South Carolina’s manufacturing and distribution organizations face never-ending disruptions – whether it’s market pressures to better manage costs and streamline operations, or it’s preparing for the impact of technological innovations such as Artificial Intelligence (AI) and machine learning.
When project teams consider the capabilities of today’s modern ERP software, the motto is “be prepared.” Teams are wise to assess whether their organizations have the enterprise technology systems in place to manage the critical needs of today’s organization in areas of reporting, planning or overall efficiency – and the features and flexibilities to succeed in tomorrow’s competitive environment.
We see these challenges to “future proof” systems in the work we do guiding enterprise technology evaluation, selection, implementation and business improvement.
Here are a few key technological disruptions in terms of preparing your organization:
The Industrial Internet of Things
As I noted in a previous post, the Industrial Internet of Things is emerging as a force impacting today’s modern manufacturing ERP systems.
The IIoT bridges the shop floor and ERP software to allow an organization to create and share data in real time.
While devices like programmable logic controllers (PLCs) and sensors collect production data and other information, this data still needs an infrastructure that gives users the ability to house the information and provide meaningful insight in real time.
Project teams will need to track these changes as they leverage the capabilities of modern ERP.
Intelligent Decision Making via AI
When machines share data without human intervention, and that data is delivered more accurately and in real-time, improved intelligent decision making is the new reality.
Gartner lists AI as the number one technology trend for 2018, noting that it has the potential to enhance decision making, reinvent business models and remake the customer experience. Gartner predicts that by 2020, 30 percent of CIOs will have AI as a top five investment priority.
As ERP systems offer new levels of integration, this change will continue to impact manufacturing organizations going forward.
Taking a closer look at the impacts of AI in the state’s manufacturing region, think about how systems can “learn” repetitive tasks that users do. AI can facilitate automation of these tasks, performing warehouse labor optimization, dynamic product pricing, and self-service employee HR assistance. Smart systems show users what information they need, and when they need it within a personal context. Examples include personalized search, dynamic dashboard content, and data entry optimization.
Finally, we’re in a world where AI or machine learning can make intelligent correlations in key business data to predict what might happen next. Examples include cash flow prediction, customer lifetime value prediction, and employee performance prediction.
There are hundreds of potential use cases for AI in manufacturing today, making this area one of the most invested-in by the global venture capital community.
Cloud Deployment of Enterprise Systems
Typically, the companies we team with look to the Cloud model to achieve strategic business process improvements as related to cost, risk reduction and improved productivity.
No matter the size organization, and given the competitive pressures faced by today’s manufacturing and distribution sector, the most compelling business driver is clearly related to reducing cost and achieving ROI via the Cloud model.
Cost considerations commonly involve looking to reduce support costs for business applications, upgrades and database systems; middleware and other technologies.
Companies seek a cost benefit by reducing the need for disruptive backups and maintenance of servers, storage, firewall, and other hardware.
An Eye on the Future
It’s tempting when considering new enterprise technology solutions to merely identify features and functions that address current business processes.
A better approach is to prepare for process transformation by evaluating, selecting and implementing a solution that addresses a desired “future state.” This includes considering downstream and upstream communication and how processes can be integrated and improved overall, especially in the face of disruptive change.
Our take: prepare in advance for major disruptive impacts so your enterprise systems help the organization transition from current to the future state.
About the Author: Jeff Carr is Founder and CEO of Ultra Consultants, an independent research and enterprise selection consultants firm serving the manufacturing and distribution industries. He is a leading independent voice in enterprise system technology. Jeff’s organizations have helped over 1,200 manufacturing companies transform their business operations. Visit Ultra Consultants to learn more about Jeff Carr and his team. www.ultraconsultants.com