Tomorrow’s ERP will enhance the ability of organizations to apply context to decision-making and adapt more easily to changing events.
Advances in data compression, storage and memory costs, and distributed computing should allow for real-time processing and analysis of internal and external data feeds. This will help an organization glean intelligent signals from torrents of data, and take action in response. The cost of not monitoring physical operations is beginning to eclipse the cost of introducing sensors and actuators throughout enterprise assets—from facilities and equipment, to supplies and finished goods. Location awareness, digital identities, and growing automation of business operations allow fine-grained knowledge of who’s doing what, where.
And social business’ growth across the enterprise shines a light on who knows what and who knows whom. The nexus of these forces provides context to inform each action taken, each query answered, and each analytical model.
Additionally, ERP’s supporting infrastructure shows signs of allowing for multi-tenant public cloud, cloud-based dedicated appliances (so-called “virtual private”), and on-premise appliances for solutions in their catalog. Options for in-memory versus disc-based solutions will also be available. Vendor consolidation will likely continue, but a handful of players may remain, touting competing platforms for owning the new world of broad enterprise enablement.
Perhaps the Most Significant Change: ERP is shifting from strict process automation based on scale and repetition, to the orchestration framework for an agile, adaptable response to often-changing events. Some areas of the business will likely rely on highly automated, autonomous, predictive, and prescriptive analytical models. Others may require human insight and intervention, where tools exist to help knowledge workers visualize and explore complex or sensitive data. This presents a much different scale problem—advanced intelligence will need to be deployed against data feeds and be accessible by employees. Today’s backbones would likely either crumble under the volume, or be financially untenable. Hence the need for a fundamentally different engine, one that is built for outside-in integration, anticipates unpredictable and intermittent growth, and can handle the exploding volumes of data and service interactions.