Magnitude was founded on a base of strong ERP knowledge (Noetix), acquired more (Datalytics Technologies), and has recently been accelerating investment in the SAP ecosystem (SourceConnect product) and the purchase of Innowera and Every Angle. With that in mind, I finally got around to reading the Gartner report 2018 Strategic Roadmap for Postmodern ERP by Paul Saunders, Denise Ganly, and Mike Guay. This report states that organizations tend to focus on monolithic, vendor-first ERP strategies that do not support digital business initiatives and recommends a postmodern ERP strategy that includes the integration of differentiated and innovative capabilities that are beyond the core strengths of the common ERP platforms.
Coming from the Kalido heritage side of the Magnitude house, I’ve lived this first hand. We grew up in a Fortune Global 10 business in the late 90s that was heavily invested in both SAP (for larger operating units) and JD Edwards (for smaller operating units). These ERP projects tended to be expensive and slow to adapt to change. Consequently, the dream of a single ERP was never realized, and in the meantime, data had to be brought together across multiple ERPs and new applications that were coming onto the scene like Salesforce.com and Concur that thrived on the back of expensive on-premises CRM and ERP projects.
To accommodate these real-world requirements for our customers, we had to develop solutions and strategies for the points that Gartner raises in this report. Specifically:
- Master Data ManagementTo address the issue of “federated, loosely coupled ERP environments” and the surrounding solutions that grew up around them, we developed an every-domain MDM solution that was agnostic of any one system. This allowed us to build authoritative sets of master data that initially seeded the ERP deployments as well as containing the mappings between different coding schemes across systems. It also addressed the specific differences between operational systems. For example, SAP may hold information about current customers you are billing, but Salesforce might hold information about prospects you are hoping to become customers in the future. The models underlying each system are different because they perform different operational functions.
- Model-Driven AutomationTo address the issue of a “diverse and rapidly evolving vendor and product landscape”, we developed our solutions to be completely model-driven. Whether you wanted to deploy a master data management solution or a data warehouse automation solution, the method of deployment was the same, a high-level business model that, upon deployment, becomes metadata that defines and automatically creates the solution. More importantly, as new products are brought in to the customer environment and existing products are upgraded, the deployed systems can quickly adapt to those changes by just tweaking the business model and redeploying those changes. Software automation does the rest.
- FederationMany of our early customers deployed a network of data warehouses that pushed a high level model and master data down from corporate to regional and country implementations. In turn, those models could be extended for local requirements, but the presence of the global model and metadata allowed data to be aggregated from country to region to head office in a seamless way. The global “golden copy” master data was essentially the glue that held everything together. This mapping will continue to be important moving forward as Gartner points out in this report that:“90% of legacy applications will still be in use in 10 years’ time, and integrating to them becomes more and more vital. Instead of approaching integration as connecting System A to System B, or Department A to Department B, consider integration holistically as how you integrate the past, the present and the future.”
The ability to package together a model and master data together like this also comes in handy for other situations. For instance, our partner Teradata has a GDPR accelerator program that packages a data warehouse automation model and data coupled with other solutions that gives them the confidence to offer a fixed price consulting engagement around it.
- Artificial Intelligence / Machine LearningGartner correctly points out embedded AI is beginning to be something that companies can start to exploit, even on the ERP side. At Magnitude, that is something we see as well. For example, our SourceConnect for SAP Central Finance solution uses machine learning to improve matching and reduce the reliance on human data stewards to match records across all connected systems (including SAP sources). Based on this initial success, you will be begin to see this functionality cascade down to other products in our stable.
This Gartner report should be a wake-up call for CIOs that haven’t yet considered their Postmodern ERP strategy. Digital business is impacting all existing systems and is bringing rapid change. When it does, Magnitude can help because these are the same challenges we’ve been helping our customers face since the beginning of our MDM and DIW product lines.