WHAT IS IT?
Operational visibility is the ability to objectively track and monitor activities within an organization.
WHY DOES IT MATTER?
WHAT HAPPENS IF YOU DON'T HAVE OPERATIONS VISIBILITY
Overtime, controlling operations become increasingly difficult. This leads to;
WHEN SHOULD YOU START TO WORRY ABOUT VISIBILITY?
Once a business has 40 employees or more, the management team slowly starts to lose visibility. At this point, the management team needs to rely on visibility tools to maintain control of the business.
What is the connection between logistics visibility and KPIs? Visibility is the ability to track activities within an organization. KPIs on the other hand, show performance of an organization. Performance of an organization reflects its activities. If KPIs are representative of activities within your business, then KPIs give you visibility. If your KPIs neglect to show performance in certain areas of your business, then they don't give you complete visibility.
When do KPIs fail to give you visibility?
1. When KPIs neglect certain areas of business. In some cases, businesses tend to assign KPIs only to major parts of their operations. Running entire portions of a business without KPIs limits visibility and control. In such cases, KPIs don't provide adequate visibility.
2. When KPIs are oversimplified/generalized. Sometimes businesses oversimplify KPIs for convenience. However, this can come at a cost of missing factors that influence performance. In other cases, businesses tend to generalize KPIs for all their departments. This is convenient but can miss important indicators specific to one department.
3. When the connection between KPIs and real performance breaks down. In some cases, KPIs don't get changed as a business evolves. Over time the connection between KPIs and real performance breaks down. In such cases, KPIs provide myopic visibility to operational activities.
For KPIs to provide you adequate visibility, you need to peg your KPIs to core issues affecting performance. If not, you at least need to understand how KPIs are related to real performance. For example, cost KPIs are popular in logistics operations. To get the best out of logistics cost KPIs; you need to understand that productivity is the real cost driver and cost KPIs only show the impact of productivity. High productivity reduces operational costs while low productivity has the opposite effect. If your logistics cost KPIs are showing bad results, productivity is your culprit.
1. Visibility can reduce operational costs:
Visibility can help you notice inefficiencies in your operations. Inefficiencies lead to thousands of dollars in unnecessary expenses. Removing inefficiencies reduces unnecessary expenses. Without operational visibility, inefficiencies can go unnoticed.
For example, a warehouse operator can have 15 minutes of unnecessary idle time for every hour of work. Those 15 minutes of idle time can easily go unnoticed in a bustling warehouse. If the said operator gets paid $50K a year, that means $12.5K of their salary was paid for them to sit idle. 10 of such operators could cost a business $125K in idle time expenses. Operations visibility allows you to notice and stop these small windows of idle time. For example, an operator on the clock without any movement of goods or task associated with them can be flagged as idling.
2. Visibility can help you foresee bottlenecks in your operations:
Every operation has at some point experienced a logistical disruption or bottleneck. Such a disruption can either be activities slowing down or operations grinding to a complete stop. When you have a bottleneck in logistics your customers get unhappy. Moreover, you end up spending more to deal with the disruption.
Visibility can help your business foresee and stop a bottleneck before it becomes a problem. Visibility allows you to monitor how fast goods are moving in different segments of your logistics. The logistical segment with the slowest movement of goods usually ends up being a bottleneck. If you notice activities slowing down in one of your logistics segments, you can deploy additional resources to speed things up. This will allow you to avoid a bottleneck before it becomes a big problem.
3. Visibility creates a suitable environment for continuous improvement:
"You can't improve what you don't measure" is an adage that makes visibility necessary for continuous improvement. Visibility allows you to measure the performance of your logistics. Performance measurement creates a suitable environment for continuous improvement. If you don't have visibility, you can't objectively measure performance. Thus, you can't be certain if a process improvement initiative is improving your logistics.
Visibility has more benefits than the 3 above. Visibility can also help improve reliability, accountability and operations management among other things. The most important thing to keep in mind is: benefits of visibility only come to life if there is a deliberate effort to improve logistical processes.
Logistics visibility is the ability to objectively track activities within an organization. The extent of visibility can vary as follows:
1. Complete visibility in which you are able to track all activities; and
2. Partial visibility in which you are not able to track all activities.
Example: Visibility in trucking operations (similar logic can be applied to manufacturing and warehousing)
If you can easily access the answers to the following questions, then you have reasonable visibility in your operations.
1. How many trucks are available for use?
2. How many trucks are on the road?
3. How much weight are the trucks on the road hauling?
4. Where are your trucks heading to?
5. How much time will each truck take to complete the delivery process?
6. How many hours of work is each driver scheduled to work?
7. What is the maintenance history of your trucks?
8. How many trailers are available for use?
9. How many trailers are currently in use?
10. What is the current level of trailers, trucks and cross-dock utilization?
11. What are the operational activities at your cross-dock facility?
12. What is the current level of inventory to be shipped at the cross-dock facility?
13. How much are the operational costs?
14. What are your cost components and their relative size?
15. What is the current performance level in relation to performance targets?
16. How many shipping requests are in progress?
17. What are the details associated with current shipping requests?
18. What are the details associated with outstanding shipping requests?
19. How much revenue is being generated from current operational activities?
Being able to answer the above questions is one step towards attaining visibility. The second step is figuring out the accessibility of operational information. Thus, visibility can also be classified as real-time or delayed depending on accessibility.
Real-time visibility: the ability to get real-time information from logistics operations. The best example of this is real-time information through dashboards. Another example is real-time access to logistical data. Real-time visibility allows you to respond to logistical challenges as they happen.
Delayed visibility: operational information is not accessible in real time. Most logistics operations fall into this category. Delayed visibility does not allow a real-time response to logistical challenges. Even with its’ shortcomings, delayed visibility is better than no visibility.
Businesses should not chase after full visibility without a clear strategy on what to do with the visibility. Visibility is only useful if it helps improve logistics outcomes. To get full benefits of logistics visibility, it needs to be paired with other best practices such as accountability and a culture of continuous improvement.
"You can't manage what you don't measure" is an old adage that is true in logistics. Thus, you should measure and analyze all aspects of your logistical operations.
Benefits of measuring and analyzing your logistical operations:
Slotting is the process of determining the most efficient arrangement of items in a warehouse, which promotes easy access to items that are frequently used. Most examples of slotting have been drawn from kitchen arrangement: We naturally place items we use the most in a close vicinity to where we stand while cooking. This helps to reduce the time and trouble of digging for these items from the back of kitchen cabinets.
The same logic applies to warehouse arrangement. You want high-selling products nearest to the access point in order to minimize travel distance. High travel distance in a warehouse means low picking efficiency, and low picking efficiency means added time in your order fulfillment cycle. Adding too much time on your order fulfillment can affect your customers, especially if it leads to late deliveries.
However, in most cases, poor slotting adds small windows of time to an individual order. Because the added time is short, it usually goes unnoticed. But over extended periods, those small windows of unnecessary time due to poor slotting can quickly add up to a lot of hours. For example, if a warehouse processes 900 fast-moving orders a day, and poor slotting adds a minute to each order processing time, that adds up to 900 minutes spent on unnecessary labor — in a single day. In a year, that translates to about $90,000 in unnecessary labor expenses, and that’s just one of the several expenses you incur due to poor slotting. You also incur the opportunity cost of unnecessary travel time and extra machine usage, further eating away at your profitability.
Below is an illustration which shows how a slotted warehouse looks like.
In the slotted warehouse, all fast-moving products are close to the warehouse access point. This allows pickers to quickly access the products and complete their orders. In the poorly slotted warehouse, pickers frequently travel to the back of the warehouse to access fast-selling products. This adds unnecessary travel time and increases the order fulfillment cycle.
Most warehouses skip on slotting optimization because they don't realize the benefits. Others skip on slotting because they think it is complicated and requires expensive specialty software. But slotting optimization can be done in Microsoft Excel, a common and simple program. The initial set-up might take a couple of hours, but soon after, you can optimize slotting with a click of a button.
Data can highlight hidden inefficiencies in logistical processes better than simple human intuition. And for that reason, most futuristic logistical organizations have already incorporated data into their operational management practices. However, the challenge for almost all logistics companies is to generate valuable business insights from their data analysis efforts. Theoretically, it is easy to say that data adds value, but in reality, the “how” is more difficult. Below, you’ll find six steps to incorporate data into improving your operations management. The goal of these steps is to lower your operational inefficiencies — in essence, this is the path to increasing your profitability.
Step 1: Create a Credible Sales Forecast
Because your sales are influenced by myriad factors ranging from general economic conditions to your customers’ behavior, a credible forecast takes time to establish. For an accurate forecast, you must invest time to understand and quantify the impact these factors have on your business.
No matter how small your business is, you’ll likely find an overwhelming number of factors affecting your business. To avoid analysis paralysis, narrow your focus to a handful of variables that have the biggest influence on your sales.
Your forecast accuracy will probably be low the first few times you do it; however, that shouldn’t deter you. As long as your forecast accuracy improves over time, you are on the path to creating a credible forecast. After all, forecasting isn’t a science, but rather an art of predicting things as close to reality as possible.
Hitting a forecast accuracy of about 90% is usually good enough to prove that your model is credible. It’s not uncommon for demand planning models to take a couple of months to hit 90% accuracy, and some take years. However, don’t get hung up on 90%: The key thing is having a forecast that can guide you to make good decisions. A good forecast is only good until it is not — and thus, it is important to periodically update your demand planning model to reflect the ever-changing business landscape.
Step 2: Translate Your Forecast into Resources Needed to Fulfil the Sales
Once you have a credible forecast in place, you need to know the resources you’ll need to fulfil the expected sales. This step seems to be the most obvious one — but this is usually where most businesses fail.
Based on historical performance of your logistics, you should have an engineered performance standard. Use the engineered performance standard to deduce the optimal resources needed, such as labor hours and equipment.
The concept of having an engineered performance standard seems trivial, but such a standard is key to eliminating inefficiencies: An engineered standard implicitly establishes the expectation of how operational tasks need to be performed to avoid idle time. The absence of an engineered standard creates room for unnecessary idle time to affect your operations.
Don’t forget to take breaks and other clerical activities into account while planning for resources needed, and pay special attention these activities that fall outside the scope of your engineered standards. It’s generally best to have operational procedures dictate how and when clerical activities are done, coupled with strict enforcement, to deter unnecessary idle time.
Step 3: Share the Plan and Clear Expectations with Your Team
After you have established the optimal resources needed to fulfill forecasted sales, communicate with your team — especially those supervising labor and equipment usage. In most cases, labor and equipment usage plans don’t go beyond senior managers, even though such managers do very little to manage day-to-day operations.
However, communicating needed resources to supervisors isn’t enough. You should also set clear expectations on what employees need to achieve to adhere to the plan you set. For example, if the plan says employees will need to put in 100 hours of overtime to fulfill expected sales, you must inform the shift supervisor. Most importantly, you should hold the supervisor accountable to overtime hours after the sales are completed. If they do better than the plan, give everyone involved a pat on the back. Otherwise, the supervisors will need to explain why they failed to stick to the plan.
Unfortunately, holding people accountable in the workplace can create negative connotations. Our version of holding people accountable focuses on understanding why the issue happened. Thus, an operations supervisor should be expected to explain why they used more overtime than they were allowed. A reasonable such explanation could be unexpected sales spikes or orders that were difficult to process.
Step 4: Monitor Operations Status for Forecast Deviations
Creating a labor and equipment usage plan based on a forecast is just half of the work. The other half is building a contingency plan in case the forecast is wrong. In fact, having a completely accurate forecast takes a lot of luck. In most cases, a forecast varies slightly from actual sales figures. If the deviation is small, you usually don’t have to do much to arrange more resources to complete orders. However, if the deviation is large, you might need to activate a contingency plan.
A contingency plan can take many forms, such as having an arrangement with a temp agency to bring you extra labor if there is a sales spike. What you don’t want to do is search for a temp agency for the first time when you see a sales spike. Instead, you’ll want to speak with an agency early on, so that if you need extra labor, all you have to do is make a phone call.
Step 5: Collect Feedback, Review Operations Data, and Make Improvements
After you have processed all the volume as per the forecast, collect operational data and feedback from all stakeholders. Collect feedback on the efficacy of the plan you created, how difficult it was to enforce, what went wrong, and how sales spikes and dips were handled. Use this feedback to improve how decisions are made in response to variation from the original plan.
If the forecast was off, identify the reason why you got it wrong and use it to improve the model. If performance was far below or above the engineered standard, identify why. You need to know if there was a labor issue, or if the engineered standard needs to be changed.
Try to avoid turning this step into a blame game. Remember, the most important outcome of this step is to improve the forecasting, resource planning, and operations management. Mastering this 5th step is what leads to process improvement which translates to more business profitability.
Step 6: Repeat Steps 1-5
Your logistical operations will change as much as your clients and their needs change. Thus, you will always need to improve your forecasting model, performance expectations, and your response to market changes. If you make steps 1 through 5 part of your organizational culture, over time, your business will become more efficient and your profitability will increase.
Don’t let continuous improvement fall to the back burner — your business’ competitive edge relies on it.
Many logistics managers share a common goal: reduce idle time. In logistics, idle time can be defined as a time within operational hours in which people and equipment are not moving goods. The ultimate goal in logistics is to move goods — and the faster you move goods, the less costs you incur. Thus, idle time can hurt profitability.
Idle time can be classified into two categories: necessary and unnecessary. Necessary idle time is caused by reasons beyond our control and is usually mandated by government, the nature of your logistical operations, or the equipment you are using. Such idle time can be anything from employees breaks to equipment maintenance downtime. Necessary idle time is unavoidable and usually encouraged to ensure sustained long-term logistical performance.
In contrast, unnecessary idle time is being unproductive because of reasons that are within our control and can be cause by anything from employees slacking or waiting for a slow printer to untimely equipment failures. In most cases, we tend to think of unnecessary idle time as just the way things are because we don’t realize its impact.
Beyond idle time, an operation can be moving slower than expected because of technological challenges. Moving slowly has the same impact as idle time: lost productivity. Think of high productivity with regular interruptions like you would think of people traveling. You can drive fast toward a destination and make a long stop, or drive more slowly without stopping. Either way, you reach your destination at the same time.
For example, tedious, repetitive clerical work is one technology-based cause of warehouse slow-downs. If there is tedious repetitive clerical work in your warehouse, you’re likely not making the most out of automation technologies. Automating repetitive clerical tasks speeds up the respective activity and frees people to do other, more productive duties.
Unnecessary idle time is a profitability enemy because you end up paying for more costs than you should. Every warehousing facility should have systems in place to reduce the likelihood of unnecessary idle time.
Why does idle time happen?
1) Difficult to notice
In operations, idle time can be subtle, but that’s not to say it isn’t costly. Small windows of idle time in an operation can translate into significant costs over the long term. For example, 5 minutes of unnecessary idle time for every hour of work for a workforce of 100 people can add up to $273K of lost time in a year. However, those 5 mins of inefficiencies per hour can be incredibly hard to detect or can be taken for granted without realizing the long-term impact — unless you put effort into identifying and eliminating it.
2) Absent or lenient operational goals
If you run an operation without setting a clear productivity target, people tend to slack — it’s human nature to relax a bit if there are no clear performance expectations. Setting a lenient goal or no goal at all allows for idle time to thrive. Logistics operations should always set performance goals and enforce them.
3) Poor equipment/ technology
In some cases, idle time is due to technological shortcomings. Doing clerical paperwork instead of moving goods is just a single example of how technology — or lack thereof — can slow down operations. In the worst of cases, I have seen operators printing data from one data management software, and soon after manually entering the data into a different software. Technology could have eliminated the data entry process and allowed the operators to spend more time on productive functions.
How do you avoid idle time?
1) Track and measure everything
Track, measure, and analyze all activities in your logistical processes, including clerical work. Most logistical operations are tracked, but companies fall short in analyzing that data and generating ideas that can improve processes. To ensure your business is not susceptible to idle time, implement a formal structure to analyze and improve processes. Sophisticated logistics service providers use productivity tracking software to reduce the likelihood of unnecessary idle time. Such software can be too expensive for small operations, but small companies can use simple analytical tools made on MS Excel to mimic productivity tracking software.
2) Set operational goals and enforce accountability
Without clear operational goals that are understood by all team members, human faults kick in and people start to slack. However, setting targets is not enough; you need a good enough target. If goal setting is not something your business has a habit of doing, it might take time for you to set an adequate operational target. Goal setting takes many iterations before you master it. However, setting good operational goals is not enough. You also need to implement an accountability structure to enforce and follow up on targets. Without an accountability structure, targets can easily be disregarded.
As we’ve seen, idle time can be subtle, insidious, and costly. The unfortunate thing is that you don't know how much idle time is costing you until you solve for it. Having a comprehensive data-driven operations management system accompanied by an accountability framework can help alleviate this type of operations inefficiency. Another thing to remember is that idle time will sneak into your operations the moment you stop paying attention. It is important to make idle time reduction part of your organizational culture and not a one-time fix.
Intuition is behind most decisions we make. One reason is because it’s easy: When you’re relying on intuition, you can make decisions quickly and without much work. However, intuition alone is not enough to always guarantee good decisions. As much as we all like to say that our gut feeling is always right, our intuition can sometimes lead us astray. Our opinions are based on past information and experiences. Implicitly, we simplify decision-making by sometimes projecting past experiences and information to inapplicable situations. In such cases, our gut feelings can be wrong. Unfortunately, we find that out only after we suffer the consequences of our decisions. In any supply chain operation, there are many moving pieces and decision points, which makes supply chain operations uniquely susceptible to these consequences.
In contrast to our opinions, analytics can consistently provide objective advice. Introducing analytics to your supply chain decision-making has two benefits among many that intuition can’t compete with
1) Analytics can reduce unnecessary business costs due to cognitive biases
Cognitive biases can be one reason, if not the main reason, why our intuition can be wrong. Cognitive biases are mental shortcuts we take to simplify decision-making. Biases speed up the decision-making process but they can also cloud judgement. Analytics, however, can make up for shortcomings that arise from our biased intuition.
For example, status quo bias — defined as a preference for keeping things the same — can hinder process improvement efforts. However, data analysis and visualization can convincingly point to process improvement opportunities. It’s easy to overlook 15 minutes of lost time due to hidden supply chain inefficiencies. But analytics can point out that, 15 minutes lost by 100 warehouse operators in a course of a year can amount to about $130,000 of unnecessary costs. Knowing that hidden inefficiencies costs you $130,000 is a good motivation to invest in process improvement. Such a convincing justification to improve processes can be hard to believe without analytics.
Having an evidence-based decision-making framework at all decision points in your supply chain can reduce costly implications of biased decisions.
2) Analytics can give you confidence in your decisions
When making business decisions by intuition, managers and executives always run the risk of facing potentially unpleasant results. Analytics can confirm or disprove your intuition and give you confidence that you are making the right decision. The power of analytics is such that, even if you make a terrible decision using bad analytical insights, you still get the benefit of doubt because you exercised due-diligence to sense-check your gut feeling.
For example, when deciding whether to acquire a new business facility, you can base the decision on optimisms that sales will increase to justify the new facility, or you can rely on a comprehensive industry analysis that clearly justifies strong indications of sales growth. If the optimism is confirmed by a comprehensive industry analysis, you can confidently undertake the decision to acquire the new facility. With the analysis in hand, the decision-maker has something to point to if sales don’t grow as expected, rendering the need for a new business facility obsolete after the facility has been acquired — it was just unpredictable bad luck. With intuition alone, however, the unfortunate decision maker looks incompetent if sales expectations don’t materialize.
Analytics inform decision-making
It is easy to make decisions on the go. There is a certain level of flexibility and speed that comes with intuitive decision-making. However, your gut feeling can be biased. Analytics can give you confidence and reduce biases in decision-making. Moreover, a data-driven decision-making framework can provide objective insights that can improve business outcomes.
But, analytics has its limits. The full value of data can only be realized if the analytical process is solving a problem that is clearly defined and deeply understood using the correct methods. In the words of Darkhorse Analytics’ Daniel Haight, “Analytics can successfully improve decision-making if you use data to solve the right problem the right way.”
Three factors — data analysis, accountability, and communication — can combine to improve your logistical processes. But the trick is to find a balance between the three that will support continuous improvement. Each factor has its place: Analysis generates performance standards, without which you cannot enact accountability. Accountability enforces the implementation of data-generated insights. Communication is the glue that holds analysis and accountability together; if communication fails, accountability and analysis alone cannot yield successful results. Let’s cover in more detail how each of these three factors can improve your operations.
How do you use data to improve logistical processes?
Data is available now more than ever before. But it takes more than the mere presence of data to truly impact efficiency. Reap the benefits through these simple steps:
Collect and Organize Data
Not only do you need to collect data, but you also must understand what the data you collected means and what it pertains to. For example, most operations have data collection systems for both productive hours and paid hours. Paid hours data should be used for budget management while productive hours should be used for productivity analysis. If one doesn’t understand the underlying meaning of this data, they can easily reverse the use of the two types of hourly data.
Visualize and Analyze Data
Present data in a manner that can spark questions. The figure below shows productivity for four warehouses. From the graph, you can see that the fourth warehouse is far more productive than the rest. This can spark a number of questions: Is building D more productive because it has more skilled staff? Does the building receive orders that are easier to process? Is the building cleaner and thus easier to navigate for operators? Investigating these questions generates insights that can improve productivity for the other three buildings.
How can accountability improve logistical processes?
Accountability is about setting objectives and enforcing them. Accomplishing one goal usually means setting a new goal. Over time, this leads to a gradual improvement in operational processes.
If there is no structure in place to sustain and guide accountability, it will eventually fail. To ensure accountability thrives, you must build a formal accountability structure that clearly defines each person’s role in improving processes. The structure can also be the vehicle through which operations targets get enforced. Below is a sample of what a formal accountability structure can look like.
Having a formalized accountability structure means you can consistently enforce target-oriented performance while controlling operational activities. Without a formal accountability structure, goals can fade into complacency, which leads to unnecessary costs.
How can communication improve logistical processes?
Effective communication creates process-improvement culture. All operations stakeholders are experts in their respective areas of the supply chain, and their collective knowledge produces far better results than individual efforts. To benefit from this collaboration of expertise, it’s important to have channels in place to facilitate communication. There are three ways to leverage communication towards a culture of continuous improvement:
The Ultimate Goal
The most important aspect in process improvement is a thorough understanding of operations. The lack of an in-depth understanding of operations means analysis, accountability, and communication cannot improve operational outcomes. Instead of making these three factors your main ambitions, use them as tools to deepen your understanding of operations.
Welcome to our newly revamped logistics blog. This blog aims to educate logistics professionals on the value of data-driven management.
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