Key Driver Analysis

Good manager takes control of the most important processes. Key Driver Analysis (KDA) scans the effect of sampled attributes on the key characteristic. It helps to identify attributes with the major effect and describes how the value of the key characteristic changes with the change of particular attributes.

Success – desire of all companies

Each of us wishes for success of our product/service and these already successful wish to get even bigger success. That’s why is important to know customers’ desires and needs and be able to affect them. Especially is good to know:

  • What affects customers’ satisfaction,
  • What the customer willingness to pay more for product depends on,
  • What is the key for sale increase.

What can Key Driver Analysis do?

  • Studies the effect of particular attributes on key characteristic.
  • Identifies attributes with significant effect on key characteristic (customer satisfaction, his willingness to pay more for a product etc.).
  • Describes power and orientation of the key characteristic relation to these attributes.
  • Predicts change of the key characteristic relating to expected change of particular attributes.
  • Recommends optimal way how to affect customer.
  • In case of the specific target groups describes relation to each group separately and recommends individual approach.

When to use Key Driver Analysis?

  • When the centre of interest is one key characteristic.
  • When there is selected several attributes that may but not need to affect the key characteristic.
  • When we wish to find the most effective way of affecting the key characteristic.

Why just Key Driver Analysis?

  • Looks at current effect of all attributes, not only the effect of separated ones.
  • Identifies what key characteristic change is caused by the change of particular attributes.
  • Well-arranged and easily understandable chart is the output.

What does the output look like?

Graphic output

  • Well-arranged chart demonstrating strength and orientation of relation to particular attributes.
  • Power of relation is demonstrated in percents.
  • Orientation of dependence says if the dependence is:
    • positive: attribute value increase causes the key characteristic increase (e.g.: Willingness to pay more for a product increase with growing age.).
    • negative: attribute value increase causes the key characteristic decrease (e.g.: Willingness to pay more for a product decrease with growing age.).

Mathematical model

  • Describes relation more precisely
  • Predicts how much the key characteristic changes if we change values of particular attributes

Key Driver Analysis helps to better understand to customer’s desires and needs and enables to meet customer’s wishes.