Continuous Improvement: Eliminating Waste in Lean Logistics Tool Creation

Continuous Improvement: Eliminating Waste in Lean Logistics Tool Creation

Creating effective (and cool) tools for customers is one of my favorite things to do. You get the Voice of Customer, merge that with your skills, and balance it all with time and cost constraints. My efforts are used to help customers cut costs, lean their operations, and create visibility throughout their supply chain. But, there are harrowing and frustrating aspects to creating tools, which are readily understood and remembered by anyone who has done so. Ask anyone who makes them and you are sure to be regaled with stories that will make you laugh and cringe. We can make the process of designing and creating tools for our customers more enjoyable, cost efficient, and ultimately, more effective by doing what many of our tools are designed to do: eliminate waste in the process. To give us a framework for what waste is, we’ll be using an acronym of the Eight Wastes: D.O.W.N.T.I.M.E.

To view parts of the chart, click on each image. -->DOWNTIME Chart

Defective Production:

Two examples of defective tools are: a broken tool and a tool which does not serve the customer’s needs. Presenting a broken tool to the customer shows a lack preparation and rigor in testing. You should test your tools with as many people as you can find; the more diverse the backgrounds, the better. You will be surprised what individuals of different expertise can do to find flaws in your tool.

Not meeting customer expectations can have an impact on customer relations, because the customer may feel that you have wasted their time and money (while incurring cost to your own company). The simplest way to eliminate this type of waste is to properly capture the Voice of the Customer, while scoping the project. You also want to establish clear and reasonable goals with deliverables.

OverproductionDOWNTIME Chart

This waste is created when we produce more than (or sooner than) what the customer demands. This is one of my personal ‘toughies’ to overcome, because while creating a tool for a customer, I find myself thinking of all the cool ‘extras’ that could be DOWNTIME Chartadded with (seemingly) little effort. Those additions can add time spent on the project very quickly, which costs your company time and resources that could have been used for other work. Two other consequences of overproduction are: (1) The time involved in the ‘addition’ is underestimated or the ‘addition’ takes on a life of its own (severely deterring from the originally scoped project) or (2) The customer is ‘put-off’ by the ‘addition’, which was not asked for. This can lead to customers feeling that the project scope was not entirely understood by you, or that, frankly, you have been wasting time on ‘non-value added’ work.

Properly scoping the project and using PDCA (Plan Do Check Adjust) to check/adjust the project can help eliminate this type of waste. When scoping the project, try to make the outputs as specific as you can. This can be very difficult in the initial phases of the project, as many times both you and your customer are still ‘feeling out’ what the deliverables should be and what would be most effective for their needs. By utilizing regular PDCA meetings with the customer, and allowing the customer to be a part of the creation process (through their feedback at each stage), we can help insure the tool is being created to the customer’s needs. Keep a log of those ‘flashes’ of creativity for additions to the tool. This can be shared with the customer at the end of the project. If the original tool is useful for the customer, those additions can become future projects (with their own revenue streams for your company).


Waiting can be a horrible stress in a project. We can end up sitting on our hands, while the project deadline inexorably draws closer. One of the main ways I have created this type of waste was through improper data requests from the customer. Data is the ‘lifeblood’ of any good analysis and tool creation. We must know that the tool is functioning properly by checking outputs against expected results with the customer’s ‘real world’ data. The tools themselves are often the technologies for analysis. What is important is to know exactly what inputs will be required to produce the required outputs.

At the beginning of the project, if we hand the customer a data ‘wish list’ without having scoped the tool’s deliverables properly or without having put the required thought into the deliverables to understand exactly what data we need, we can find ourselves waiting; depending on the amount of data and the business structure of the customer. For some of the more complex tools, the required data may have to be found across many of the company’s branches and involving people who have no knowledge of the project. Typically, the more data required, the more waiting that you will have to do before you can begin analyzing it. Spend the appropriate amount of time to understand the difference between ‘critical’ data points and those that may or may not have an impact on the tool.

Not Engaging Employees (Knowledge):

One aspect of creating tools for our customers, in which this waste appears, is by not establishing contact with the appropriate personnel within the customer’s organization. For example, talking directly with the IT professional who will be pulling together some of the key data points. Much can be lost in the translation of what data we need (and why) by using our key contacts as ‘go-betweens’ to the individuals who will be getting the data together. By engaging the correct people, we can be assured that the proper data is being collected, the form the data will take, the limitations of collecting the data, and an accurate estimate of when we can expect to receive the data.

Many times, it is either impractical or, because of legal constraints or internal politics, we cannot access the appropriate people. To help minimize the impact of the waste, try to structure the data collection as regimented as possible. Create data collection forms, set timelines (and hold individuals responsible for them), and establishing ‘why’ you need the data.

Within your own organization and team, ensure that the appropriate individuals are working on the project’s components that will best utilize their skills and expertise. This may not be the case if you are training an employee. Cross-training or broadening an employee’s skill-sets are worth-while endeavors that will allow for greater value to be gained from the employee in the future. When cross-training, have a mentor with the employee to help minimize the waste that could potentially occur.


Improper handling of the data collection process can create an abundance of transportation waste. As previously mentioned, requesting data from the customer that will give little, if any, value to the project creates potential waste through waiting. This waiting is often the direct result of the ‘leg work’ necessary to collect the data. If the data is unnecessary or under-utilized in the creation of the tool, the result could lead to people feeling they have wasted their time.

Delivery of the data can lead to transportation waste, if you have not correctly scoped the correct data points or the range of data. Extremely large files may be generated, which take excess time to transfer across the internet or that have to be sent in the mail. Asking for the last two years worth of transportation data, with all the headers a WMS can squeeze in, is not necessarily going to give you the results you need for an analysis. This is especially true if the customer’s industry is in recent flux or their business model is changing. Scope the data date ranges to be appropriate for the project and what should be in the data, and leave it at that.


We can also think of obnoxiously large files as increasing a waste of inventory. Data storage, as a physical entity, is not typically an issue with modern memory capacities, but it does add up over time. This excess data inventory can also increase the complexity of the analysis. More data means more time spent culling bad from good data. Once again, having an understanding of the Voice of the Customer, the deliverables, and the creation of the deliverables can help you minimize this type of waste before it becomes an issue.

One can also think of the inventory waste as being created through the tool itself. Filling dashboards and interfaces with lots of graphs, numbers, and other such devices can look really cool, but unless they are driving action for the customer, they can become burdensome. They can also make navigating the tool more difficult (not including the wasted effort of creating and formatting them). Keep the purpose of the tool in mind, what actions should it be driving, and what metrics should be displayed to fulfill that purpose. Simple and elegant can sometimes be all that is required in a tool. Although, customers do appreciate the ‘WOW’ factor in their tools.


I’m going to take up the banner from the last point, concerning cumbersome tools. Ideally a tool should not only be effective in its design, but easy to use. The more physical action required navigating around the tool, the less likely they will be to utilize it. It still may be used daily, but having a tool that is concise enough to where the information they are looking for is readily available, will make the use of the tool more likely. Of course, actually designing this within our tools is much easier to talk about than to accomplish.

Similarly, most of our tools need to be updated with current data, in order to accomplish their goals and give output that is relevant to the customer’s current situation. We must ensure that the updating process is not overly burdensome. If this is not the case, our customers will be less likely to update our tools with relevant data. One technique that I like to use is to find the top ‘driver’ inputs that have the largest effect on the outputs. These will be required inputs, but the rest of the inputs can use averages. These ‘lesser’ important data points can then be updated at anytime in the future.

Excessive Processing:

Many of the waste examples and solutions discussed to this point could fit into over-processing. Instead of rehashing them again let’s look at other areas where this waste can be found in creating customer tools. First, don’t re-invent the wheel if you don’t have to. Take stock of tools that either you or others in your company have created. Are there aspects of these tools, which would fulfill your current needs? I don’t only mean forms, logic, and coding, but formatting. Formatting of tools will allow your tool to have that ‘WOW’ effect, but anyone who has ever done it knows the time involved can be considerable.

Along these lines, strive to keep the design of your tools as flexible as possible. This will allow for easier adaptations of the tool in the future and will allow you (or others) to transfer the technologies you have created into future projects. You may find an initial increase in effort to instill this in the tool, but the payoff in the future will more than compensate for the initial investment. With proper pre-design work, the time involved can be minimal.

Creating tools for our customers can be a very rewarding experience. We utilize a myriad of skills to accomplish it, and our customers get to take the fruits of our labor to further increase their competiveness. By eliminating the waste in the design, creation, implementation, and usage of the tools, we can reduce the effort (and cost) of creating them; while increasing the tool’s effectiveness and the enjoyment of the creation process.

Written by Chris McLaughlin, Lean Deployment Specialist at LeanCor

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Posted by LeanCor Supply Chain Group

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LeanCor Supply Chain Group is a trusted supply chain partner that specializes in lean principles to deliver operational improvement. LeanCor’s three integrated divisions – LeanCor Training and Education, LeanCor Consulting, and LeanCor Logistics – help organizations eliminate waste, drive down costs, and build a culture of continuous improvement.

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