Tag Archives: “Manufacturing
Top 5 IIoT Implementations in Manufacturing
The widespread implementation of the Internet of Things in industry, along with concurrent advances in machine learning and cloud storage, is thought to represent a fourth Industrial Revolution.
Manufacturers who can integrate digital, analog, physical, and human components into their production systems will generate unparalleled efficiency and value, while manufacturers who lag behind on implementation will struggle to compete.
Here’s what you should understand about the industrial Internet of Things and how it’s already being leveraged to create smarter, safer, and more productive plants.
What is the Industrial IoT?
The industrial Internet of Things, often abbreviated as industrial IoT or simply IIoT, refers to the network of machinery, instruments, and other physical devices that have been embedded with digital sensors for the purpose of monitoring, collecting, and sharing data over private internet connections.
The industrial IoT effectively takes the same wireless technology that drives the consumer Internet of Things (think fitness trackers, home security systems, and smart thermostats) and applies it towards industrial purposes, including core manufacturing operations.
Some aspects of the industrial IoT may not seem particularly new or novel. Manufacturers have, after all, collected and analyzed machinery data for decades.
What’s changed, though, is the emergence of small, low-cost sensors along with expansive, high-bandwidth wireless networks. By combining connected sensors with machine learning software that can analyze the data they’re collecting in real-time, it becomes possible to quickly and autonomously address inefficiencies while optimizing and synchronizing any number of processes.
Top 5 Industrial IoT Implementations in Manufacturing
Industrial IoT technology is already transforming manufacturing operations across the globe through several common implementations. Let’s look at some examples.
1. Asset Monitoring
It’s 3 a.m. Do you know if your next big shipment from Shanghai is on time? If your equipment in Canton has been serviced recently? If power outages across Central Europe will impact your operations in Hungary?
IoT-enabled sensors are helping manufacturers, especially remote manufacturers, track production processes in real-time—across locations—and keep key personnel updated on status changes. This means production problems at remote sites can be solved from a centralized location based on the exact same data that site operators are seeing.
Industrial IoT provides not only increased connectivity with specific devices and facilities, but more comprehensive intelligence about entire production systems. This data can be combined with other sources of information, including weather conditions and historical enterprise figures, to help augment logistics, sustain inventory, and avoid quality control problems.
For example, if you have shipments coming from multiple factories in China that are running late, and you know this in advance, you can draw up new shipping plans to save you money.
2. Predictive Maintenance
Across the globe, countless millions of dollars are spent each year on machine operational and maintenance costs.
Factories have historically either adopted a reactive (meaning run-to-failure) or preventive (meaning periodic examinations) model for keeping their equipment up-and-running. No matter the approach, the objective is always the same: avoid downtimes and expensive pauses on production.
Today, though, IoT sensors are driving a transition to a predictive maintenance model. That’s because the data these sensors are continuously collecting can be fed into machine learning models, which will compare new numbers with older data to actually predict when failure is likely to occur. What’s more, combining IoT with cloud computing lets you leverage information from multiple machines, making your predictions even more reliable.
This predictive approach translates to fewer instances of mechanical error, increased machine lifetimes, and huge cost savings. In fact, a recent McKinsey study notes that “predictive maintenance typically reduces machine downtime by 30-50% and increases machine life by 20-40%”.
3. Optimizing Legacy Machines
The high-tech benefits described above might seem unattainable for older manufacturing plants. After all, legacy equipment represents the backboard of manufacturing in the United States, as most facilities continue to depend on decades-old production equipment. Replacing these older machines can cost anywhere from hundreds of thousands to millions of dollars.
Thankfully, industrial IoT upgrades are not prohibitively expensive.
Smaller IoT-enabled sensors that detect factors like vibration or temperature can be attached to legacy machinery to provide connected feedback and data at a fraction of the cost of replacement. And even simple sensors like these can provide great benefit by identifying normal operating parameters and then sending out warnings when data indicates the machine is beginning to malfunction.
This is a key consideration for older pieces of equipment, which typically have higher maintenance costs and greater risk of failure. Upgrading existing machines with sensors can reduce such costs while saving time and labor.
4. Operational Intelligence
Operational intelligence is something of an umbrella term that reflects asset monitoring, predictive maintenance, and other industrial IoT benefits.
But it’s more than that, too.
Operational intelligence can be thought of as a real-time analysis of operational visibility—i.e., the monitoring of your system’s operations, performance, and readiness. Industrial IoT facilitates end-to-end operational visibility, including data from remote assets and systems. By collecting and analyzing operational visibility data and comparing it with historical information, organizations can generate actionable insights.
What’s more, the sort of data-driven, prescriptive advice generated by OI not only informs decision-making, it also reduces the time necessary to operationalize those decisions by automating key actions (especially time-sensitive ones).
The benefits to this approach are clear. Imagine, for instance, how operational intelligence could help you not only detect potential machine failures at overseas facilities before they occur, but also automatically order replacement parts and take other steps necessary to reduce disruptions via prescriptive analytics.
Operational intelligence for manufacturing is the most common industrial IoT application according to PTC, and it’s easy to understand why.
5. Safer Workplaces
Maintaining a safe work environment is critical for numerous reasons, not least of all protecting workers and avoiding production interruptions. Industrial IoT can help improve safety by providing facility managers with real-time understanding of worker activity, safety shutdown causes, machinery compliance, and other relevant trends.
The potential safety applications are quite numerous. For example, wearable smart devices can track workers’ biometrics (including body temperatures) and alert supervisors when there are health concerns. And the increased visibility provided by sensors can provide insights into safety-system performance and even help identify the root causes of shutdowns. Safety-system diagnostics can also be used to identify leading indicators and address machine issues before they lead to machine accidents.
In short, connected systems present greater opportunities to monitor performance, assess risk, and proactively improve safety.
Why it matters
Manufacturing has been transformed over the past decade by the convergence of several related technological advances. When working together, these complementary technologies can help you create automated plants that produce large volumes at maximum cost efficiency, or even smart plants that produce highly customized products.
But coordination is the key, as harnessing the most value from Industrial IoT-enabled sensors, cameras, and other devices requires sophisticated machine learning software to analyze the data.
As a leading data science platform, RapidMiner provides a blueprint to make your operation successful. We help manufacturers across the globe deliver business impact with machine learning and AI.
If you’d like to see how we can help your business, sign up for a free, no-obligation AI Assessment, and see what kind of impact machine learning can have on your organization.
5 Principles for Sustainable Innovation with Cloud Manufacturing
Reading Time: 3 minutes
Though the rise of Industry 4.0 in the last few years has encouraged manufacturers to digitally transform, the latest global events have made it more of a priority than ever before. It’s become clear that manufacturers need to change the way they implement operations, use data, engage with customers, and create an overall more sustainable and resilient ecosystem. And all this can be done with a cloud-based strategy.
The truth is that many manufactures are not adequately prepared for disruptive events. Disruptions are caused by a number of different reasons:
- Advancements in technology can cause strong disruptions in the way of doing business.
- Disruptive innovative competitors can affect your business; therefore, having the right insights can avoid investing in the wrong ideas or products.
- Customers’ tastes and behaviors continuously influence the company’s strategies forcing them to adapt production to be able to quickly react.
- Economic volatility leading to changes in customer behaviors. Think of the automotive industry during this global pandemic; if you’re locked at home you don’t need access to a car.
The good news is that digital transformation is still top of mind for most manufacturers in many areas. Trends that have been found include:
- 40% of manufactures will use IoT sensor data to diagnose issues and reduce downtime, which requires predictive maintenance1
- 50% of new IT infrastructure will be deployed outside of data centers1
- 35% growth in digital twins to create a virtual factory2
- 20% of G2000 manufactures will employ IoT, ML, and AI to automate decision making3
The pandemic pushed us towards the future of manufacturing by almost five years. Before many companies had already started or had plans to start a digital transformation. Suddenly, a new unforeseen critical factor was added: staying in business.
Since the pace of digital transformation won’t slow down, the question is if today’s manufacturing industry is agile and innovative enough. And more importantly, is it resilient enough to survive the next disruptive event and outpace the competition?
The future of manufacturing leverages the concepts of cloud manufacturing to create a sustainable ecosystem to navigate through the next major event by successfully implementing these five core principles or 5Cs:
- Connected
- Collaborative
- Cloud-centric
- Customer focused
- Continuous improvement
In order to achieve the 5Cs, you need to implement a cloud-based strategy that utilizes the following:
- Integration to support SaaS providers and an API-first strategy.
- Low-code approach to speed up the time to market, create newer services, and innovate faster.
- Power back to the people to empower all levels of users and create more synergy with processes and technology.
- Hybrid architectures to decide what data to migrate and when.
- Scaling and deployments to support out-of-the-box scaling to increase service availability and speed up the release cycle of new services.
- Processing at the edge to allow more edge IoT, 5G, and serverless computing patterns.
Cloud also enables modern event-driven responsive architecture. With a responsive architecture, you can process critical factory events and support your operations with immediate actions. You gain the necessary agility for the so-called “new normal”.
Here are a few of our customers who have implemented cloud manufacturing:
- Campari is one of the largest spirits beverage producers in the world. Since 1995, Campari has made 27 acquisitions so it needed to integrate with all different kinds of systems. The beverage producer had the pressure to minimize the time to market. Only by moving to the cloud was Campari able to gain the necessary business agility to sell the newly acquired products as fast as possible on the market and to sustain future acquisitions.
- Cosentino is a family-owned business founded 40 years ago in Spain and active in mining hills for granite and selling unfinished slabs to stonemasons. It completely transformed its business when it went digital to become a leader in high-end kitchen and baths finishing. But with the expansion, Cosentino had to face challenges to scale operations and keep running many different business processes. By integrating their global IT systems in the cloud and adopting a cloud-native architecture, a customer is now able to see in real-time if a product is available in two to three days compared to three to six months.
The future of manufacturing leverages the concepts of cloud manufacturing to create a sustainable ecosystem to navigate through the next major event. Click To Tweet
Manufacturing isn’t going away any time soon. But, if manufacturers want to remain competitive in this new environment, they have to look towards digital transformation, specifically with cloud. This will give manufacturers the necessary sustainability, agility, and resiliency to be prepared for the next disruptive event.
Learn more about how TIBCO enables manufacturers of the future and how these capabilities can help your business.
Henry Ford, Industry 4.0, And A Recovery For Manufacturing
There is a quote attributed to Henry Ford that I think holds the key to the future success of manufacturing. It may even change our thinking during the current crisis and provide the basis for successful recovery, digital transformation, and the adoption of Industry 4.0. And perhaps it can unlock significant value from an organization’s legacy investments.
Now, these are bold and potentially career-ending statements. So, before I tell you the quote I am referring to, I need to provide the context and the rationale behind such a claim.
To understand where we are today, we first need to look back to see where we came from.
Historic trends in manufacturing before Industry 4.0
Over the past 30 to 40 years, global manufacturers have followed four major trends in parallel that have been aimed at improving their manufacturing performance:
1. Strategy
In its simplest form, manufacturing strategy is essentially what to make, how to make it, and where to make it. Strategy is influenced by a huge range of internal and external factors. Pre-2020, the typical examples I used to illustrate strategic influences were sustainability, the circular economy, Brexit, changing consumer behavior, disruptive business models, trade wars, emerging markets, workforce skills, labor, energy, and material costs.
Strategic factors drive mergers, acquisitions and divestments, new market entry, new product development, and capital investment in manufacturing facilities.
The objective is to gain a competitive advantage from manufacturing operations in whatever form that takes for the organization in question, such as increased market share, cost reduction, product quality, shorter time to market, and product innovation.
A look at any global manufacturer’s history will provide an example of this trend. Clearly, the current crisis will have the biggest impact on manufacturing strategy we have ever witnessed.
2. Operational excellence
The second major trend has been the introduction of operational excellence programs. Most major manufacturers have their own internally branded methodology, but the core principles can be traced back to the fundamentals of Taylor, Ford, Shingo, Toyota Production System, LEAN, Six Sigma, and Theory of Constraints.
Examples of these tools and techniques can be seen in action during a walk around most production facilities.
3. Information technology
The third major trend aimed at improving manufacturing performance has been the investments made in information technology. Here, I am referring to the solutions that typically fall into the domain of the CIO and the IT department: ERP, CRM, and SCM applications, IT infrastructure, networks, and platform standards, to name just a few. These enterprise-level IT systems have a huge impact on manufacturing performance because they are the solutions that run the supply chain outside of the “make” activities. They capture demand, plan production, procure raw material, manage work in progress (WIP), store finished product, and transport it.
4. Operational technology
The fourth major trend has been the investments made in operational technology. Operational technologies are the solutions that perform the “make” activities inside the four walls of the factory, and this is normally the domain of the engineering department. OT includes instrumentation, measurement and control, automation, PLCs, HMI, SCADA, DCS, historians, APC, batch control, MES, LIMS, and OEM equipment. These investments are centered around capacity increases, quality improvements, process optimization, labor savings, and waste reduction.
The results: falling short of expectations
Most organizations can see clear improvements in manufacturing performance that are directly attributable to each of the four investment areas. Manufacturing has made huge strides during this time period and is clearly far more efficient and effective than it was.
However, the overwhelming feedback is that none of the four investment areas have fully delivered on their potential. The manufacturers didn’t quite achieve the level of manufacturing performance improvement they expected, and their current KPIs show that there is room for improvement.
Why is this the case? In a word: silos. Not just internal departmental silos in the manufacturer’s own organization but silos in the external ecosystem of suppliers.
Internal silos
Let’s begin by looking at the internal dynamics inside a typical manufacturer. The strategic manufacturing goals and objectives are cascaded down from CXO level to plant directors and manufacturing teams. The operational excellence program provides the principles, tools, and methodologies for manufacturing to utilize in the pursuit of performance improvement. And the business looks internally to IT and engineering functions for solutions that will provide both the information and processes needed to support manufacturing’s objectives.
As mentioned previously, IT provides many of the core Level 4 solutions in the classic ISA95 model. On a typical manufacturing site, it is IT solutions that provide the production planning, warehousing, logistics, and financial reporting systems. The choice of technology, vendor, and implementation partner and the budget normally rest with IT.
Meanwhile, OT is the domain of engineering: process, chemical, mechanical, electrical, and automation engineers, to name just a few. These are the people who design and build new production facilities, whether it is a car production line, soft drinks, chemicals, or pharmaceuticals. The choice of technology vendor, implementation partner, and budget normally rest with engineering.
In my 30 years of experience, IT and engineering have not collaborated particularly well. In many cases, they appear to be in competition, as they champion different solutions to solve the same business problem. At times, there also appears to be a lack of understanding of their respective domains. This is understandable, as the roles within each domain have their own full-time education and career paths. The example I often use to illustrate this point is their respective interpretations of the term “‘real-time.” Real-time in the world of IT is a transaction. Something has moved from A to B and has a different value (e.g., WIP). In the world of OT, real-time is usually millisecond scans on a process to ensure it is in control.
The net result is that these internal frictions and challenges often leave manufacturing operations without the solutions they need to hit their goals, and the overall results tend to plateau below expectations.
External silos
Let’s look at the dynamics of the external ecosystem of suppliers.
The dominant players advising on strategy in the C-Suite are the “pure” consulting firms, such as McKinsey, BCG, Bain, AT Kearney, and Bearing Point. In addition, there are the “Big Four” advisory arms and the consulting arms of the large system integration companies.
In the traditional IT ecosystem, you will find the major enterprise software application vendors, their integration partners, and a wide range of hardware and platform providers. But in the OT ecosystem, we find a very different set of hardware and software vendors because the implementation partners differ and OT is also where we find the OEMs. Yet, the operational excellence ecosystem is largely populated by consultancies that provide professional services that specialize in teaching and implementing operational excellence techniques and programs.
In many respects, the external ecosystem of suppliers is a mirror image of the silos found inside manufacturing.
My experience leads me to believe that there are very few manufacturers that have truly broken down both the internal and external silos and fully optimized their investments in these four areas. The point to emphasize here, however, is that what we are still discussing is Industry 3.0. In recent years, the picture has become more complicated by the advent of a fifth global trend, Industry 4.0.
The emergence of Industry 4.0
The past decade has seen the emergence of a range of disruptive technologies such as AR/VR, AI/ML, IoT, 3D printing, and several others. When grouped together and applied in a manufacturing context, we have the basis of Industry 4.0.
The Industry 4.0 market, however, is emerging and immature. The Industry 4.0 “white space” is being entered by most of the established strategic consultancies as well as the traditional IT and OT ecosystem players. This area has seen the emergence of the hyperscalers together with a large number of startups. Acquisitions, mergers, and failures are a regular occurrence, and this will continue to be the case until the market consolidates.
This is an exciting area to be involved in, and I genuinely believe that the potential value Industry 4.0 offers manufacturers is enormous. My prediction, however, is that on our current path, investments in Industry 4.0 will also fall short of expectations. They will be investments that again under-deliver against both their potential and promise.
Why? Silos still persist.
The traditional pre-Industry 4.0 internal and external silos are still largely intact. The players are still grouped into their traditional domains and following their established business models. We now have the added complication of a fifth silo in Industry 4.0, which is certainly blurring the lines but also making the challenge more difficult for manufacturers.
An audit of a typical manufacturing facility will illustrate the large number of players who currently have an influence on manufacturing performance. However, solving this problem is challenging but not impossible.
The solution
Most articles currently being published recognize that a major rethink of global manufacturing supply chains is required in what is being termed “the new normal.”
It is my contention however that radical change and a new way of working should not just apply to manufacturers. It should go much further and apply to the entire ecosystem of external suppliers. We must break down the competency silos and the competitive “arms-length” way of working.
Success will be delivered through collaboration and coopetition.
The facts are that each external supplier has significant value to add to bring to the equation. Clearly there are some areas of overlap but, once the competitive process is completed, there is no reason not to cooperate, as that is in everyone’s best interests.
And while this crisis has been a monumental shock to us all, it has highlighted the need for huge change in manufacturing. It seems illogical to expect manufacturing to successfully execute a paradigm shift while the external ecosystem of suppliers remains unchanged.
So what is the quote from Henry Ford that encapsulates the message I am trying to convey to both the manufacturers and the supplier ecosystem alike?
“If you always do what you’ve always done, you’ll always get what you always got.”
In this time of uncertainty, we are opening access to technologies that can help employees, companies, communities, and governments continue to move forward.
The Intelligent Industrial Manufacturing Enterprise: Five Ways Forward
Gone are the days when the industrial manufacturing value proposition was relatively simple: industrial manufacturers made products and delivered them.
Now, the industrial manufacturer’s job does not end with delivery. Driven by ever-more-demanding customers and supported by the widespread uptake of the Internet of Things (IoT) and the emerging power of machine learning and artificial intelligence, industrial manufacturers are developing new capabilities to track huge volumes of data generated by thousands of devices and are adjusting their service depending on the circumstances.
The goal is to be more responsive, always-on, and highly adaptable. Industrial manufacturers seek to collaborate more fully with their customers from discovery through design, service, and beyond. Wherever possible, they aim to deliver the kind of experiences and outcomes that customers reward with loyalty and ongoing business.
But how do companies move forward? Successful ones are focusing on the following five strategic priorities:
Be customer-centric
Industrial manufacturers are looking for ways to maintain customer-for-life relationships based on a 360-degree understanding of their customers. The starting point is a holistic view of their customers’ business processes – ending with the knowledge of how those customers use the products in their daily operations.
To get there, industrial manufacturers are moving toward omnichannel models for managing customers’ interactions across channels (Web, direct sales, IoT, and more). The goal is seamless interactions with customers, the ability to quickly see all products bought, and real-time visibility into how products are performing. This will help companies position the customer’s point of view at the center of every decision.
Serve the segment of one
Increasingly, industrial manufacturers will be able to deliver completely customized products, services, and solutions that precisely fit the needs of individual customers based on sophisticated platform, configuration, and mass-customization strategies.
Industrial manufacturers are moving toward this goal by rationalizing existing product options using machine learning to understand what really sells and what doesn’t. In addition, organizations are pulling in customer experience data to better understand requirements – and then using this data to inform requirements in product configurators that let customers define their own products on the fly.
Embrace digital smart products and solutions
Industrial manufacturers are shifting to products with more digital functionality, allowing even more flexible configuration of products. Thus, software-based features are on the rise with connectivity to enable remote access and monitoring.
Industrial manufacturers are extending original (physical) products with digital services that augment and extend product functionality. Combining insights into the end-user experience and the relevance and value of digital capabilities, manufacturers will extend the lifecycle of the product and increase lifetime revenue. With a direct feedback loop from the product back to the manufacturer, product enhancements and future developments will be based on the actual usage and experience of the product, from first interaction to product retirement.
Implement the digital supply chain and smart factory
Supply chains and manufacturing networks are becoming modular and flexible to allow the seamless execution of different manufacturing strategies. Industrial manufacturers, accordingly, are using Industry 4.0 philosophies and new digital technologies to implement “shop-floor-to-top-floor” connectivity for real-time visibility.
Subsequent steps will increase machine-to-machine connectivity and collaboration, allowing autonomous decisions based on sensor data and machine learning algorithms. Industrial manufacturers will combine feedback from connected stakeholders (customers, workers, suppliers) and associated processes to further improve overall manufacturing and supply chain performance. Intelligently connecting manufacturing, logistics, and supply chains enables companies to quickly address short-term demand impulses, supply fluctuations, and changes to customer orders, allowing a truly modular production process. This production flexibility enables industrial manufacturers to produce higher-quality individualized goods at lower costs.
Develop service-based business models
As revenues are increasingly linked to services that are based on and built around smart products, more industrial manufacturers will offer products as a service based on the value delivered to the end customer.
Remote condition monitoring of assets is critical to success with such models – enabling manufacturers to identify and provide additional value-added services. Based on the data collected, organizations can get better insight into how products are used. This enables them to offer pay-for-outcome models where the risk and long-term value of each customer is clearly understood.
The future is bright
Ultimately, the winners in the industrial manufacturing industry will be those companies that successfully transform themselves into fully customer-centric companies. Ahead for the industry is unprecedented change at unprecedented speed – but our industry is positioned to be a driver of progress. Together, we can lead the way.
Join our virtual event to learn more
Want to find out more about the latest trends and innovations in today’s global industrial manufacturing business? Register today to join our flagship 60-minute virtual industry event:
SAP Industries Forum 2020: Industrial Manufacturing
Experience the Intelligent Enterprise
Thursday, March 26, 2020, 8 a.m. PDT, 11 a.m. EDT, 4 p.m. CET
Register Now
Predictive Analytics in Manufacturing: A Winning Edge
The modern manufacturing world is a delicate dance, filled with interconnected pieces that all need to work perfectly in order to produce the goods that keep the world running. In Moving Parts, we explore the unique data and analytics challenges manufacturing companies face every day.
Building an accurate predictive analytics model isn’t easy. It requires a skilled data team, advanced tools, and enormous amounts of clean data from the right combination of inputs. It’s a difficult process, but an effective predictive analytics engine is an enormous asset for any organization.
Big challenges, big rewards
Manufacturing companies are in a unique position regarding data: they create and capture tons of it every day. The process of producing goods is an enormous opportunity for data optimization. Raw materials need to be ordered, received, constructed, packaged, and shipped out for sale in the most efficient manner possible. Because the steps are repeated so many times through the process, a small edge created via predictive analytics in manufacturing will be magnified at every repetition to produce significant benefit.
Because of the cyclical nature of the manufacturing process, data-driven companies are building superior processes to create bigger and bigger advantages. Here are a few examples of companies using manufacturing analytics to win the future:
Predicting return rate
Skullcandy’s dive into predictive analytics started with the challenge of understanding return rates on new products. The logic was that if the team could predict certain features or aspects of a product that would lead to a return, they could optimize those policies around returning products. They used BigSquid to blend and analyze historical data related to returns and added their learnings to features and products on their roadmap. From there, the team could ask new questions of that dataset to understand the way customers were interacting with their products and ultimately build a better warranty policy for products before they were even released. This data was also useful for product managers, giving them a clear picture of what was making customers adopt Skullcandy’s products (or not).
Once the return rate questions were answered, the team focused their efforts on uncovering insights around reviews and warranty claims to generate insights about positive and negative drivers. Data like this is ideal for making decisions for product roadmaps. All those customer insights can be used in a number of creative ways to better focus resources and improve products.
Improve forecasts and maximize revenue
Gentex made the most of their budget to optimize their incoming revenue. Just six months after implementing predictive analytics, their ecommerce sales increased by 50%!
Gentex deployed Sisense to comb through millions of records after switching over from an outdated ERP system. They needed a platform that could churn through all that data quickly and deliver quick intelligence about both current and future revenues. Initially, Gentex created dashboards for their sales and operations teams that collected information about sales, quotes, and orders across the company. Those dashboards answered immediate questions about the current state of the business.
To answer more forward-looking questions, Gentex creates a sales forecast for an entire year using just a few months of data. They use predictive models to forecast revenues based on spending. They even incorporate trend data to improve accuracy over time. Currently, Gentex builds visualizations of year-to-date revenue data to forecast up to 15 months into the future.
Operating off those accurate forecasts, Gentex made the most of their budget to optimize their incoming revenue. Just six months after implementing predictive analytics, their ecommerce sales increased by 50%!
Improve inventory management with demand forecasting
Making a product that consumers want to buy is only useful if a company can find a way to get that product in front of the consumers who demand it. Several of today’s most cutting-edge manufacturers are blending historical customer data and external factors to predict demand for goods so they can increase production when demand will be high and decrease production when demand will be low. These companies aren’t just building for the future, they’re building the future.
The need to accurately forecast demand is crucial to these manufacturers. Assessing demand in real-time is ineffective since companies need to make decisions about demand far enough in advance to complete an entire production cycle and get that product in front of customers. With a solid predictive analytics model in place, manufacturers can create exactly the right amount of products (and the right variety of those products) to satisfy future customers.
These forecasts optimize sales revenue, but it also avoids unnecessary costs associated with producing, shipping, and stocking items that won’t sell. Accurate predictions are a win-win for any manufacturer.
Build your manufacturing business with analytics
Predictive analytics in manufacturing have gone from being science fiction to being a make-or-break addition to any company’s technology stack. Using a platform like Sisense for manufacturing analytics, combining internal and external information into a series of accurate forecasts is incredibly invaluable to any manufacturer. Improving any step of the manufacturing process is an advantage over the competition, but improving every step is a data-driven way to become an industry leader faster.
Adam Bonefeste is a veteran content marketing manager. When he isn’t writing copy, he’s probably reading books, running through San Francisco or getting lost in YouTube holes about math/logic problems.
3 Manufacturing Inefficiency Problems Solved with Microsoft Dynamics 365
There are IT inefficiency risks that are consistent among the manufacturing industry. Businesses that leverage CRM software see their sales increase by , sales productivity increase by 34%, and sales forecast accuracy increase by 42%. Let’s identify the problems, and then talk about a simple approach to significant process improvement using Microsoft Dynamics 365 CRM.
, more than some other industries, greatly benefits from a full-service CRM solution such as Microsoft Dynamics 365 Customer Engagement. This shouldn’t be surprising, yet it is a requirement that some manufacturers have ignored.
From not having a 360-degree view of customers to poor demand forecasting, and limited visibility into your sales pipeline and inefficient sales processes, these challenges can be met with a robust, integrated CRM solution.
Which of These Inefficiency Problems Does Your Manufacturing Business Face?
Problem 1: Excessive Internal Communications About Order and Invoice Information
Obtaining order and invoice information can be a nightmare for some sales teams in manufacturing. Sales reps will call or email someone in their department to obtain order and invoice information. In most cases, the required information is in an ERP or accounting system to which the sales team doesn’t have access. Phone calls are made, and emails are sent back and forth to get the information to the sales team, which would relay to the sales rep.
Problem 2: Double Entry of Sales Order Information
Your sales reps are responsible for getting orders and closing deals. Once an order is received, it’s not uncommon to see the sales rep hand off the order information to someone else within the sales department. This could be done by email, Word template, or hand-written paper document delivered to the back-office staff for manual input. When such information is manually being passed across people and departments, there is great risk of sales order information being lost, entered multiple times, entered erroneously, or siloed into systems or outdated spreadsheets.
Problem 3: Sales People Need to See Their Open Order Status
For your sales rep, any open order represents pending revenue. If an order remains open, the sales rep (and the customer) needs to know why. Sales representatives want to be able to see open order information in real time, either to manage customer expectations or to assist in resolving an order that hasn’t been fully processed or shipped. Since sales reps generally earn their commission on invoiced and delivered products, income from these open orders will not show up in their paychecks.
Solving Inefficiency Problems Through System Integration
One of the simplest ways to resolve these common inefficiency problems is through System Integration, the process of connecting your business systems so they can work together seamlessly. For sales people who don’t have access to your company’s , System Integration offers a host of benefits:
- System Integration pushes data from the ERP to the CRM system and vice versa.
- Sales people can initiate orders from the Dynamics 365 CRM system; they can populate products (which are also integrated with the ERP’s product catalog) as well as any other information needed about the order.
- When the order is ready, it is pushed to the ERP system where it is processed.
- As the order travels through its normal process, the order status managed in the ERP is passed back to the CRM system in real time for much needed visibility for the sales team.
The Advantages of Microsoft Dynamics 365
It is reported that for companies that use a CRM system, the average return on their technology investment is for each dollar spent. Given how critical a CRM system is for manufacturers, offers a bevy of benefits to sales teams. The out-of-the-box solution comes with a robust quote-to-order system so that sales reps can convert a quote to an order with a simple click. Another key advantage is that order and invoice data tables and fields already reside in the system and are ready to be received from the ERP via the integration.
Microsoft Dynamics 365 CRM when fully integrated with your ERP provides improved ability to sort and filter through order and invoice information. Sales people can manage a “My Open Orders” list where orders fall off automatically as they are invoiced. Invoice information is also available for sales people for real-time visibility and for summing invoices on a daily, weekly, monthly, and annual basis.
Achieve Efficiency Gains
In today’s customer-centric era, the importance of an integrated CRM solution has never been greater. A quality CRM solution not only allows manufacturers to facilitate basic sales tasks, but it also helps them overcome the many challenges they face. Microsoft Dynamics 365 Customer Engagement is a full service CRM solution that can add value to your distribution business by creating a leaner organization that will manage customer demand and meet it quickly and efficiently. If you’re looking to achieve efficiency gains, invest in Microsoft Dynamics 365 today!
Learn more about how to leverage and help improve the business processes of your .
As Senior CRM Consultant of Synoptek, Julie brings a solid business background in addition to 9 years of hands-on experience in D365 CRM. It’s with this broad understanding of business processes that aids in serving companies well and knowing how and why the D365 CRM provides positive change. As a Microsoft Dynamics Certified and ClickDimensions Certified professional, Julie provides leadership that helps the deployment team stay focused on quality and project priorities.
Add Muscle And Flexibility To Your Manufacturing Operations With 3D Printing
Part 3 of a 3-part “Manufacturing Fitness” series
Concluding our series on manufacturing fitness, we now turn our attention to 3D printing – the process of physically manufacturing a product directly from a CAD model. Simply upload the CAD file to a 3D printer, feed it with some sort of base material, and the printer builds the object layer by layer.
This layering approach is what gives the technique its other name: additive manufacturing. The base material that gets added or layered can be almost anything imaginable. Typically, it’s plastic dust – but it can also be metal or concrete. In some futuristic scenarios, it can even be human tissue. So, if you’re looking to add muscle to your manufacturing operations – lean, flexible muscle, that is – then additive manufacturing or 3D printing may be the answer.
While 3D printing is certainly on the rise, perhaps the most significant factor holding back wider adoption is its slow speed of production. This issue, however, may soon be solved. According to UPS, one of the most prominent players in the 3D printing space, the average speed of production for 3D printing is expected to increase by 88% by 2023. Already, 3D printing represents a multibillion-dollar market that is projected to hit $ 21 billion by 2020.
Use cases today
Most manufacturers want to know what 3D printing is good for today. In terms of products that can be produced, the list is quite long: eyewear, dental molds, prosthetics, jewelry, smartphone cases, musical instruments, architectural models, car parts, medical devices – the list goes on.
But why would 3D printing replace traditional manufacturing approaches for any of these products? It all depends on the manufacturing context. Here are some ways in which 3D printing is being used today:
- Prototyping: 3D printing is quite flexible for single-use scenarios. Organizations with design and engineering skills can quickly draw up CAD models for new product ideas and generate physical versions of products with a 3D printer. Traditional manufacturing approaches – such as machining, casting, and forging – can be cost-prohibitive for quick prototypes. 3D printing helps drive a more iterative approach to innovation – one that makes it easier and more cost-effective to get physical products into the hands of stakeholders, decision-makers, and focus groups who can then determine whether or not to move forward with further development.
- Replacement parts: Keeping all possible spare parts in inventory is costly, and depending on third-party providers to deliver a needed part can mean long wait times. But if you have a 3D printer and the needed CAD drawings available – or if you can find them quickly – you can use 3D printing to produce the part on-site. For organizations running large vehicle fleets, warehouses, or manufacturing facilities, 3D printing offers a way forward that can help minimize downtime due to equipment failure or maintenance.
- Profitable individualization (configurable products): 3D printing represents an intriguing solution for highly configurable products where keeping all possible combinations of parts in stock can be a logistics headache. At a time when organizations seek ways to profitably address the expectations of customers for individualized products that fit their unique needs, companies can use 3D printing to meet demand by simply printing out the parts that customers require.
- Sustainability: 3D printing localizes production – which cuts down on shipping costs and the carbon footprint associated with it. When products are produced using plastic dust or powder, the products are also 100% recyclable – so whatever is produced can be returned to the dust from which it is formed, making the base material available once again for use in new products. For organizations serious about their sustainability efforts, 3D printing can help put the circular economy into action.
Networks for 3D printing
As the 3D printing market matures, the cost of printers is coming down. Today, lower-end hobbyist machines for in-home use weigh in at just around $ 300 while professional-grade machines can cost more than $ 10,000.
But does it make sense to own your own printer? Increasingly, the idea of 3D printing as a service is taking hold – with 3D printing farms emerging to serve the needs of the market. UPS, in fact, offers 3D printing services from its many retail outlets across the U.S. Organizations or individuals can simply send CAD drawings to UPS, place an order, and pick up the final product when it’s ready – or have it delivered by UPS as needed.
But how do you get the CAD drawings if you don’t have the ability to generate them in-house? Here is where the idea of a manufacturing network for 3D printing comes into play. Manufacturing networks that connect organizations to suppliers and manufacturing service providers have been around for some time. Increasingly, these networks are offering pre-made CAD drawings for, say, spare parts – or services for custom drawing as needed.
Let’s say you’re a refrigerator manufacturer. In a 3D printing world, instead of keeping all of the parts for every model you produce in stock, you can provide the schematics for each part to manufacturing networks where suppliers can offer the service of 3D printing the part on demand. Or you can maintain your own printer farm and serve your customers yourself.
The point is that as 3D printing takes off, manufacturing networks will play an increasingly important role in facilitating the market – enabling more organizations to take advantage of the benefits that this new mode of manufacturing has to offer. So when it comes to maintaining your manufacturing fitness in a highly competitive environment, think of 3D printing as a way to add some of the muscle and flexibility you need to succeed.
For more information, download the latest IDC report on digital manufacturing.
How CPQ Can Drive Manufacturing Sales
In manufacturing, margins are everything. In fact, if you’re like most manufacturers, your business operates on such tight margins that even a small change in the price list can have an enormous impact on your bottom line.
So what happens if your sales team inadvertently uses an old price list and the cost of steel actually has gone up a quarter since that price list was made? A million-dollar project quickly could go from profitable business to a big loss.
Unfortunately, this situation happens too frequently in manufacturing — but it is preventable.
Disconnect Between ERP and Sales
Most manufacturing companies encounter several common challenges that limit sales potential and create situations like the ones described above. Critically, all of those challenges stem from a disconnect between the sales team and the enterprise resource planning system.
Every manufacturing organization has an ERP system, and this tool typically gets significant attention because it’s required to operate the business effectively. However, this tends to create challenges for sales, because ERP systems are not sales tools.
It’s typically slow and difficult to make changes in ERP systems, and they’re definitely not optimized for sales processes like lead and pipeline management. As a result, sales people end up using spreadsheets or a handful of systems cobbled together to build quotes and manage deals, and neither approach is reliable or trackable.
When this happens, sales processes operate completely outside the ERP, even though important information like costs, margins, valid configurations and price lists live inside the ERP. Ultimately, this disconnect leads to challenges like these:
- Sales people selling and pricing products that don’t reflect the products you actually can deliver or the prices you want in the market;
- Lost money due to sales people using inaccurate price lists to develop quotes;
- Double entries for sales quotes, which create a higher likelihood of mistakes;
- No way to audit approvals in the sales process or, in some cases, no way to control the approval process; and
- Individual sales people using their own methods for delivering quotes, which can create inconsistencies and lead to quotes with outdated business and legal terms (in addition to inaccurate pricing).
How CPQ Can Resolve the ERP Disconnect
The best way for manufacturing organizations to resolve the sales-ERP disconnect is to introduce a program that can formalize the process for configuring, pricing and quoting products. Essentially, the CPQ should act as a bridge between your ERP system and your sales processes.
With a CPQ integrated into your ERP, your product master list can continue to live in the ERP, but you also can make all of the relevant data (available products, pricing, etc.) accessible to your sales team through the CPQ. Notably, the CPQ will reflect any changes to that data in real time. With the right integration, this setup accomplishes the following:
- Ensures sales people always have the most up-to-date product and pricing information to eliminate the issue of generating quotes based on inaccurate data;
- Introduces a standard and automated approval process, complete with different levels of approval and thresholds for discounts, to create a documented and auditable process without adding significant time or aggravation for sales people;
- Creates a standard quote template with opportunities for dynamic terms and conditions to ensure sales people always have accurate business and legal information and deliver a professional-looking, on-brand document; and
- Automates document input once a customer signs the quote to save time and eliminate the risk of human error or miscommunications.
Beyond these initial uses, many manufacturing organizations also use CPQ to manage cost plus markup pricing. Since most sales systems only do pricing, integrating a CPQ program that can handle the appropriate markup goes one step further to ensure that sales people always give accurate pricing in quotes.
On top of that, you can make it so that your CPQ properly reflects the bill of materials for each quote. That way, when the signed quote gets pushed back to your ERP, your team immediately has a clear list of what to build for the customer.
A leading manufacturer of steel roof and wall products and structural roof and floor decks recently launched a CPQ program to resolve the disconnect between its ERP and its sales tool. The team used two best practice solutions for ERP and sales, but still found a disconnect between the two that led to sales people using inaccurate data, making it difficult to audit customer quotes.
To resolve that challenge, the company introduced a CPQ program to act as a bridge between the two solutions and bring ERP data– like product lists, price lists and valid configurations — directly into the CRM.
By introducing CPQ, the company increased control and auditability over the quote process, and ensured sales people always would have the most accurate data, since what they see in the CRM through the CPQ program is the exact data that lives in its ERP system.
Now, the company can remain confident that everything sales people send to customers — from quotes all the way through to production — is correct.
Introducing CPQ can help drive sales in manufacturing by resolving the disconnect between sales processes and ERP data — but that’s only the beginning. It also can act as a bridge between other systems to help calculate appropriate tax and shipping costs, confirm inventory availability, improve the online payment process, and more.
Waiakea Overcame Major Manufacturing, Supply Chain and System Issues to Thrive as a Premium, Sustainable Water Brand
%20(1).jpg "Waiakea Overcame Major Manufacturing, Supply Chain and System Issues to Thrive as a Premium, Sustainable Water Brand")
Waiakea Overcame Major Manufacturing, Supply Chain and System Issues to Thrive as a Premium, Sustainable Water Brand
Posted by Kendall Fisher, Executive Producer and Host of The NetSuite Podcast
Waiakea is a premium water company founded in 2012 with the sole mission of protecting our earth through sustainable packaging, sustainable sourcing and sustainable logistics.
Under the leadership of CEO and co-founder, Ryan Emmons, the Waiakea team has remained dedicated to this mission, which sets the brand apart in the premium water industry. However, its focus on making the world a better place was getting slowed down by Waiakea’s business processes, which became outdated and cumbersome.
Both Emmons and Plant Manager, Jerry Clark, explain the company started off writing everything down on paper and taking hand-written logs. At the end of the month, the team would then reconcile production reports, resulting in time wasted as well as inconsistent numbers.
“It wasn’t that people didn’t want to buy the water,” Clark explains. “We actually had to slow ourselves down because we just weren’t reliable in our process. Every time something went wrong, we had to scramble to try and figure out what was going on.”
Emmons says Waiakea saw about 50% downtime in a day, bleeding money and barely staying afloat. And that’s precisely when he realized Waiakea needed to update its business processes and management system in order to survive.
Watch the video to find out why Waiakea ultimately chose Oracle NetSuite to manage its entire business—from manufacturing to the supply chain, demand planning to sourcing and accounting.
And to learn more about Waiakea’s growth story, click here.
by NetSuite filed under
Design To Operate: Manufacturing For Empowered Customers
Part 3 in a 5-part series on Design-to-Operate with the Digital Supply Chain
In this blog series, we’re looking at the design-to-operate (D2O) product lifecycle, which spans the phases of design, plan, manufacture, deliver, and operate. The first installments focused on design (by Thomas Ohnemus) and planning (by David Vallejo). My focus here will be on manufacturing.
Breaking down silos
Today’s customers are connected, informed, and always on. They demand high-quality, individualized products and faster delivery. When it comes to the manufacturing function, manual processes and isolated information silos make meeting these demands increasingly difficult, putting your organization at a competitive disadvantage.
A lack of data transparency, for example, impedes consistent performance measurements across plants and contract manufacturers. It makes scheduling production runs a tedious chore. It clouds insight into quality metrics while also impeding manufacturing agility – a key requirement for delivering what customers want in an individualized, dynamic, and highly variable market. How do you quickly accommodate new product introductions when you can’t even get the engineering bill of materials (BOM) to align with the manufacturing BOM?
Today’s manufacturers are also challenged by highly variable demand from customers who expect individualized products and experiences. This means that organizations are increasingly moving to product platforms that enable greater configurability while still keeping costs down, quality up, and lifecycles short. The move is one from mass production to mass customization – where the ability to deliver the lot size of one is what helps you deliver to customer expectations and demand.
What’s needed are connected manufacturing processes that are integrated across the entire D2O product lifecycle to break down silos and enable visibility across the phases of design, planning, logistics, and operations. This can enable next-generation business processes that leverage intelligent technologies to analyze root causes of inefficiency, predict machine and process failures, and speed execution.
Integrated D2O for manufacturing
An integrated D2O environment for manufacturing can help you compress cycle times, speed time to market, minimize costs, and meet manufacturing demand with greater efficiency and agility – despite growing variability. To get an idea of how such value can be realized, let’s take a quick look at each phase:
- Design: When engineers share data with production teams, they can better understand issues of manufacturability from the get-go – making production processes far less likely to break down mid-process. An integrated D2O process, moreover, helps align engineering and manufacturing BOMs so that you execute the handoff from one phase to another in a more seamless fashion. Ultimately, this speeds product delivery to the end customer regardless of configuration complexity.
- Plan: To serve customers demanding more individualized products, planning and manufacturing teams need to collaborate more closely. With connected manufacturing processes, both teams can share information to more effectively respond to variable product demand. Planning, for instance, may need to shore up smaller lots of inventory and stage raw materials in more defined increments to meet production requirements. Simulation tools can help planning teams prepare more effectively for these more individualized production runs. Meanwhile, manufacturing needs to quickly plan and adapt production schedules to current plant conditions, capacity, and demand – while also communicating back to planning on any bottlenecks in production that create gaps between the plan and actuals on the shop floor.
- Deliver: Increasingly, organizations are under pressure to move produced goods directly out of production and into the delivery phase. To honor SLAs for same-day delivery, the handoff to logistics teams needs to take place virtually immediately. This requires increased levels of cohesion between the two groups such that the timing of production – which can be variable according to demand – is aligned with the scheduling of trucks and other delivery vehicles.
- Operate: The capital equipment used in production needs to be constantly monitored to avoid the breakdowns that lead to downtime. At the same time, products and assets that are produced for end customers can also be monitored to yield insightful usage data for improving product quality or managing after-sale maintenance businesses. Whatever the use case, manufacturing and operations teams can work together to share information with an eye toward increasing efficiency, maximizing uptime, improving products, and revealing important insights on what users want.
The low-hanging fruit
So how do manufacturing teams move forward with integrated D2O processes? One piece of practical advice is to avoid boiling the ocean. Quick wins that demonstrate the value of D2O integration can generate the kind of buy-in needed to take on projects at a larger scale.
Internet of Things (IoT) technology serves as a good example. By outfitting production equipment with IoT sensors, manufacturing teams can generate high volumes of high-value data. This data can be used to help planning teams pinpoint production issues early, coordinate with logistics to ensure on-time delivery, and optimize the maintenance of production equipment.
When it comes to manufacturing, sophisticated digital supply chain capabilities and greater connectedness can help organizations increase shop-floor visibility, identify process bottlenecks, and manage operations with greater agility. This, in turn, facilitates smart factory capabilities where rigid production lines are transformed into flexible manufacturing cells – making it possible to shift from mass production to mass customization.
These are just two quick examples of how to move forward with integrated D2O processes. The ultimate objective, of course, is the smart connected factory that uses data visibility, advanced automation, and the integration of shop-floor processes to optimize performance and deliver what empowered customers expect.
Learn more
If you need more information on the D2O product lifecycle, have a look at the new whitepaper from IDC. Also, be sure to catch the next blog in this series, which will focus on delivery and logistics in the context of the D2O lifecycle.