By leveraging data, manufacturers can better respond to customer needs, empower employees, and even invent new business models and revenue streams. By Stefan Krauss

Many of the biggest technology innovations of recent years have been a result of increasing consumer demand for mobility. Autonomous vehicles and delivery drones are examples of how mobile technology enhances our personal lives. We are starting to have similar, technology-inspired expectations in our professional lives and in the business environment. This type of environment, an intelligent enterprise, is only possible when an organization harnesses the power of data.

Manufacturing companies that strive to become intelligent enterprises can utilize a variety of technological advancements, such as automation, machine learning (ML), Big Data and the Internet of Things (IoT) to become more strategic and break down barriers in their organizations. This type of approach – one that places operational efficiency and data-driven decision-making at its core – also enables better communication, innovation, and collaboration between teams. As an example, at a recent customer conference, the car manufacturer Rinspeed shared how it is  utilizing transformational thinking and technological innovation to become a data-driven intelligent enterprise. This is just the beginning of how manufacturers can take advantage of opportunities in the digital economy.

Best-in-class enterprises have already begun to realize the benefits of prioritizing a data-driven approach to manufacturing. Yet, truly leveraging that data to empower employees through process automation, anticipating and proactively responding to customer needs, and Inventing new business models and revenue streams are the keys to becoming an intelligent enterprise.

What is an Intelligent Enterprise? 

An intelligent enterprise is one that prioritizes the integration of technology into the fabric of the organization to achieve its desired outcomes. This is often achieved by automating repetitive tasks, reducing waste, and elevating employees to focus on more strategic high-value assignments, thus enabling them to communicate better inside the organization and with customers.

A key component of an intelligent enterprise is seamless integration between people and data. Connected data can help manufacturers understand and predict behavior, which can be applied to employees, customers, or even machinery in the plant. Understanding these groups better is key to becoming an enterprise that plans and predicts its needs proactively rather than reacting to them.

Beyond KPIs and optimizing efficiency with predicative analytics, a push for an intelligent enterprise will drive change within the organization. The groups that utilize data to improve operational efficiency and increase the speed of innovation will take the lead. Manufacturing leaders and their teams will be rewarded for using data to be more competitive and, as a result, they will be better informed about their own products, teams, and customers.

“An intelligent enterprise is one that prioritizes the integration of technology into the fabric of the organization to achieve its desired outcomes.”

Disrupt Or Be Disrupted 

Future business challenges, by their nature, promise to be radically different than the challenges we face today. To address these challenges and to maintain their competitive position, manufacturers need to utilize increasingly large amounts of data, improve productivity, and accelerate innovation. Leaders at nearly 60 percent of the world’s Top 100 organizations believe that the digital economy will have a significant impact on their organizations over the next year. Technologies like artificial intelligence (AI), machine learning, IoT, Big Data, advanced analytics, and blockchain are vehicles for this change, and can help businesses adapt. Implementing these tools to help make data actionable creates a variety of positive outcomes for manufacturing enterprises. Here are a few examples of how companies are embracing change:

Reduce waste and become more strategic – Automation can now be implemented far more cost-effectively, providing greater efficiencies as well as enabling the manufacturing workforce to focus on high-value activities like customer success, strategic planning, and collaboration. As an example, Mitsubishi Electric offers customers automation solutions that support the need for increased manufacturing performance and digital transformation. Mitsubishi Electric leverages cloud technology in conjunction with the IoT to easily link shop floor and asset information with a cloud-based management system to enable advanced analytics. As a result, customers gain insight into connected automation systems – including up to date information about status and usage – as well as predictive analytics to trigger capacity alerts and maintenance requests. This enables better monitoring, more accurate forecasting, and higher asset availability for Mitsubishi Electric’s customers.

Analyze trends and predict inefficiencies – Data on its own is useless if it’s not made actionable for leaders to make informed, strategic business decisions. Advances in machine learning are enabling algorithms to become highly accurate with the capability to reference patterns in data to predict future outcomes. Manufacturing leaders can use these increasingly sophisticated capabilities to drive the next level of intelligent business-processes and automate or eliminate repetitive manual tasks. In doing so, employees will be afforded more time to work together on these solutions, rather than remaining isolated from each other. As an example, global fleet management company ARI uses IoT technology, telematics, and predictive analytics to let customers track and report on every detail of vehicle fleet operations. From driver activity, to fuel data, to repairs and more, companies can see where time and money are dedicated to subsequently adjust business strategy accordingly.

Innovate and create new business models – Once organizations have taken steps to become more strategic and leverage data to drive business decisions, there is a new opportunity to improve upon established business models and revenue streams. This is the area where an intelligent enterprise will truly begin to feel the benefits of its transformation journey, and separate itself from competitors. For example, Microsoft already owned tremendous data and cloud resources in Cortana and Azure, but it was a strategic business decision to unite these assets, and utilize the powerful AI and ML built into each, to analyze and predict new methods to drive deeper savings and new revenue streams.

Foster collaboration internally, and with customers – While an intelligent enterprise is the ideal destination for tomorrow’s manufacturing leaders, it’s also the vehicle that will enable better collaboration along the journey. Each component of this process allows for improved communication and builds conversation naturally within business teams – making collaboration a natural piece of the experience, rather than something that requires additional planning and effort. Further, a dedication to becoming an intelligent enterprise can directly lead to enhanced communication and co-creation with customers and partners. In the digital economy, companies cannot meet all challenges and leverage all opportunities on their own. For example, Rinspeed’s “Snap” project, a connected, automated ecosystem to redefine the mobility services of the future, is a unique demonstration of how partner organizations can establish new ways of cooperating and co-innovating to drive new ideas for the future on a global scale.

Future business challenges, by their nature, promise to be radically different than the challenges we face today.

Making an Impact with Intelligence 

Becoming an intelligent enterprise is no easy task. As most manufacturing executives can attest, building bridges to overcome organizational silos – and removing complexity from existing business processes – requires a deft balancing of responsibilities. Fortunately, tools like AI, ML, IoT, and analytics support the manufacturer’s transition to an intelligent enterprise and can dramatically increase the odds of success.

Manufacturing businesses must invest in three key areas: an intelligent suite, intelligent technologies, and a digital platform. Collectively, these individual pieces form a cohesive strategy that will help leaders achieve the goal of becoming an intelligent enterprise and a digital leader. Focusing on data-driven insights helps organizations make strategic business decisions, cut waste, and become more transparent in communication. Each incremental step in this process enables sharing and fosters better communication between teams, creating an atmosphere where internal and external collaboration is the norm.

The path to becoming an intelligent enterprise is critical for manufacturers to succeed and with the right technology and leadership in place, it is within reach. Today’s leaders in the manufacturing industry are leveraging technology to increase visibility, focus resources on business models of the future, and gain the agility to disrupt and outmaneuver competitors in the industry. By becoming an intelligent enterprise, manufacturing organizations can achieve these goals – and more.    M