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Worthwhile Prioritization

Prioritizing work is quite the topic. Most of the time, work first gets prioritized when it is already in the system and, quite frequently, that leads to perpetual reprioritization. The criteria for reprioritization usually remain unclear, and they often only deal with the fear of possible consequences. However, assuming the priority is already classified with a logical approach before the work enters the system: Which approach should be used for it?

An economical approach makes the most sense. What I hear in the stories and questions of participants in my trainings is that, in many companies, there are indeed the beginnings of an economic approach to work prioritization. These approaches, however, are often not completely thought out. Value, or “business value”, is the prioritization tool used in such cases. It’s a great idea, but leads me immediately to the question: “How are you using it?” The answer to this question is usually: “Work with the highest value comes first, and those with lower value are implemented later.” Sounds logical, doesn’t it? Yes, as long as you don’t consider the amount of time needed to implement the work. When work X generates high value, and needs four weeks to be completed, while work Y can generate the same value in two weeks, which one gets implemented first? It probably makes more sense to complete work Y first because, stated simply, it brings money in faster than X. When we use value as a prioritization attribute, it should always be considered in relation to the implementation time of the individual work.

2017-01-Blog-KAP-BKK - 2Let’s go one step further: Is value a static quantity? Chocolate Santa Clauses do not sell well at Easter—in other words, the value of work can change over time. Or it can, subject to seasonal influences, only reach its full-potential at a specific time or within a specific timeframe. The change in value over time should absolutely be taken into account in a prioritization process. Now we have all the ingredients for prioritization based on Cost of Delay:

  • How high is the value of the individual work?
  • How long does it take to implement the individual work?
  • How does the value of the work change over time?

Cost of Delay are those costs, as well as economic effects over time, which occur when the completion of work is delayed or doesn’t respond quickly enough to the market. Cost of Delay includes not only actual costs incurred, but also all lost revenues which are incurred, regardless if a project is worked on or not.  To be able to work on orders in an economically useful sequence, the Cost of Delay is quantified by visualizing it in concrete monetary amounts. Cost of Delay is always drawn from the value-generating elements (deliverable units), that give the customer a concrete benefit. It is a function of the value generated by an activity, and its urgency.

I recommend initially using Cost of Delay when the Kanban system is being designed with deeper understanding. What do I mean by this? The people assessing the individual implementation options allow other criteria to be used in their valuations, since there are several risks to consider. However, as long as you do not have other information or measurements available in the Kanban system, it is always better to work with the cost of delay instead of slipping back into the old prioritization game.

lkna klaus

Don’t Optimize Teams

The title of my talk at the Lean Kanban North America 2016 conference carried a quite direct message: Don’t optimize teams! 

One of the biggest mistakes I see in Agile transformations (gee, I hate this term) is that organizations “install” Agile methods on teams and then they think agility of their organization improved. Unfortunately, that is totally not working!! I mean, it’s a perfect approach if you are a consulting company. You really can sell a lot of billable days because all these teams need training and coaching. However, if you are the company that’s striving for agility it’s no good advice. In most of the cases the company’s performance will go down and this with very high consulting costs. But just watch the video:

Unfortunately, nobody told me that the cameraperson glued his camera to a fixed position. That’s why I disappear behind the slides from time to time :-/

I loved the energy of the audience in the room during my session. I really had a lot of fun on stage and many very deep conversations after the talk. And there was also quite some Twitter coverage during my session. Here some highlights:

The economy of waiting times: Cost of delay

CoD

The article “The effects of increasing capacity” is all about companies increasing capacity without paving the way for such an undertaking. What is even more dramatic is the fact that most companies lack a real feeling for the economic effects increased waiting times can have. It is, therefore, not clear what cost of delay may incur when work is finished later. How about an example?

A sports article manufacturer lost approximately 300,000 Euro per year because bookkeeping was not able to make use of discount periods. By the time the invoice made it from the various departments to the people who can authorize payment, the discount periods had long expired and the full amount was then due. This was quite a shock after everything had been calculated and one could see how much money could have been saved if the periods would have been taken into consideration. The path of the invoice through the company was laid out and it quickly became clear that several handoff points were completely redundant. The people involved were given more competences in order to make their own decisions. Thus the “cycle time” for invoices within the company was reduced from 20 days to just three and each discount period could be used to its fullest advantage. This company was able to save an average of 5,800 Euro a week just by understanding and optimizing procedures without having to make anyone work any faster or employing more workers in order to get invoices to their goal. This is the economy of waiting times.

We can of course argue that the sports article manufacturer had a pretty easy job with quantifying the cost of delay. True, in this example the quantification was not exactly rocket science. But, just because cost of delay might be difficult to quantify, does not mean that the easier choice of ignoring them will supply better results. The opposite is true! As long as a company does not have a feeling for how much money is lost on waiting or delayed market entry, then that company will continue to make the wrong  decisions what to work on next during queue replenishment. Time is an economic component, or to quote Don Reinertsen: “While you may ignore economics, it won’t ignore you.”

Of course, there are many other risk criteria which influence prioritization decisions and I do not want to say that the quantification of the cost of delay is the all-singing all-dancing method that will help to always make the right decisions. However, understanding the cost of delay is, as far as my work within companies is concerned, a good starting point for helping all parties involved to get a feeling for the idea that classic prioritization creates more problems than it solves.

Understanding cost of delay helps to go from subjective randomness to economic rationality and thus shift the goals of the company back into focus. Because the cost of delay brings a common language – the value of a job defined in Euro – into discussion, comparability between individual alternatives is made possible.

For me personally, it is crucial that waiting times, which make up the majority of the cycle time, finally get a price tag through cost of delay. In some cases, the longer the wait during processing, the smaller the possibility becomes to tap into the fullest value of a job and the more costs incur. I have often seen some of my training participants gasping after they have calculated their cost of delay and initiated improvements for their projects for the first time. Suddenly it becomes clear that people do not need to work faster in order to have a competitive time-to-market. In 1993, W. Edwards Deming was quoted as having said “A bad system will beat a good person every time” during a seminar in Phoenix, and he was quite right. Let us not work on breeding high performance employees, but rather find a way to make their work easier. When it becomes clear how much handoffs, runarounds and unnecessary processes cost for all parties, then this will quite often lead to discussions on improvement. This is exactly the reason why I try to establish quantifying cost of delay as the first tool for prioritization within a company.

tapwater

The effects of increasing capacity

In many businesses with well-filled order books, I often come into contact with purely capacity oriented thinking. There is so much demand that it can neither be met with the current pool of qualified employees nor the amount of material resources at hand. The solution seems to be perfectly clear: increase capacity. There is the notion that capacity is something like a tap which can be turned on and off, and the problem is solved – this just happens to be the business model of temporary work agencies as well as some consulting firms. Unfortunately, things are not that easy and especially not in knowledge work.

The building up of capacity is indeed a crucial investment in the future which definitely has a positive effect, but this effect only takes hold much further down the line. Constantly increasing capacity on a short-term basis due to shortages is often accompanied by effects that are not intuitive and are thus often ignored: Sooner or later, businesses find themselves in the same situation again even though they have increased capacity. The whole situation of having more projects in progress than capacity and not being able to keep to project deadlines starts all over again. Or as Don Reinertsen und Preston Smith put it: „If we add more resources, sooner or later we will be back in the same situation with more projects than we have the resources to handle, and we will be diluting our effort and delaying projects again.“ The problem is that more work is being started than can be finished – the work within the system is not really limited.

There are two crucial aspects when considering how additional capacity will affect a work system: Throughput and Lead time. The throughput is the amount of work done within a time period. The more throughput found within a work system, the more one can sell – the throughput is thus an economical aspect. The lead time, on the other hand, tells us how quickly one job is completed between two measured points. Time-to-market describes the lead time when measured from idea to completion. Now, what happens when capacity is increased within a work system, for example, by hiring additional employees?

Quite probably, the aspect of performance will paint a rather ambiguous picture. Initially, throughput will increase because the additional employees will be able to complete more orders. But: the lead time will also increase – the work system will become slower and the customers will wait longer for their products. There are two reasons for this:

  1. Initial phase: Each new employee needs some time until he is somewhat familiar with the procedures and processes of the company he is new to and until he has familiarized himself with a product or project.
  2. Friction losses: If more employees are added to a work system, then the complexity increases as well because the amount of coordination also increases. Often additional capacity goes hand in hand with more focused specialization which, in turn, increases the number of handoffs.

 

Friction loss especially influences the lead time. With the increasing of capacity, one tries to optimize active work. From my own personal experience, I can say that active work only makes up about 2 to 20 percent of the actual lead time. The lead time is made up mostly of waiting times which occur during the handoffs to the individuals involved in the work.

An example: Let us assume that the lead time of a job is 100 days. Now, let us assume that the active work time is approx. 20 percent. Within the graphic below, we see how this active work time is distributed over the entire lead time. Again and again people have to wait for suppliers, information is missing or there is simply no more room in the input queue of the next department responsible and so on.

active vs wait 1

In a condensed form, the following bar expresses just how small the active work portion really is.

active vs wait 2

Again, let us assume we are in the fortunate situation that customers are ordering from us like crazy and, for this reason, we have to increase our capacity by 100 percent for this project – twice as many employees are now working for this project. Even if there were absolutely no friction losses due to the additional complexity and the new employees are able to go straight to work without any limitations, the lead time will only be reduced by a maximum of ten percent even though the work time has been cut in half. This effect could be graphically illustrated like as follows:

active vs wait 3

This minus of 10 percent, however, only represents exactly the case that will never happen: the best case. The next figure illustrates the normal case: Work time is cut in half, but the lead time increases due to processes becoming more complex and because coordination efforts increase. Here, the only question is: How high is the increase to the lead time?

active vs wait 5

 

This game can only be played to a certain extent. At some point, the lead time has increased so much through continuously adding capacities that it takes forever until work is completed. Guess who is not going to be happy about this: the customer. From his perspective, it is the lead time that counts. This is the dilemma in which many large companies find themselves when they continuously increase capacity: More throughput means more income, but you can easily lose sight of the lead time itself. This is exactly what should not happen, when you are looking to optimize your position in the market.

The problem is:

  • In most businesses, it is not clear what is being worked on from the portfolio to the team level.
  • More work is being started than can be finished. Thus, the system expresses a starting and not a finishing behavior.
  • Furthermore, there is no feeling for what is active and inactive work.
  • In the sense of optimization, the focus is always on active work – efficiency -, but people seldom work on optimizing the waiting time.

If someone only increases capacity within an environment, that person sub-optimizes his time-to-market.

What could be a solution?

  • You need effective work control above and beyond the boundaries of the team – Kanban on Flight Level 3 or 4 can help.
  • The work within the system must be limited and the system must express a finishing behavior. “Stop starting, start finishing” has to be the motto.
  • Inactive work and waiting times have to be made apparent.
  • The economy of waiting times must be understood so that not only the active but also the inactive work is optimized.