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Ideal Final Result or IFR, a breakthrough innovation concept

Minimal cost solution

Ideal final result

The concept of Ideal Final Result or IFR is one of the most important contributions of Altshuller, the father of innovation system TRIZ, towards systematic innovative problem solving.

By definition the IFR solution would have to achieve infinite Ideality,


$\text{Ideality} = \displaystyle\frac{\sum \text{Benefits}}{{\sum \text{Costs}} + {\sum \text{Harm}}}$


where you strive for Ideality to reach infinity in your IFR solution.

In ideal solution, sum of bad or harmful effects is zero while desired good effects or benefits are achieved. By definition, you need to achieve this solution at zero cost.

To be more explicit, the Ideal solution must pass the tests,

  • Eliminates the deficiencies and preserves the advantages of the original system
  • Does not introduce new disadvantages
  • Does not make the system costlier or more complicated.

You would notice that the IFR solution has to reach the Ideality at zero additional cost. This by far is the most astonishing characteristic of the IFR concept and at first thought seems to be impossible to achieve.

If you do not deviate from your IFR and analyze the definition, it would be clear to you that achieving the Ideality at zero additional cost can be achieved only if,

  • Free resources are used that are not easily visible, or
  • Relationships between some of the components of the system are changed so that the shortcomings are removed. This rearrangement must be simple and involve no cost.

To illustrate the concept let us take as first example the classic candy factory problem posed by Altshuller himself.

Case example 1: Candy making problem

Problem description

In a candy factory, small bottle shaped chocolate candy filled up with thick sugar syrup was produced. First the hollow chocolate bottles were produced and then the syrup was poured into each candy bottle. But as the syrup was thick the process of pouring in was slow. It was felt that productivity needs to be increased. This is a classic problem posed first by Altschuller.

Initial attempts to speed up the process of filling

Initial attempts of improvement to speed up filling up chocolate body with thick syrup were:

  • Heating up the syrup to make it thin for faster filling up, but it didn’t work as it melted the chocolate body and deformed it.
  • Alternatively, in blown injection molding method the pressurized syrup provided the propulsive force to shape the chocolate in a mould. But that increased cost considerably and violated the Ideality condition badly.

These were the conventional approaches to the solution. Failures of these prompted you to think fresh. It is clear now that faster filling in at zero cost is not possible.

Further analysis

Analyzing the product, you identify two components in it:

  • A bottle shaped chocolate body and,
  • A thick syrup filling inside the bottle body.

After a while you realize that the filling in idea has originated from the fact that the syrup is inside the bottle. What if we think the candy as,

An amount of thick syrup covered by a chocolate body coating?

The final state can very well be described by this view also. This new view of the final state would prompt you to think of a new possibility to explore,

Can we first form the syrup filling and then cover it by chocolate?

If we can achieve this easily, we might achieve the IFR.

What is the barrier to this approach? Obviously we didn’t think of this possibility first because the syrup filling is liquid. Can we easily solidify the liquid syrup?

Yes we can – just by cheap freezing. Let’s then mentally form a bottle shaped solid body of freezed syrup filling.

How to cover it by the solid chocolate? That’s not difficult. You knew chocolate melts and solidify easily. At this stage the pieces of the puzzle finally fall into their respective places.

Final solution of IFR

  • First freeze the syrup filling into a bottle shaped solid.
  • Now dip this solid syrup body (it would actually be the filling finally) into liquid chocolate to form a chocolate coating suitably.
  • Bringing the product to suitable temperature would solidify the chocolate with melted syrup inside it.


  • Unless you stuck to your target of achieving the IFR, you may not have thought of this innovative approach to solution at all. The ideality requirements forced you towards the IFR rejecting non-optimal solutions on the way. This is the reason for the IFR concept to be considered as a powerful psychological tool for innovative problem solving.
  • In IFR approach you must form your target IFR clearly and analyze it fully from various angles – remember we are talking about analyzing the final state. That’s where we find similarities between End State Analysis approach and IFR driven approach.
  • Two major inventive principles have been used in forming the Ideality solution – the Other way round inventive principle and the Change of state or parameter change principle (no. 13 and no. 35 in the list of 40 inventive principles respectively).

One of the important observations here is that the solution was not really achieved at zero cost – rather it was a solution using cheap and simple processes. Remodelling the manufacturing process should not be complex or costly. Nevertheless it would involve a cost.

That’s natural as being pragmatists we recognize that

We must form the ideal goal and always strive towards the ideal goal, but being ideal, the goal cannot ever be fully achieved.

Thus we restate the ideality test requirements of IFR solution simply as:

Desired solution at minimal cost.

How one should arrive at forming a clear idea of the desired solution in a real life situation is a complex process mainly driven by customer needs and reasoned analysis.

Many times, IFR solution is achieved by using free resources abundantly available in the environment but not easily visible. A second example should exemplify this path.

Case example 2: Eliminating traffic jams in a large city

For years you have faced interminably long traffic jams in almost all major junctions of your city. It is one of the largest cities in the country with least proportion of road surface. That’s the major reason behind the traffic bottlenecks.

Then one day while driving to your workplace when the driver takes an unusual route, you ask him, “What happened? We never used this route before!”

That day you first became aware of new regulations of driving in the city. Apparently, during first half of the day, cars can move only in north to south direction along some of the main roads and the traffic flow will change to the reverse direction during the latter half of the day.

The direction restriction had more complexity but in a few months people got used to it and you observed with quite a surprise that the traffic jams vanished as if magically.

Later you had learned that the architect of the good work was the new traffic chief who took up his charge recently.

Analysis of how the magical solution could have been achieved

Problem definition

Reduce or preferably eliminate the traffic jams in the main road junctions of the city especially during peak hours.

Initial problem analysis

Initial analysis revealed that,

  • the congestions occured especially during peak hours in the morning and in the evening
  • the offices were concentrated near the centre of the city towards which all traffic moved from the outskirts.

It was a tough problem and eluded an easy innovative solution at minimal cost till then.

Possible solutions – conventional

  • Build flyovers across the main road junctions selectively – it was costly, time-consuming and particularly difficult as the city is an old one with very little flexibility because of lack of space with buildings and other structures spilling over on to the roads.
  • Break up the office concentration and distribute the offices to additional spread-out centres – this again was a people sensitive, time consuming and costly solution.
  • Build an intra-city fast moving railway system to reduce the road traffic itself – this was definitely the costliest and most time consuming process.

The decision maker, being a believer in minimal cost solution in quickest time, rejected all the conventional solutions for the time being and analyzed the situation further.

Further analysis revealed

  • The city roads followed a system of roads along two perpendicular axes.
  • The roads along each axis were parallel to each other.
  • Any road had an alternate route parallel to it.
  • Traffic moved both way along all the roads, and
  • The roads were not very wide with many lanes.

The decision maker identified the both way traffic along relatively narrow roads as the major cause behind slowing down of the traffic and eventual congestion.

Even though the traffic from the office centre towards the outskirts was much lighter than the reverse traffic during the morning, still it occupied half of the road width capacity.

Why not exchange this relatively sparse opposite direction traffic with the office going morning traffic on a parallel smaller road and declare both the roads to be one way only? This would automatically increase the effective use of road surface significantly, as the office going heavy traffic would get the full width road to travel compared to the earlier half width allocation!

This was the breakthrough idea.

Technically we know it to be the load balancing technique. Later we routinely used this powerful technique to balance loads of highly congested communication routes to loads on large computer servers.

Use of free resources

While travelling along the heavily congested roads where traffic moved both way, it was not easy to visualize that half of the road width was sparsely used while the other half was heavily congested and with little bit of ingenuity this sparsely used half could be made free for use by the resource hungry traffic on the other half.

But this was not the only free resource that was used. The clinching one way rule needed to be switched to reverse direction during the evening when traffic density also reversed. This is the important technique of using time dimension. The main principle was to be implemented spread over time dimension also.

Implementation of the solution

Having an innovative idea is not enough. You must be able to implement it in quick time and at minimal cost. It needed no less than quite a bit of complex computer modelling and analysis before the system could be implemented successfully.

Our traffic chief met these requirements admirably and we had our congestion free roads at last.

Sum up

You would observe that all along we followed an approach of deductive reasoning coupled with a resolve that we must achieve the solution at minimal cost.

We consider this concept of minimal cost solution as the biggest contribution of IFR. This always keeps the decision makers and analysts under pressure to explore new ways rather than accept conventional costly solutions.

Solving a tough real life problem is a complex process. After long and many analytical stages you might reach a point not very far away from the desired minimal cost solution. But jumping across this final gap, as we call it, is never easy. You need a breakthrough idea to break down this final barrier. Usually we call this as an innovative idea.

Assured and systematic real life problem solving needs breakthrough ideas invariably and thus innovation forms an essential and inseparable part of it.