Fitness method to evaluate product launches

Marketing & Management

The launch of new products for any company constitutes a crucial economic effort, and an associated risk, which badly calculated, can greatly affect the competitive position of the company.

In the different brainstorming of the decision makers, different visions arise regarding the opportunity to turn an idea into a new product launch.

Is there the possibility of evaluating those ideas, to keep the one that has the greatest probability of success, when developed into a product / service?

Yes, it is about the measurement of entrepreneurial Aptitude: which is to evaluate the compatibility of the behavior of the different functional areas of the company in relation to the ideas that are decided to select.

In this sense, a “compatibility matrix” is prepared for each area, in which the following factors intervene:

• Variables that are part of the process of each area

• A priori qualification of the behavior of each variable

• Probability corresponding to the behavior of each variable

• Expected value of the behavior of each variable

• Total expected value of the area

Practical example: oil and derivatives case

Suppose that company "X" has the following ideas as alternatives for introducing new products:

A: Tires

B: Plastic coatings for upholstery and decoration

• Commercialization Area:

"Alternative Compatibility Matrix A"

Marketing Variables	VERY GOOD (10)	OKAY (8)	REGULAR (6)	BAD (4)	Value Expected
P	GO	P	GO	P	GO	P	GO
Product	0.9	9	0.1	0.8	-	-	-	-	9.8
Price	0.7	7	0.2	1.6	0.1	0.6	-	-	9.2
Distribution channels	0.8	8	0.1	0.8	0.1	0.6	-	-	9.4
Advertising	0.5	5	0.3	2.4	0.1	0.6	0.1	0.4	8.4
Sale promotion	0.9	9	0.1	0.8	-	-	-	-	9.8
Sales force	0.4	4	0.3	2.4	0.1	0.6	0.2	0.8	7.8

Total 54.4

As can be seen in the preceding matrix, we have evaluated all the controllable factors of the commercialization area. Conventionally we have quantified the ratings on a descending scale of 2 by 2 from 10 to 4 points and we have assigned probability values ​​(P) to the eventualities that each of the factors had one of the aforementioned ratings. The Expected Value arises from multiplying the Rating by the Probability (P). Ex: Product:

VE = 10 * 0.9 = 9

Expected Value = Sum of VE = 9 + 0.8 = 9.8

The values ​​of the probabilities are assigned on the basis of:

• Marketing investigations carried out

• Informed judgments by those responsible for the area about the behavior of each factor with relation to alternative project (tires)

• Historical data available

Notes:

1. The probabilities of a variable in relation to the grades are dependent events (the sum must give 1)

2. The probabilities of a variable in relation to the others are exclusive events (the sum is greater than 1)

In our example, alternative A, yielded a value of 54.4 points out of an ideal total of 60 points (assuming that all the marketing variables had obtained 10 points each).

This means that the suitability or probable behavior of the commercialization area in

relation to alternative A (Tires) will be 90% efficient.

E = RC / CIT; Ex.: 54.4 / 60 = 0.9

E: Efficiency; RC Result of compatibility; CIT: Total ideal compatibility

"Alternative Compatibility Matrix B"

Marketing Variables	VERY GOOD (10)	OKAY (8)	REGULAR (6)	BAD (4)	Value Expected
P	GO	P	GO	P	GO	P	GO
Product	0.8	8	0.1	0.8	0.1	0.6	-	-	9.4
Price	0.9	9	0.1	0.8	-	-	-	-	9.8
Distribution channels	0.3	3	0.4	3.2	0.2	1.2	0.1	0.4	7.8
Advertising	0.5	two	0.3	2.4	0.5	3	-	-	7.4
Sale promotion	-	-	0.5	4	0.3	1.8	0.2	0.8	6.6
Sales force	0.3	3	0.5	4	0.2	1.2	-	-	8.2

Total 49.2

E (B) = RC / CIT; Eg: 49.2 / 60 = 0.82

In relation to alternative B (Plastic coverings for upholstery and decoration) it will be 82% efficient.

Comparing the behavior of the commercialization area for both alternatives results:

Alternatives	Matrix values	Relative efficiency
Covers (a)	54.4	90%
Coatings (b)	49.2	82%

If we apply the same procedure, we will have a matrix for each of the company's areas: finance; production; administration; human Resources.

Assuming that each of the matrices returned the following values:

AREAS	COVERS (A) Relative efficiency	COATINGS (B) Relative efficiency
COMMERCIALIZATION	90%	94%
PRODUCTION	93%	94%
FINANCE	87%	80%
ADMINISTRATION	95%	93%
HUMAN RESOURCES	92%	90%
AVERAGE	91.4%	90%

To be more precise, it is appropriate to weight the gravitation of each area within the development of each alternative, for which it is necessary to multiply the values ​​expressed in the previous table by a weighting factor. Suppose that for this company it is:

Areas	Weighting factor
Commercialization	4
Production	two
Finance	two
Administration	one
Human Resources	one
Total	10

The final evaluation of the behavior of the company in its different areas in relation to each of the alternative ideas will be:

	Covers (a)	Coatings (b)
Areas	Effective	Pond.	Total	Effective	Pond.	Total
Eat.	90	4	360	82	4	328
Prod.	93	two	186	94	two	184
Finan.	87	two	174	80	two	160
Admin.	95	one	95	93	one	93
Rrhh	92	one	92	90	one	90
Totals			907			855

Comparatively, it now turns out in weighted form that alternative A has 907 points over 855 of alternative B, or in index numbers

A: 907/907 = 1

B: 855/907 = 0.94

To decide, the following criteria can be adopted:

• The alternative with the highest score or relative index is chosen (in this case A)

• Those alternatives that meet an absolute efficiency index of more than a pre-established minimum value are chosen (Ex: if that minimum value was 0.8, then would choose in this case both alternatives A and B)

Final reflection:

It is interesting to note how a tool can allow us to reduce the risks in the selection of different products, for the launch of some of them, or perhaps none, in which case the ideas or perceived business opportunities will have to be recycled.

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