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Agile 101 - Three Practical Guidelines for Business Decisions
A humorous and practical approach to understanding why decisions are so complex
By: Michael Nir
Jun. 23, 2014 02:16 PM
In order to create the combination between top-down problem-decisions (waterfall like approaches)and local problem-decisions (Agile project approach) here are practical guidelines to pursue
Three practical complex decision-problems guidelines:
We describe in detail, each practical guideline, below.
Simple local rules
The local decision rules are the ones mostly used, they must be easy to follow, understandable, and unequivocal. Consider the warehouse forklift operator who is re- stocking raw material. If she needs to follow a complex decision protocol for placing newly arrived material in the warehouse, it would result in chaos.
Instead, we need to equip her with an easy to follow mechanism for stocking the warehouse.
One such mechanism is FIFO - First In First Out. This is also the rule, you're following when stocking your fridge with groceries, if you don't want dairy products to go sour.
Supermarkets also follow this rule when their organizing their product shelves. At least, they're supposed to follow this rule, otherwise they will have outdated products on display.
The modern big supermarkets actually stock fresh items from the back, ascertaining this way, that older items are pushed forward.
Sly consumers will then pick up dairy products from the back of the shelf if they want to make sure that it is the freshest available.
There is even an acronym that goes along with local rule simplicity which is: KISS - and stands for: keep it simple and straightforward.
The Japanese KANBAN approach which we've previously mentioned, implements an easy to follow rule of thumb.
It is: when you're operating a manufacturing machine, you should only produce when the physical container carrying a finished product in front of you, is empty. In practice this was actualized by using Kanban cards. Kanban is the Japanese word for card.
For manufacturing purposes it much easier for operators to follow this simple rule. However, ordinarily in production floors, operators follow a complex weekly/daily production plan that is very confusing. This is the opposite of simple.
Make your local decision-problem rules are simple
Strategic top down rules
The strategic top down rule which we select for our decision-problem has to constrain our decision space.
Consider for example a hospital's most expensive resource - the surgery room. Each such room has to be utilized as much as possible.
Reaching 100% utilization is not feasible - this can be proved using queuing theory; however 85%-90% utilization is desirable. The reason we require high utilization is for the pay back on the investment. The hospital invested money for the equipment in building and equipping the room and wishes to receive a return on the investment.
Hospitals' surgery rooms are generally a resource in shortage, hence there will always be patients requiring the room. It seems logical that the 85%-90% utilization will be easily achieved. This is not that case - the rooms are approximately 65% utilized in many cases - and it is driving the financial officers of hospitals crazy.
It drives them crazy almost to the point that they require ulcer treatment and have to wait in line for the surgical procedure - and yet the operation room is only 65% utilized.
The situation described of having lower utilization than expected and desired has to do with selecting an unsuitable top down problem-decision rule. The hospital schedules surgical procedures, utilizing the operation rooms, by using a monthly plan, as we've illustrated before, the top down plan fails because of many small changes.
What are these small changes and why do they occur?
In order to perform a surgical procedure in the operation room, the room has to be ready - i.e., cleaned, sterilized and with the proper equipment. The surgeon and his staff also have to be ready.
What happens if the surgeon and his staff are ready and waiting, however the room isn't prepped and cleaned?
The impact: we have very expensive employees (the physician, surgeon and others in the team) and a very expensive resource (the surgery room) as well as a prepped patient - all waiting for the room to be cleaned.
Wait a minute - this doesn't make sense you say! Didn't the top-down plan specify that maintenance personal have to be cleaning, equipping and readying the room?
The plan might have have designated and scheduled the cleaning to be performed, however the cleaning staff is currently working in another location and are unavailable for cleaning the specific room.
Crazy - we have two very expensive resources waiting for important yet cheaper staff.
Why aren't there enough cleaning staff?
Because the top down rule, that the ulcer stricken financial officer defined, is based on efficient planning and budgeting of resources. In this plan, it makes no logical sense hoarding on maintenance staff when we can fire them and save...
Thus, selecting the wrong top down planning, decision mechanism leads to an ineffective use of the hospital's expensive resources.
The depicted hospital scenario is quite common in many industries. Eli Goldratt, a physicist by education, claimed that we wrongly select the top down rules to manage our complex systems and to make decisions. Since the top down plan will fail, we won't be using the critical resources in our system optimally. He suggested an alternative top down rule which he presents in five books. The rule he devised is known as the theory of constraints, and in each book he applies it to different departments within a company. In each department the fundamental concept is to analyze the critical resource from the system perspective and utilize it optimally.
The theory of constraints top down problem-decision rule: always protect the most limited and expensive resource. Protect its time, utilization, and allocation.
In the hospital scenario, the top down rule would translate into constructing the plan around the surgery rooms and expert physicians, making sure that the cleaning staff is always ready before time, catering to the room.
The approach translates into a seemingly surplus of maintenance employees, at times wallowing around the corridors having an extra Latte, and contributing to the financial officer's ulcer. The alternative though is worse, unacceptable mediocre utilization of surgery rooms.
There have been many academic critics of Goldratt's approach. However, most demonstrated that his approach fails in extreme conditions. For most business purposes, Goldratt offers a straight forward, intuitive, top down constraining, problem-decision rule.
An alternative to Goldratt's rule in production environment and in project portfolio management can be to limit the overall time or products that are processed. In other words, limit the WIP - work in process.
How would that rule operate in project portfolio management?
The IT or software departments will only accept new project, when their total work in progress is below a certain threshold. The underlying mechanism is of Pull - new projects are pulled into a work status from a backlog waiting queue based on the total number of projects that are at present, concurrently managed.
The constant work in process is an easier to manage rule, however it is difficult to figure the threshold and to commit to it, without surrendering to requests from top management. More on that, later.
Select a resource constraining top down rule, instead of planning the entire system.
Visual problem presentation
‘If we don't see it it's not there'
We assess the world around us through our eyes.
‘A picture is worth 1000 words'
The fundamental principle is that we rather see a graphical representation rather than a list.
‘Seeing is believing'
Philosophically speaking visual presentations can lead sometimes to mistaken results, however more often they DO enable us to clearly see the overall problem.
Since we use our eyes as the tool to capture the world, it is crucial that we inspect and evaluate decision-problems in the same way.
Visual representations of decision-problems enable us to better grasp, the problem, assumptions, constraints, options and solutions.
Reflect for minutes on the traveling salesperson problem. It's much easier to explore a tangible map of 10, 15 or even 30 destinations and analyze possible routes, rather than assess the problem using a table or spreadsheet.
The same is true for production environments. It is easier to solve the complexity of production machine allocations, using visual signals such as Kanban boards and cards, rather than using a computer-generated paper output of production orders.
One of the challenges we've witnessed in managing multi projects in virtual global companies, is that we lacked the visual representation of the activities and projects allocated to resources and people.
Use any relevant tool to display the decision-problem visually.
For example: During a project at a petrochemical plant, we created a war room for the intense 4 months, construction stage. While we had a detailed Gantt chart with over 2000 entrees for specific activities of construction, it made more sense to create huge visual boards depicting daily tasks with resource and people allocated, to display overall allocations, possible collision points, impacts, deadlines, opportunities, and threats.
The strategic top-down rule has to be shown in the visual representation of the problem. Hence, it is not enough to portray the problem using a visual approach, it is also important to superimpose the strategic top-down rule on the visual presentation of the problem.
How can we illustrate the strategic top-down rule on the visual image?
Create a visual representation of the complex decision-problem. Use visual methods to illustrate the top-down strategic decision rule
Two more rules:
• Enforce consistency through publicity
Are presented in the best seller: D-side - practical decision making business Guide
You will also find there more about decision making, it is a a humoristic practical approach to understanding why decisions are so complex and what can be done about it
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