As the manufacturing world continues to evolve to meet new challenges, there’s a step-change in innovation for the products and services that are delivered and supported. Many industry insiders are expressing the need for a focus on driving sustainable (and profitable) business growth. Deloitte suggests digital investment and supply chain resilience as the key pillars. Partnerships are also increasingly important to achieving sustainable business growth, whether that’s upstream or downstream within your supply chain or enabling partners such as application and technology providers.

In all of those partnering scenarios, it’s important to have a common understanding of your desired outcomes, so you can ensure you’re all speaking the same language, which helps shorten the time to value. Manufacturing is shifting towards industry-specific applications and these applications are now nearly always delivered in the cloud to maximize adoption, flexibility, availability, and security, as well as reducing through-life cost of ownership. In fact, Gartner forecasts end-user public cloud spending to grow by 18% through 2021.

Even when your warehouse operations seem to be running smoothly, there is always room for improvement and a need to stay up to date with innovation. While steps are taken to keep warehouse operations at peak performance, when fulfilment times and levels are jeopardized, it’s still up to you and your team to race to recover, to ensure actions to get back on track are taken correctly so that product can make its way out the door, and time is always working against you.

If your organization previously reviewed and dismissed the value of moving your warehouse management system (WMS) to the cloud, it’s time to reevaluate. Decisions that seemed to make sense last year or even last quarter, likely look very different with new challenges emerging over the past several months. By empowering critical systems like a WMS with cloud capabilities, your organization can scale quickly, maximize productivity, and minimize outages and downtime to prevent bringing the company’s mission-critical operations to its knees.

1. Are we organizationally ready for significant change?

Organizations are only as good as their people, and manufacturers must look carefully at whether they have the right people and culture to support a different way of doing things. It is the people who will be responsible for implementing change, and they should be ready, committed, and on board with any type of transformation plan.

An organization’s culture can make or break a digital transformation project and “organizational change management” is one of the key components of such a project. Organizations should aim for an inclusive culture where people feel like they are key contributors to the company’s future success.

To achieve this, management teams should encourage a culture of openness to help employees step forward with their ideas. All change, and all transformation, starts with an idea – so it’s important for people to feel empowered to put their ideas out in the open.

Know you want to transform but don't know where to start? Want to gain $9-12 for every dollar you spend? Read on to find out why starting with your people is the best first step to prioritizing digital transformation projects.

Digital transformation is at the top of the to-do lists of most companies, but one topic that is often missing from a discussion on digital transformation is which areas to prioritize. Most businesses can’t afford to completely overhaul a core function of the enterprise top to bottom, along with the technology that supports it, at any one time. Instead, they’ll target specific areas for transformation. That approach minimizes disruption to the business, keeps costs manageable, and helps the business apply lessons learned to future transformation projects. The question, though, is which areas to target first?

Traditionally, almost all business intelligence and analytics solutions were designed as general-purpose platforms or desktop tools suitable for any industry, department, or use case. That does mean, of course, that the burden of developing data models, data pipelines, dashboards, and reports falls to the customer. They effectively start with a 'blank sheet of paper,' which, in theory, can be developed to fit the organization's exact needs. However, the reality is that the organization may not have either the skills, resources, or time to develop an analytics solution that quickly meets business requirements.

The answer to avoiding this overhead of entirely homegrown analytics is to use a modern analytic application that can deliver ready-to-use analytics, right "out-of-the-box." Deployment and adoption of these analytic applications are accelerated because of built-in content developed by industry domain experts that understand the industries, roles, data, business applications, and specific analytics required by typical business user personas. A significant amount of development time can be saved because this domain-expertise-driven content can replace typical internal development processes.

Manufacturers eager to jumpstart growth opportunities are embracing digital strategies. New technologies offer exciting ways to leverage sensor data, engage with customers, and automate processes. New ways of looking at products, services and the complete value chain are transforming the way we think about manufacturing products and distributing them to the market. While the potential impact is promising, it can also be intimidating. Where do you start? How do you measure success? This checklist provides nine elements critical to a successful digital deployment, based on a timely report by R “Ray” Wang of Constellation Research.

By Nick Castellina, Infor industry & solution strategy director

Digital manufacturing. Industry 4.0. You’re probably familiar with these terms, and maybe you’ve even successfully piloted these concepts. But how do you roll out such an initiative more broadly, beyond a specific use case, to ensure you are deploying operational intelligence to your entire operation and across factories, and gaining the promised productivity increases?

Many companies start with a predictive maintenance pilot, according to Capgemini’s podcast: “Emerging Trends in Digital Manufacturing with Pascal Brosset.” Improving the reliability of critical assets has an obvious payback, uses proven analytics, and is overseen by a limited, self-contained team: maintenance. Further, more and more equipment manufacturers provide maintenance services or applications along with the asset itself, which further accelerates the maturity and popularity of this use case.