5 practical scenarios for jumpstarting the future of your business with smart machines
Many manufacturing, construction, and high-end professional services companies are anticipating changes in their business models and industries. Technology continues to present opportunities for transforming organizations to become more competitive or customer-focused. While many companies are still looking for ways to benefit from the internet of things (IoT) or 3D-printing, other technology trends like machine learning or artificial intelligence (AI) move into the spotlight and get people excited.
When you want to produce better outcomes now, what’s the best thing to do?
It often takes large investments and carefully planned strategies to realize the advantages of something like machine learning or AI. The returns in terms of organizational agility and productivity can be tremendous, but they may take much time and dogged teamwork to come to fruition. Business leaders we talk to often wonder what they can do today to generate benefits from technology innovation that has a shorter payback period but still aligns with their more transformative goals.
Digital transformation or Industry 4.0 are not always what makes most sense for your business right now. Not all improvements and changes in your business need to come with substantial complications and costs. Maybe implementing advanced, predictive analytics or designing a smart digital factory is not even what helps you achieve the best results if you commit all the effort and resources they demand. As Cornelis Bosch points out in his post, it really depends on how you create and deliver value to customers.
Here’s a more affordable, efficient approach: You may be able to use some of the technology you already own in a more organic, less revolutionary manner to make a real value difference.
Taking automated notifications a few steps further
Many manufacturing and other production companies today use some version of automatic notifications. For example, when certain evens happen in the ERP system, or when IoT values from a production line indicate poor throughput and potentially missed KPIs, a messaging system ensures that the right people are aware of these conditions and can correct them.
A possible next step, somewhere between today’s practices and full-fledged AI, would add a layer of enablement to make these automated notifications more meaningful. The smart machines you end up with would then take many of the steps that today rely on human intervention. Corrective actions could take place immediately, without second-guessing and without waiting for a person to travel, review documentation, consult peers, or whatever else it takes to get the job done. Over time, incorporating the experience from various events, the situational analyses performed by your machines would become more accurate and their actions therefore more effective.
Most of the technical building blocks to accomplish this are already present in many companies. The critical elements are relatively common assets like process controllers, IoT sensors, ERP systems, analytical tools, workflow designers, and other technologies. What would be new would be the integrations that connect them and the systems’ ability to assess data, choose the best of several options, and act on their own.
Where smart machines can make a difference
There are many possible scenarios where autonomous, smart machines could help your business. Here are five that come up a lot in conversations:
- #1: Condition-based action. When a machine runs at too high a temperature, develops an odd vibration, or manifests some other behavior that could indicate malfunctioning or a breakdown, an automated response would adjust operations or initiate whatever self-repair the machine can perform. When performance flags or there is a departure from your particular OEE balance or other KPI, the smart machine recalibrates operations and finds ways to avoid similar, future incidents. Depending on the level of connected automation, production planning and expected throughput could also be modified. Humans would not become involved until machine-performed diagnostics show the need for action beyond what the machine can do.
- #2: Materials planning and procurement. Production and warehouse data combined with financials, sales data, demand forecasting, and supply-chain insight on suppliers, availabilities, and costs could enable your systems to initiate timely purchasing of items and raw materials that go into your products. As your machines become smarter, the timing of actions and the acuteness of decisions could steadily improve. Shipments and deliveries would happen on time, and all routine communications would be between digital systems. You could expand from here into contract, project, and resource management.
- #3: Maintaining safe and efficient production environments. When your production involves perishable items, toxic substances, the presence of allergens, or challenging environmental conditions, smart machines in cooling, heating, ventilation, and facilities systems could keep your workers safe, your goods at optimal quality, and your consumers away from harm. Your enhanced facilities management technologies could find ways to reduce the consumption of water, gas, and electricity, and interact with utility systems to purchase these resources at best available terms.
- #4: Enhanced product management. You can take advantage of smart machines to simplify the process of getting new designs from the product lifecycle management (PLM) system used by engineers into production and distribution. Today’s standard PLM and ERP integrations already create change orders and update financials. More intelligent systems could reach beyond that into your inventory and procurement processes to make efficient use of existing stock and source parts and materials at optimal terms, replenishing automatically from the best available selections in terms of cost and availability. They could also help you avoid conflicts and bottlenecks in production scheduling and resource assignments. What’s more, you could enable your machine systems to find ways to source the most effective and economical packaging, containers, and shipping services whenever the weight, size, or composition of your products requires an adjustment.
- #5: Fleet management. As automation comes to specialized vehicles used in mining operations and is slowly making its way to the trucks running on highways and freeways along with all the other traffic there, you can enhance them with automated capabilities to keep them safe and efficient. With experience, an added layer of intelligence in vehicles and centralized management systems can, for instance, make route planning more effective, reduce fuel consumption, and improve the ability of your vehicles to roll safely through the huge variety of potentially dangerous situations in road traffic.
What’s left to do for people will be more interesting
What all these scenarios have in common is that you would free people from stressful, yet often dull tasks and the many possible errors and liabilities in reviewing large masses of data from a variety of sources. Smart machines can be much faster and more reliable at this kind of work. Digital technologies and machine systems don’t get tired or bored, and they don’t have emotional biases.
Humans would come in where machines reach their limits. Sooner or later, they may find an opportunity or a need for correction that goes beyond their structured, predictable resources, that involves unforeseen elements and changes in the business model or process flows that require a more strategic view. Machine learning or AI might even handle those types of situations, but remember, we’re looking for the more affordable, simple steps you can take now. Evolving automatic notifications to make your machines smarter might well be feasible and affordable, and yield a much faster payoff than more radical and disruptive activities.
Where do you see the most interesting use cases for smarter machines, and how are you planning for them? Send me a note at firstname.lastname@example.org.