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Archives for September 2019

Managing the Calendar on Warehouse Automation Projects

By Ian Hobkirk | 09/24/2019 | 5:25 AM

Most companies that have attempted to implement automated material handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is fifth in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

Blog 5 DC 350Many companies set themselves up for failure early on by committing to an unmovable deadline for completing the project. The most common reasons for this are:

  • Facility exits: The timeline is based around a date when the company must exit an existing facility
  • Seasonality: The timeline is based on the need to have the system operational in time for a peak period (often around the Christmas holiday season).
  • 3PL contract expiration: The timeline is based on transitioning away from a third-party logistics provider on a certain date.

The deadline may be set far enough in advance that the company believes it is easily attainable. Then, Murphy’s Law begins to play out, and the timeline is extended by unforeseen circumstances. Faced with the seemingly unmovable deadline, the company then marches inexorably towards a go-live date that becomes more and more risky with each passing day. Executives issue ultimatums. Project managers are offered carrots or threatened with sticks based on achieving the timetable. Key stakeholders feel increasing pressure to “launch the boat” while workers are still patching up holes in the hull.

All of these pressures often cause the project leaders to decide to move forward with the go-live, even though all the indications are that the technology is not yet fully tested and ready- sometimes with catastrophic results. Executives may fear the impact of a delayed launch, but be blind to the far greater consequences of a premature, failed launch (remember, it’s too late to bring the boat back to the shipyard after it’s sunk to the bottom of the harbor!).

So, what can be done to resist this pressure for a premature go-live?

  • Estimate the timetable accurately: To begin with, project planners should research the actual time it will take to complete the project.
  • Don’t ignore design and vendor selection time: Companies often under-estimate the time it will take to fully design the system and conduct a thorough vendor selection process (these two steps alone can take six months or more on complex material handling systems).
  • Approvals always take longer than expected: Executive approvals for capital-intense warehouse automation projects are rarely  Blog 5 excerpt4x-100obtained in a matter of days, even at small companies with streamlined decision-making processes. Obtaining capital request approvals, negotiating details of contracts, and performing legal reviews can take weeks or months- not days. This process is often repeated multiple times: once for the overall project budget approval and again each time large vendor contracts are to be executed. Time for this should be built into the timetable from the beginning.
  • Manufacturing lead times can change: In busier economic periods, 
    manufacturing lead times can be much longer than in slower times. Don’t assume that vendors can manufacture equipment as quickly as they may have done during the last project you worked on. Get updated manufacturing time estimates prior to presenting any project timetable to the management team.
  • Add contingency time: Remember, it is usually difficult or impossible to anticipate when Murphy’s Law will strike. Add contingency time to the project schedule, even if the weather seems good and it looks like clear sailing ahead.
  • Have a backup plan to extend the deadline: In most of the scenarios cited above (facility exits, peak periods, 3PL contract expirations), the deadline is often not truly “unmovable”. Lease extensions can be negotiated, penalty clauses can be enacted and paid, overflow facilities and temporary labor can be hired to survive peak periods, and 3PL contracts can be renegotiated. While all of these alternatives can be costly, they may be vastly less expensive than having a failed project with product unable to ship. Additionally, if the backup plan is developed early enough, it may be possible to negotiate more favorable terms than if the discussions are held at the last minute under emergency circumstances.

 

 

 

Expecting the Unexpected on Warehouse Automation Projects

By Ian Hobkirk | 09/17/2019 | 7:09 AM

Most companies that have attempted to implement automated material handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is fourth in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

 

Blog 4 DC 350A key tactic to avoid disappointing project results is to explain the concept of Murphy’s Curve to the executive team and financially account for the inevitable drop in productivity during implementation. Plan for Murphy’s Curve. Build it into the project ROI model through a solid risk mitigation plan.

Some key cost increases which often occur during the Murphy’s Curve period at project startup include:

  • Temporary labor costs: Often more labor will be required in the weeks (or months) following the technology deployment. Workers must become acclimated to the new processes and technology, and productivity rates will almost certainly suffer at first. Additionally, managers must get used to different ways of releasing work into the new system to be able to balance labor and workflow across the operation. It is rare to get this right the first time, even with sophisticated warehouse control software (WCS) systems. Additional labor and supervisors will likely be required, and perhaps even an additional shift will be needed on a short-term basis.
  • Expedited shipping costs: Even with additional labor, it may not be possible to keep up with outbound order volumes in the first few days or weeks after go-live. It may be necessary to subsidize the cost of expedited shipping on some orders to maintain customer service levels.
  • Additional inventory carrying costs: If the project involves relocating the distribution center from one site to another, then it may be necessary to purchase additional inventory in order to allow the facilities to operate in parallel for a brief period.
  • Unknown costs – contingency factors: Additional costs for labor, shipping, and inventory represent only the “known” areas where overruns can be expected. Each project inevitably contains unexpected, “unknown” costs that present themselves once the project begins. These unknown events are what often come to mind when the phrase “Murphy’s Law” is used – anything that can go wrong often does go wrong. A few real-life examples of unplanned-for events plaguing warehouse automation projects include:
    • A company that was expanding its distribution center discovered that the incorrect sprinkler heads were used when the building was constructed many years before and was forced by the local fire marshal to upgrade the entire sprinkler system in both the existing and new portions of the building.
    • A company that was constructing a new distribution center encountered a period of unseasonably bad weather which severely delayed the foundation work and set the entire project behind.
    • A company that was installing new pallet racking in California was unable to find a certified slab drawing of the building they had moved into and was forced to have core samples taken for the seismic analysis after weeks of searching for the drawings.

In each of the above (true) examples, the problems which befell the project were difficult to anticipate but resulted in both time and cost overruns. Adding a certain percentage of contingency time and cost to the project budget is the only way to ensure that the budget can withstand some of these unexpected manifestations of Murphy’s Law.

The above costs should be estimated as accurately as possible and included as project costs in the accounting model. While doing so will almost certainly increase the payback period for the technology, failing to account for these factors will result in a return-on-investment projection that is incorrect. If the project will not meet the corporate ROI guidelines once the additional costs from Murphy’s Curve have been factored in, then perhaps the rationale for the doing the project in the first place should be reconsidered. Don’t fall prey to thinking that the current project will be the exception to the rule. Remember, the productivity drop from Murphy’s Curve occurs even if everything goes according to plan. There is an inevitable adjustment period as operators and managers get used to using new technology, which will result in loss of efficiency even in the best of deployments.

 

Assessing Risk on Warehouse Automation Projects

By Ian Hobkirk | 09/10/2019 | 5:04 AM

Most companies that have attempted to implement automated material handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is third in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

Blog 3 DC350
A good first step towards accounting for Murphy’s Curve is to perform a risk assessment on each of the potential solution scenarios being considered. Often, the technology that holds the greatest promise of cost savings can also involve the greatest risk of failure. Certain forms of warehouse automation may be very unforgiving of minor design flaws or changing business conditions, while other technologies may be more flexible and adaptable to these forms of change. Other technologies may seem promising but may be relatively new and untested in the marketplace. Companies seeking aggressive cost savings can often be blind to the risks inherent in some technologies. A thorough risk assessment can be an effective way to highlight these risks and impact the choice of design and technology early in the project.

To perform a risk assessment, start by identifying the specific risks which are present on the project. Examples of risks to account for include:

Risk bullet@2x

Next, assign each risk a weight factor based upon your company’s tolerance for risk in this area. For example, the company may be relatively unconcerned with the risk of cost overruns compared to the risk of the project not going live on time prior to a peak demand period. These two risks should be weighted differently.

Lastly, give each potential solution scenario a numeric rating for each of the risk areas (a low score represents low risk, a high score represents high risk). Multiply this rating by the weighting factor to achieve a weighted risk score for each solution scenario. It may be discovered that certain solutions that offer the highest potential for labor savings may also have the highest risk of cost or schedule overruns. As a result, the company may choose a solution that is less automated, but less risky, or may choose to proceed with the riskier technology and build in contingency factors for cost and time overruns. 

 

 

Don't Ask the Barber for a Haircut

By Ian Hobkirk | 09/04/2019 | 5:03 AM

Most companies that have attempted to implement automated material handling equipment have discovered that these projects can be particularly vulnerable to Murphy’s Law, the principal that, “anything that can go wrong, will go wrong.” This blog is second in an ongoing series on “Beating Murphy’s Law in Warehouse Automation Projects.”

Blog Template 2 DC 350
One key tactic for beating Murphy’s Law is the need for objective advice during the project concepting phase, the adage of “don’t ask the barber if you need a haircut.”

Why is Murphy’s Curve such a surprise to so many companies? In other words, why do organizations embark on projects with such unrealistic expectations for achieving rapid performance gains? The reasons likely differ in each case but being “over-sold” on a return-on-investment (ROI) projection by less-than-objective sources is often at the heart of the matter. Executives reviewing a business case for a capital project would do well to ask themselves whether those preparing the figures have any incentives to present an overly optimistic picture, either intentionally or unintentionally. It may be that the underlying business case was developed by an equipment provider who stands to benefit if the technology is adopted and who may chose to ignore the potential Murphy’s Curve of temporary productivity losses.

In another scenario, the business case may have been developed by company employees who may be desperate for the relief they believe the technology will provide, but too inexperienced to understand the trough of productivity that will inevitably occur before the benefits are realized. In either case, very few companies appear to account for “Murphy’s Curve” in any meaningful way during the project concepting phase. While some may acknowledge that there may be a learning curve associated with new technology, most seem to believe that the curve will be short and performance will never be worse than the present (pre-go-live) levels. Very few companies actually build-in an increase in operating expenses to the project budget to account for Murphy’s Curve. As a result, executives embark on the initiative with an inaccurate view of what could unfold.

The opinions expressed herein are those solely of the participants, and do not necessarily represent the views of Agile Business Media, LLC., its properties or its employees.

About Ian Hobkirk

Ian Hobkirk

Ian Hobkirk is the founder and Managing Director of Commonwealth Supply Chain Advisors. Over his 20-year career, he has helped hundreds of companies reduce their distribution labor costs, improve space utilization, and meet their customer service objectives. He has formed supply chain consulting organizations for two different systems integration firms, and managed the supply chain execution practice at The AberdeenGroup, a leading technology analyst firm.



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