An assumption is a supposition, something taken for granted or accepted as true without proof. As such, an assumption can be interpreted to be an unsubstantiated choice, and hence a [decision]. 

Assumptions — choices made in absence of conclusive information — are best made by an expert, as the expert’s expertise and ability to perceive information (even when it is not fully perceived) will maximally reduce the associated risk. As each assumption carries a risk the assumption is to be considered for risk management.

Best Value Approach

The Best Value Approach (BVA) includes a procurement model, a risk management model, and a project management model. It was first introduced in 1991 by Dr. Dean Kashiwagi as the Performance Based Procurement System. It was modified to the Best Value Performance Information Procurement System (BV PIPS) and has also been called the Best Value Procurement (BVP). The Best Value Approach replaces the owner/buyer’s decision making and Management, Direct and Control (MDC) with the utilisation of expertise. It is an approach which transfers the control of the project to the best value expert vendor.

Decision Free Solutions (DFS) is congruous with BVA. DFS is based on the same licensed technologies of Information Measurement Theory (IMT) and the Kashiwagi Solution Model (KSM), both developed by Dr. Dean Kashiwagi. DFS differs from BVA in that it provides a generic, systemic approach that can be applied in all fields (and is thus not ‘wedded’ to procurement), and that it places a much greater emphasis on the importance of a definition of the aim that is to be achieved.


See Best Value Approach


The definition of “decision” as used in Decision Free Solutions is a choice not substantiated to contribute to achieving a desired outcome. For short: an unsubstantiated choice.

The DFS article “On Decision Making” explains everything you ever need to know about what a decision is and why decision making is to be avoided. You find the article here.


Within [Decision Free Solutions] a ‘decision’ is defined as ‘a choice not substantiated to contribute to achieving an aim’.

This directly implies two things. One, there is something to choose between – there is an alternative. Two, a decision requires knowledge on the aim – without an aim a choice will simply remain a choice.

Within Decision Free Solutions ‘a decision increases [risk]’ when there is both an aim and an alternative. A decision increases the risk the aim will not be achieved.

A decision is not to be confused with managerial activities such as ‘approving’, ‘consenting to’,’providing permission’ etc. etc. The latter are all done when, to the owner/managers/board members, a transparent substantiation has been provided as to how the proposal/results/next steps contribute to achieving the aim.

Decision Free expert

The Decision Free expert is able to identify, to avoid, or to mitigate the effects of all types of decision making.

The Decision Free expert has in common with the Best Value expert that the principles of IMT/KSM are fully understood. By observation some A+ certified Best Value experts may also rightly be considered Decision Free experts. By observation some others are not.

No certification scheme to become a Decision Free experts exists. You may be one, you may become one, or you will never be one. Everything is possible.

Decision Free Leader

Within [Decision Free Solutions] a role is defined labelled the ‘Decision Free Leader’ (DFL). The one who takes on the DFL-role has the following responsibilities (listed per [DICE]-step):

  • Definition:
    • Identify as many [initial conditions] as possible (especially those pertaining to the ‘system’ to which the expert might not have access)
    • Ensure the aim is unambiguous and understood the same by all involved
  • Identification: Ensure all types of [decision making] are avoided in identifying the [expert] to achieve the aim
  • Clarification: Ensure all types of decision making are avoided in the expert explaining the plan and how progress will be communicated
  • Execution: Ensure the expert frequently and periodically communicates the status of the plan, deviations to the plan, and how the deviations are going to be resolved

The responsibilities of the DFL-role can be taken on by an existing role in a particular field, such as e.g. the role of project leader, procurement officer, or ‘birthing partner’. The pre-requisite is that they are they able to avoid all types of decision making.

Decision Free Solutions

‘Decision Free Solutions’ (DFS) is a generic, systemic approach to achieve unambiguous aims with minimal risk by avoiding decision making.

Applying Decision Free Solutions in whatever field will result in the optimal usage of available and relevant expertise, will unlock potential and spur on creativity, will minimise risk and the use of resources, and will maximise benefits, including the achievement of the aim. 

Applying DFS will benefit those who have an aim, and those who have expertise. In other words, everyone.

Decision making

[Decision Free Solutions] minimizes [risk] by avoiding decision making. Decisions are unsubstantiated choices. As [experts] are able to substantiate their choices, only [non-experts] make [decisions].

Decision Free Solutions avoids three types of ‘decision making’:

  • the making of a choice without substantiating how it will contribute to achieving an aim (i.e. ‘decision making’)
  • past decision making (e.g. protocols, guidelines)
  • precursors to decision making (i.e. [thinking])

The four steps of [Decision Free Solutions]:

  • D – Definition: The definition step is the step where the aim is to be defined. This is the single most important step: the expert will be identified based on the aim, and the aim is what the identified expert will achieve.
  • I – Identification: In the Identification step the expert best able to achieve the aims is to be identified by the [non-expert] (the ‘owner’ of the aim).
  • C – Clarification: In the Clarification step the identified expert will explain how (with which tools, scope, performances etc.) he will achieve the aim. The expert will define concrete goals or targets, and make it transparent to the non-expert how these will result in achieving the aim.
  • E – Execution: In the Execution step the expert executes the plan. To avoid [decision making] by the non-expert (e.g. in the form of [MDC]) the expert keeps the non-expert informed on the status of plan-execution by periodically reporting on any deviations to the plan and or risk mitigation plan which might affect the achieving of the aim.
Dominant information

Dominant information is information that can be understood by almost everyone due to its simplicity, and it does not require technical detailed knowledge that only a few may possess. Dominant information can be described as a “no brainer”, “common sense”, “easy to understand”, or where there is no requirement to use one’s unique experience to predict the next state or future action. [Source: 2016 Information Measurement Theory – with the “Kashiwagi Story”; Dean T. Kashiwagi]

The term ‘dominant information’ has been proposed and defined by [Dr. Dean Kashiwagi].


Everything that takes time to happen is called an ‘event’. Events have ‘initial conditions’, ‘natural laws’ that work on them, and ‘final conditions’ (outcome of an event).

An expert perceives the initial conditions of an event, knows the natural laws that apply to the event, and thus also knows the final conditions of an event. An expert can see the future.

A ‘project’ is an example of an event. So is ‘pregnancy’. So is basically everything.

Event condition

Each [event] has unique conditions at any moment of the event. Anything that is relevant to uniquely define the event is called a condition. These “conditions” include e.g. people (with their talents,  thinking, traditions and practices), the physical environment, the law, available resources, the time, the location, etc. etc. 

Event model

The Event model (see Figure), as defined by [Dean Kashiwagi], states that, at any point in time, an event:

  • Has unique “Event conditions” (where “conditions” include e.g. people (with their talents,  thinking, traditions and practices), the physical environment, the law, resources, etc.)
  • Is governed by unchanging “Universal Rules” which regulate how the event conditions change using a predictable logic. Universal rules always exist and never change and apply to all the event conditions (e.g. the laws of physics, but also the predictable logic pertaining to human emotions, intellect and behaviour).
  • Has a unique “Outcome”, which is simply the result of the universal rules impacting on the event’s conditions over the event’s duration.


Within Decision Free Solutions an ‘expert’ makes no decisions. This implies that an expert is always always able to substantiate that what he is doing (the choices he makes) contributes to achieving the aim.

In terms used by Information Measurement Theory (IMT) an ‘expert’ is aware of all initial conditions at the beginning of an event, and knows all ‘natural laws’ that will affect the event. Therefore an expert will know the outcome of an event. Phrased differently: an expert ‘can look into the future’.

A simple example is when you hold a bottle at the cap, and then let go. An ‘expert’ can tell you what will happen (he can look into the future!). He sees all the initial conditions (you holding the bottle, standing on planet Earth). He knows all ‘natural laws’ that will affect the event (law of gravity). As a result he will be able to tell you that when you let go of the bottle, the bottle will fall because of gravity. There is no decision making.


Experts generally have expertise, but those who have expertise are not necessarily experts.

In Decision Free Solutions an expert is someone who doesn’t make decisions. There are many experts, and in DFS the second step of DICE (Identification) is used to identify the expert who is the expert in achieving the aim.

Everybody can obtain expertise by working long and hard at something. It doesn’t mean that decision making is avoided by them.

External risk

External risks are [risks] which lie outside of the control of the [expert].

Generally the expert is still best positioned to both identify, estimate the impact of, and mitigate these risks. Even though an expert may be actively managing external risks, he/she can never totally rule them out as they are outside of his/her control.

Information Measurement Theory

Information Measurement Theory (IMT, see pdf) has been developed by Dr. Dean Kashiwagi from the 1980’s, and was first published in 1991 at Arizona State University as the structure for optimising the effectiveness of information by creating “easy to understand” information environments.

IMT, and the Kashiwagi Solution Model (KSM) which uses IMT’s principles to show the relationship between different characteristics, are the foundation of both the Best Value Approach, and Decision Free Solutions (which is congruous with the Best Value Approach).

Initial Conditions

From Information Measurement Theory: ‘At any one location, there is a unique set of conditions. Conditions include people, their thinking, traditions and practices, the physical environment, resources, and the level of technology in the environment. Every set of conditions is connected with a location and time which are unique.’

At the beginning of an [event] (anything that takes time, like a project) there are initial conditions. Decision Free Solutions emphasises the importance of providing [experts] with as much information as possible on what these initial conditions are (in addition to the expert’s ability to perceive many initial conditions themselves already). The more of the initial conditions the expert is aware of, the smaller the risk the expert will not achieve the aim.

Internal risk

Internal risk is the risk that an organisation, team or individual has when executing activities to achieve the desired outcome. Internal risk consists out of identified and unidentified decisions.

By definition an expert organisation, team or individual  — perceiving all information in his/her field of expertise — has no internal risk as all decision making is avoided.

Kashiwagi Solution Model

The Kashiwagi Solution Model (KSM) uses the principles of Information Measurement Theory (IMT) to show the relationship between different characteristics.

Kashiwagi, Dr. Dean

Dr. Dean Kashiwagi, PhD, PE, is the creator of the Best Value Performance Information Procurement System (PIPS) – also known as the Best Value Approach – and the deductive logic based Information Measurement Theory which includes the Kashiwagi Solution Model.

In 1994 Dean Kashiwagi started the Performance Based Studies Research Group (PBSRG) at Arizona State University, which has been developing tools and processes to improve the procurement and delivery of projects and services, as well as the measurement of internal operations and personnel.

Manageable risk

A “manageable risk” is a risk that has been identified.

Management, Direction and Control

‘Management, Direction and Control’, or ‘MDC’, is a catchphrase for what a [non-expert] does to fight the feeling of unease of not understanding, not being in control, not knowing what is happening. MDC is what the non-expert imposes on the [expert]. The effect is that the expert cannot fully utilise his expertise, and it thus increases the [risk] the aim will not be achieved.

Examples of MDC are managers to tell project leaders to achieve something by a certain time while restricting the use of certain resources, telling experts to abide by company policies or use certain protocols, by requesting experts to provide detailed reports on executed activities.

MDC is a manifestation of various types of [decision making]: decisions (choices not substantiated to contribute to achieve the aim), past decision making (e.g. policies and protocols), and precursors to decision making (i.e. [thinking]).

MDC reduces the utilisation of expertise and increases risk. It is a waste of resources.


See [Management, Direction and Control].

Natural laws

“Natural laws” are the equivalent of [universal rules] as used in [Best Value Approach].


The non-expert is the ‘owner of the aim’. The owner of the aim is the ‘non-expert’ in the sense that he is looking for a certain [expertise] (to achieve the aim) he is not in possession of. If he would be the [expert] in relation to the aim, he would achieve the aim himself.

The owner of the aim (the non-expert) is the one who makes [decisions], as the non-expert is not able to substantiate how a choice he makes is to contribute to achieving the aim (the definition of a decision). The expert can substantiate all his choices, and thus doesn’t make decisions.

It shall be emphasised that the ‘non-expert’ generally is in the possession of expertise which often may be relevant to achieving the aim. E.g., an organisation may want to procure a machine to achieve an aim, and also have many engineers on board familiar with the technology. The expert-vendor (providing the new machine) may also use this available expertise as part of its plan.

Outcome risk

Outcome risk is the risk that an event will fail to achieve the desired outcome. See also [Resource-Outcome model].


A “perceiver” is an observer who is interested (curious) in the [universal rule] that lead to the new [information] what was just observed.

Not all observers are interested in this. Not all observers, hence, are perceivers.


“Resources” are those aspects of the [event conditions] over which one (e.g. an individual, an organisation) has some control.

Organisations use resources to achieve outcomes.

Resource risk

Resource risk is the risk of spending resources over and beyond the necessary minimal resources to achieve the desired outcome.


The definition of risk is the following: Risk is the effect lack of information has on achieving a desired outcome.


  • information refers to the event conditions and the universal rules impacting upon them and is always simply there (“lack of information” thus means that some information hasn’t been perceived)
  • risk can be expressed in terms of Outcome risk and Resource risk
  • where resources are those aspects of the event conditions one has a certain amount of control over.

The following is to be noted:

  • The provided definition is very similar to the one defined by ISO 31000 effect of uncertainty on objectives”, whereby this uncertainty both includes events (which may or may not happen) and uncertainties caused by ambiguity or a lack of information. Instead of “objectives” the term “desired outcome” is used, and “uncertainty” is substituted with “lack of information” (albeit with a different, broader definition).
  • The differences with the ISO 31000 definition may seem small, they are still important enough to point out:
    • When risk is said to be caused by “lack of information” this doesn’t mean some information is not available but rather that information is not fully perceived (e.g. because of a lack of expertise).
    • Risk is thus not merely the result of uncertainty with respect to knowledge on “conditions” (events which may or may not take place and or “information” in the classical sense of “knowledge or facts learned”), but also with respect to uncertainty as to what will happen to these conditions. In other words, even when there is no uncertainty concerning events taking place, everything is non-ambiguous and all the information in the classical sense is readily available, then there is still plenty of risk to go around if there is no or little understanding as to how conditions are bound to change in time (and how these can be made to contribute to achieving the desired outcome).
    • Finally, the way risk is defined by ISO 31000 — where “effects” on objectives can both be positive and negative — the word “risk” may thus refer to positive consequences of uncertainty, as well as negative ones. This does not make sense when talking about “lack of information”. There is no positive effect to be had because of lacking information. Opportunities may still arise, but this will then only mean that information has been perceived which may reduce resource risk and or outcome risk (or allow for additional or more desirable outcomes).



See also Outcome risk, Resource risk, External risk, Internal risk, Manageable risk, Unmanageable risk.

Risk Management

“Risk Management” is the identification, assessment, and prioritisation of risks, followed by the use of resources to minimise, monitor, and control the probability and or impact of risks occurring.

The objective of Risk Management is to both minimise the likelihood of identified risks occurring, as well as to minimise the impact of those occurring risks on achieving a particular aim.

Risk management is integral to the approach of Decision Free Solutions.


Within Decision Free Solutions ‘thinking’ is to be avoided as it is a ‘precursor to decision making’. [Decision making] is something non-experts do.

The context for this statement (that ‘thinking’ is to be avoided) is that [experts] must always be transparent (i.e. use [dominant information]) why they are doing what they are doing, and how this is to contribute to achieving the aim. It is the expert who has to avoid the situation whereby something remains unclear or puzzling to the non-expert, resulting in the non-expert to think.

When the non-expert starts to think (as a result of something being unclear to him), he is more likely to want to try to control the situation (by employing [MDC]), or make a [decision]. In both instances the risk is increased the aim will not be achieved.

If the expert is not able to communicate in such a way the non-expert doesn’t have to think, then the non-expert is allowed to think the expert might not be an expert.

Thinking is what the expert (to be) does in building up his expertise, using observations to determine links between effects and causes ([initial conditions]).


[Decision Free Solutions] is an approach to avoid all types of [decision making] in achieving an aim. [Decisions] are made by [non-experts]. To avoid decision making thus:

    1. An expert must be identified able to achieve the aim,
    2. The identified expert must avoid decision making by the non-expert.

Five principles are proposed which are to be observed at all times in order to avoid decision making. These principles, within DFS collectively labelled as TONNNO, are:

      • Transparency
      • Objectivity
      • No details
      • No requirements
      • No relationship

There are two types of trust:

  1. The type of ‘trust’ where you are asked to have confidence in something or someone without substantiation
  2. The type of ‘trust’ which is an extrapolation of demonstrated performances

Within Decision Free Solutions the first type of Trust is not allowed. It is a decision.

Universal rules

“Universal rules” is a concept as used in the [Event model] as proposed by Dr. D. Kashiwagi (who uses the term “Natural laws”). Universal rules regulate how the [event conditions] change using a predictable logic.

“Universal rules” always exist and never change, and apply to everything (e.g. people, organisations, environment). These rules include the laws of physics as well as anything else which defines the change of a physical environment over time.

Given the right conditions, if you sow something, it is a universal rule it will grow. Over time food will perish. If somebody hasn’t changed his/her abusive behaviour for twenty years, then in absence of any relevant change in the conditions this behaviour will persist. If a politician skilled at manoeuvring him or herself to gain control or power becomes the chairman of the board of directors, then the focus of strategy will shift from the long to the short term. If you appoint cabinet positions based on loyalty rather than merit, chaos will ensue. If a company lacks discipline and is run by a first-class jerk this will have an impact on the quality of provided solutions.

See also [Information].

Unmanageable risk

Unmanageable risks are risks which are the result of unidentified decisions. These risks cannot be actively managed. Organisations may blunt the impact such unmanageable risks have when occurring by managing, directing and controlling all of the organisation’s activities.


From Robert Pirsig’s “Lila; An inquiry into morals” (1991), chapter 9 :

“The brujo’s values were in conflict with the tribe at least partly because he had learned to value some of the ways of the new neighbors and they had not. He was a precursor of deep cultural change. A tribe can change its values only person by person and someone has to be first. Whoever is first obviously is going to be in conflict with everybody else. He didn’t have to change his ways to conform to the culture only because the culture was changing its ways to conform to him. And that is what made him seem like such a leader. Probably he wasn’t telling anyone to do this or to do that so much as he was just being himself. He may never have seen his struggle as anything but a personal one. But because the culture was in transition many people saw this brujo’s ways to be of higher Quality than those of the old priests and tried to become more like him. In this Dynamic sense the brujo was good because he saw the new source of good and evil before the other members of this tribe did.”

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