Tag: manufacturing intelligence

The Magic Bullet for Real-Time Supply Chain Collaboration? Cloud Visibility.
Jessica Twentyman reported in the Financial Times, that for many manufacturers, supply chain collaboration is stuck in the dark ages. When it comes to ordering materials and components, managing inventory levels, or organizing the delivery of finished goods to customers, companies are forced continually to chase business partners – mostly suppliers, logistics companies, and retailers – via a messy stream of emails, phone calls, and even faxes. Worse still, much of the data that could give manufacturers a complete, end-to-end view of their supply chain already resides within the systems of these partners; as much as 80 percent of it, according to some industry estimates.

Supply Chain Market reported the closest any manufacturer can get to the magic bullet of efficiency (collaboration) is through greater supply chain visibility. Supply chain visibility means all partners get access to – and share data – in real-time. Visibility to all orders allows suppliers to proactively respond to demand signals. Poor visibility often results in parts shortages. Frustrated manufacturers report having no idea they were down to the last box of parts. The result is expensive; using faster shipping methods to get the part back on the shop floor. A real-time view of parts on hand allows a supply chain manager to take action before there is a stock out, eliminating expedited fees.

A single – visible – version of the truth

Modern Demand-Driven Manufacturers are leveraging real-time Cloud-based visualization and collaboration systems to view data from multiple, disparate sources while keeping the data in its original, host environment. The value of these visualization systems is in their inherent flexibility. Once the data connections are made, they can be accessed and used (with appropriate permissions) at any point along the end-to-end supply chain spectrum. There is no limit to the data sources that can be connected or how the data can be sliced and diced and made visual to accommodate the different layers and levels of the manufacturing enterprise.

The result is a single – visible – version of the truth that enables a more compliant, consistent, Lean, and waste free supply chain. Visualizations can be created or configured by and for the individual user, work center, plant or multi-plant/enterprise, supplier, or customer level. Order, replenishment status, inventory levels, machine maintenance, system alerts, KPIs, logistics tracking, and more can be made accessible to the appropriate parties anytime, anywhere, providing a single source for real-time information.

Data on Demand: Examples of value across supply chain layers
- Customers gain visibility into order receipt, status, and delivery data. In ETO environments, visibility tools can provide further collaboration capabilities on product specifications and requirements.
- Suppliers receive real-time demand signals with the ability to exchange purchase order and projected delivery information online. Supply Chain Managers can collectively visualize and track the performance of all suppliers against their service level agreements (SLAs).
- Individual users have easy access to information they can act on to analyze issues and improve performance. Customer Service representatives can follow the status of their customer’s order and confirm delivery details; Operators have a clear view of priorities and an understanding of what to work on next; Quality Analysts are immediately alerted to issues and can quickly trace the source of the problem.
- Work Centers can monitor all the machines in their area through a single screen to collectively determine overall equipment effectiveness (OEE) and gain insight for preventative or prescriptive maintenance.
- Individual Plants can visualize real-time end-to-end production flow and the status of safety, compliance, and key performance indicators (KPI) at any level in the facility.
- Regional Plant Networks can connect to Warehouse/Distribution Centers to better manage excess inventory and monitor status from Third Party Logistics (3PL) providers.
- Multi-National Enterprises can connect to global data sources – including Supplier networks and Contract Manufacturers – to assess individual plant performance and collectively view and track logistics flow throughout their enterprise.
Newer Cloud technologies are more intuitive with drag-and-drop functions and natural language queries. IT is no longer saddled with pulling data and generating reports. Through self-service tools, even non-techies can perform their own analyses and create their own dashboards and visualizations.

The technology is available and the impact of such can be far-reaching. The investment quite often produces an immediate or near-term return just in avoiding costs associated with downtime, waste and expediting.

Standardizing data formats – the key to universal, real-time accessibility.

With the multitude of data sources feeding the supply chain, the visibility value is in the ability to “mash up” or bring together data from these disparate sources to tell a complete story. The strategy for doing such is standardizing – or normalizing – data. And while this is not a new concept, today there is a more efficient and cost-effective approach. Through the Cloud, data is accessed from its host environment and aggregated, analyzed, and shared by standardizing the data and making it accessible in real-time through technology tool sets like SignalR. These lighter weight, highly flexible and scalable web-enabled technologies are rapidly replacing costly hardware devices traditionally used for data standardization.

Ultimately, visibility technologies should be measured by their ability to provide the right data to the right people at the right time. The true value proposition is in having the right information to take immediate action – the decision-driving data that will make a difference in how your supply chain is performing today.

More information on this topic:

White paper: End-to-End Supply Chain Visibility Technology is Here

Video case study: How Orbital ATK is Leveraging the IIoT and Visual Factory Technology to Drive Continuous Improvements

Video: SyncView Real-time Manufacturing Visualization System – 4 minute overview
June 19, 2017
Aligning Metrics to Strategy

Measuring your strategic goals against their value and the time, money and attention they need

When we began our metrics discussion, we talked about how behaviors are too often dictated by metrics—and whether or not these behaviors actually “move the needle” for sustainable supply chain improvements. Mark Davidson’s blog about aligning metrics to larger goals and objectives covers this topic well. I’d like to go over what I find especially valuable about these tactics. Mark writes: “Largely due to the misalignment of goals and objectives, a considerable number of organizations struggle to realize the full business value that manufacturing can generate.” (e.g., Don’t miss the boat.)

Let’s talk about the “real-world” first. We all know that in today’s organizations there are many, competing strategies and objectives. Look at any strategic plan, and there are many initiatives that cover the gambit of popular business systems, such as CRM, Big Data, Business Intelligence, Cloud Computing, ERP implementations, Supply Chain implementations, Human Resources employee engagement programs, Safety Programs, etc. There’s no shortage of cost savings and performance enhancing methods to transform organizations. Yet, without a good way to measure them, they will meet a great deal of resistance.

Who is driving this thing?

One of the biggest issues I see is that once strategic objectives are accepted, people start making assumptions. These assumptions have effects that start to come to light when the tasks and activities are disseminated and the people responsible for implementing the changes start working. These people are already busy, and now we add new tasks for them to accomplish, often overloading them. If there are multiple strategies to work on among the same teams, then there is a worse problem, as these “difference makers” compete for time, attention, and money.

Remember, someone has put their butt on the line to drive these strategic objectives. It seems we all have to have several people in leadership whose job it is to drive these objectives—and the rest of us in an organization have a conflict between the objective’s tasks and our daily workload.

Getting SMART

Savvy manufacturers set “SMART” goals—Specific, Measurable, Actionable, Realistic, Time-Based.

It’s important to understand the interrelationships between high-level goals and objectives as well as what actions or methods are required for an organization to achieve them – this falls under Specific. Measurable and Actionable are when metrics come into play—any desired result must have a set of defined measurements, targets, and actions that can be taken in order to “move the needle” on the metrics that are leading or lagging indicators of results.

If an organization is only creating one measurement to support one strategic objective, applying SMART makes sense.

Beware of too much noise

The reality is, it’s hard to limit ourselves to one measurement per objective. So, ask yourself, how many new measurements and objectives do you have? Are they all in alignment and driving the desired behavior? The pressure for too many measurements creates dysfunction within the organization. All these initiatives create competition for scarce resources and even more scarce time for change. And, we often find that when you have too many metrics, at some point they may even work against each other. The result is a contentious and noisy organization that struggles to make any sustainable improvements.

That’s why Davidson talks about not only setting KPIs but ensuring that there are processes in place to act on what they reveal. He also insists upon effective communication strategies around the KPIs as well as tying them into the organization’s performance incentives. These are solid ways to ensure that the strategies are not only assigned, but measured, and that the results you achieve really help your organization become more valuable—internally profitable and externally, to become a partner of choice to your customers.

Every day we work with manufacturers applying demand-driven methods to align all aspects of their operations in order to drive the optimal rate of production flow. This strategy is backed by a specific set of operational metrics these manufacturers measure and take action on for continuous performance improvement.

Next time- we’ll get more into specific, actionable metrics you’ll need for your demand-driven, lean manufacturing change. Many of the strategies your organization needs to initiate to get the most out of the supply chain function link to becoming more responsive to demand. We’ll figure out how to do that by measuring the right things at the right time for the right results. Read the white paper, Demand-Driven Manufacturing Metrics that Drive Action, to start thinking how you would like to align your metrics to strategy.

February 13, 2017
If it’s Not Real Time Data, It’s Old Data
We have so much real-time data around us in our daily routines. A barista starts to prepare my order the moment that I purchase my daily coffee. I instantly know how close I am to the speed limit thanks to my car’s speedometer. And I see an accurate count down of the number of minutes before my computer turns off due to a drained battery. Since all of this real-time data is available in our day-to-day lives, shouldn’t we expect the same for data we use in our manufacturing organizations?

Countless times I have walked into customer sites on Day 1 and seen old data everywhere. I have seen four walls of a conference room covered with 8 ½” by 11” printed reports, most of which were multiple weeks old. Or users that explain that they perform analysis based off of desktop spreadsheet files, with manual data loads. In each of these cases, people are operating off of old data, even if it was updated just a few hours ago. If my speedometer had that same delay, I would have a lot more speeding tickets!

Old Data is Just… Old Data

Manufacturers today are asking themselves how they can do better and be better. They realize that to be competitive, they should look inside the factory first and explore their own processes to find areas for improvement. If they analyze their data to see what it shows about their operations, they tend think that any data to go off of is better than no data, right? Not always, I say.

Based on how fast your environment changes, it could be detrimental to make decisions off of old data. Since the pace of business has increased for manufacturers, thanks to both technology and complexity, so too should the pace at which data is collected and made available to make informed decisions. For example, consider everything that can happen in the span of an hour:
- Purchasing finds out that a truck shipment of raw materials will be delayed two days due to weather.
- A new customer puts in a rush online order double the size of previous months.
- Maintenance begins fixing a problem on a constraint resource that is estimated to take at least a couple of hours.
Wouldn’t your organization want to know about all of these situations as soon as it could? Certainly. Keep in mind, however, that as more and more data is available, you’ll need to discern if, when, and how you take action. That is, you’ll need to separate knowing that events occur versus reacting to them right away. Each event could immediately impact your organization’s priorities, but you also don’t want to be jumpy and let every event disrupt your overall process. The important thing is that you are aware and that you have the right information at hand to make necessary decisions.

Better yet, your systems can also be aware of this same event data and alert you only to the issues that require your intervention. Technology solutions for manufacturers should be able to take real-time data, assess it against other conditions and values, and then notify you to respond only to the events that need your attention. This is the nature of demand-driven manufacturing – since the focus is on overall production flow, you only need to address those issues that disrupt flow. The rest is probably just normal “noise” – or what becomes a normal day for a manufacturer.

Manual Reporting Makes Data Stale

So how did we get to the point where so many manufacturers are not using real-time information? Thankfully, manufacturing technology is catching up to provide all of the information and analytics that companies seek in an automated, real-time manner. Organizations have always had the desire for information and reports, but they’ve commonly only had manual methods as options. Consider the volume of reporting that a typical manufacturing company does on a recurring basis – that’s a lot of manual reporting happening based on non-real time data. Think of the time drain that both the manual data collection and report running put on a company. If it takes an analyst only two hours to run a report, that means they are already using information that’s at least two hours old.

If you run reports on yesterday’s manually collected data, then you will only have information about yesterday. Further, we will still need a clear, straightforward way to display that information to users. I know my car’s current speed based on the easy-to-read dashboard, for example. If we demand that our organizations collect real-time data – and we have a tool like a visual factory system to display this information – then we have a powerful platform from which to understand what is happening today and what to prepare for tomorrow within operations. In the next blog, we will pick up on this topic of how to use historical data in a meaningful way, but in the meantime, send me your comments and questions.
January 14, 2016
Visual Beats Verbal

If a picture is worth a thousand words, then visualizing a factory floor says a lot for an organization. The ability to translate any environment into a visual representation is incredibly empowering and is a strong step toward evolving a manufacturer into a connected, cutting edge company. I have had the privilege of working with organizations in their journey to becoming a ‘visual factory.’ What I have learned is that the drive to become a visual factory is founded less on a technology revolution, but more a basis to communicate with users in more natural ways.

Dominant Visual Learners

I believe the manufacturing evolution toward visual factory information systems is an example of technology catching up with basic human behavior. At 65%, visual learners make up most of the population. However, you wouldn’t think this if you consider all of the written reports, emails and spreadsheets that the average company outputs. Often, this is in absence of a tool that allows users to create the same information visually. When the result is verbose and hard-to-absorb written communication, it’s no surprise that people have difficulty retaining information. When the objective is to have all people within the system on the same page and informed, it’s best to communicate according to their preferred learning method.

Pictures are a Universal Language

A significant advantage of a visual information system is its universal nature and language independence. Visual factory systems use elements such as diagrams, charts, and colored indicators to communicate status with very few words. In my experience, organizations have a wide range of language and literacy levels. User adoption increases based on the tool’s ease of use, but also by having all users comfortable with using the information that the system presents. Additionally, removing written components also makes the information more understandable across languages. This is an important feature for global enterprises.

Allow Antidotes to be Created

In a slightly contradictory way, the other advantage of a factory visualization system is that it doesn’t spell out everything for a user. In my experience, writing out what people should be learning doesn’t always lead to higher information retention. It’s good for them to create an antidote in their mind about what they see. Naturally, when someone looks at a simple, clear diagram or picture, they take a brief moment to absorb the information and come to some sort of conclusion. They are taking in the visual elements and making a judgement or asking a question based on what they see. If they have a question, ideally they interact with screen components and drill into the visualizations to learn more. Creating the antidote of what they observe leads to more user investment and sense of ownership with the tool and information. Sharing this antidote with other people also increases understanding. This is key to making a visual factory system the primary tool in a continuous improvement journey. For example, when an employee sees a downward trend in on-time delivery, perhaps they drill through to escalated maintenance information related to a resource. The maintenance information may display time series data to the employee, showing increased downtime every day around a consistent period. The employee could come to a conclusion that to improve and prevent this downtime – and avoid compromising deliveries – planned maintenance could occur weekly to make sure the utilized resource is running at its maximum available capacity.

While manufacturing companies have been creating reports for many years, only now do they have options when it comes to visual factory applications. Being able to reach users at every level in the organization and clearly communicate status is the dream for any manufacturer. The benefits of a visual factory are far superior to the verbal and written alternatives. Next time, I will explore the potential and power behind real-time visual factory metrics. Until then, feel free to send me your questions or experiences on anything visual factory related.

September 24, 2015

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