For enterprise software, big data and BI have made incredible advances lately, but we still may be a while away from systems that configure themselves at the enterprise level.
Imagine a world where even your home appliances are connected to the internet. Fridges that are wired predict your preferences based on past consumption, recommend similar products or brands that are similar to yours to try, or just even to “top up” your current grocery inventory. If you buy filtered milk, your fridge may say to pick up the same brand or try a substitute if that brand is not available.
This is the principle that is currently employed by smart retailers such as Amazon, Wal-Mart, Target, Indigo, Barnes and Noble, etc. Nearly every online site where something is purchased additional items are recommended at the bottom as suggestions. You may know these as “Customers who purchased this product also purchased this product” and several suggestions are made. The reality of cross-channel retailing that suggests additional or suitable products is an intricate set of business procedures, software capabilities, data aggregation, and web design. What’s notable is a competent BI system, database connections, several connected systems (warehouse, transportation management, procurement, web/ecommerce and demand and forecasting planning) are involved in this convenience.
This functionality ripples down from manufacturing from seeing what is on order always through the supply chain down to the retail level.
Predictive business intelligence is on its way of just passing into the next phase of maturity for BI software. Business Performance Management has evolved to predicting what your next move is based if you feed it the correct information. ”Smart systems” that “learn” from past performance can predict the future. This can be compared to artificial intelligence software where it learns from repetition and past performance.
Now imagine “Smart ERP systems.” These systems might predict proactive, pre-emptive actions based on conditions that you set. An example of this may be if an inventory level falls below a certain level the system automatically reorders which exists today as min/max levels if they are set. What if these systems start to predict business process flows with alerts modeled after an existing workflow? It sets up similar alerts, calculates probability of completion, calculates risk of the operation, compares the alert and sign-off hierarchy to existing workflows/processes, and even compares stock levels and calculates stock levels to complete, and time to complete the preset tasks. These are starting to become a slow reality in enterprise system software.
The technologies of SOA, integration, collaboration, and business performance metrics are working in unison with some agility throughout the ERP system.
“Predictive ERP,” the next wave of software evolution will definitely take its cue from the business intelligence and demand planning software that exists today. The term Predictive ERP refers to systems that ascertain, calculate,e and predict certain repetitive behaviours that mimic existing business processes and conditions. This can stem all the way from suggesting to apply a software patch all the way to desiging a workflow with alerts, event management, and sign-offs by supervisors. This level of intelligence should help organizations gain more ROI in their technology investment, utilize more functionality, gain operational efficiencies, and maximize profit margins by process and SKU.
As ERP and all enterprise business software evolves and changes, it’s an exciting time to see what the right software can unleash in your company. Will “Predictive ERP” systems be sold the same way they are now? How will support be handled? Will ROI be measured much differently from today’s technology investments? How long will this take to get there to this level? H ow will technology advance to support this new predictive architecture? How will implementation be differ from today? Will it be more difficult or easier than today’s systems? Will this transfer to cloud computing? How fast? These are all questions that organizations and vendors will need to answer and collaborate on getting there to make this a quicker reality. The use of the BI can even give directions to users by understanding workflows and may even be able to help in configuration.
Another example of this system is the smart refrigerator that is connected to the internet tells you that you should pick up the short items such as milk or eggs (which may be set on a min/max level) and places the order for you through your connected credit card and will wait for you to confirm the delivery time - directly to your door.
For enterprise software, big data and BI have made incredible advances lately, but we still may be a while away from systems that configure themselves at the enterprise level. Vendors have however come a far way in the design of their interfaces and business agility such as the BLINC architecture that allows customers to configure their systems themselves according to changing business requirements. We will see where the next level of next-generation ERP technology takes us and what it will be capable of doing.
It should be a fun ride.
Eval-Source is a consulting firm that provides all enterprise software selection and strategic technology consulting services for organizations to achieve success in their IT initiatives.
Visit www.eval-source.com to learn more.