Actions can influence your enterprise data management approach
Leveraging the DART methodology, SAPinsider’s report has established some critical takeaways for organizations seeking clarity around data management strategy. To integrate all of the learnings around business Actions, organizations should consider the following takeaways:
- Assess current and future automation and analytics needs while bridging the gap between IT and business stakeholders. Organizations are different, but many experience information and communications gaps between business users and IT teams. By including business users in the identification, assessment, and development of business cases, you can build lasting consensus and facilitate an environment of collaboration. Having these users early in the process can better prioritize the data, analytics, and automation use cases that will drive greater business value.
- Don’t wait to upskill internal IT team with data migration and cloud management resources. Organizations are all taking different paths toward the cloud. Many are adopting hybrid models and leveraging SAP Data Orchestration Engine or third-party tools. Others are going cloud-native and leaning fully into SAP HANA. Regardless of your position, migrating data to SAP HANA to on-prem, hyperscale cloud, or hybrid environments are skills your team must become acquainted with. Develop the core skills the team and business need to succeed while partnering with organizations that can support your unique stack.
- Enable data orchestration to leverage seamless data use across the enterprise. As data flows and touches multiple applications and data stores, tracking it through business processes has become a daunting challenge. Data orchestration solutions provide new concepts such as DataOps (to mirror DevOps) and ensure data behaves as it should. As new applications get rolled out, such a process and technology can smooth the path to deployment.
If you found this blog insightful, please comment below—I would love to hear from you. In the next blog, I will highlight the importance of data management Requirements and how they inform enterprise data strategies.
If you want to read the entire research report published by SAPinsider, you can download it now.