An apparatus comprising: a transformer that receives an entity sensory representation that represents an entity; wherein the entity sensory representation comprises a plurality of sensory representations that represent a plurality of items that are part of the entity in which each of the plurality of items is associated with a set of values for a set of measurable factors of interest, wherein the set of measurable factors of interest comprises a level of importance of the plurality of items; wherein the transformer calculates a set of scale factors for each of the plurality of sensory representations based on the set of values associated with the each of the plurality of items; wherein the transformer modifies the plurality of sensory representations using the set of scale factors to form a plurality of modified sensory representations that establish a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the set of measurable factors of interest; wherein the transformer acquires the set of values continuously over time from one or more sensor systems configured to monitor the set of measurable factors of interest; wherein the transformer adjusts the set of scale factors to update the plurality of modified sensory representations in substantially real-time as the set of values changes; wherein the entity sensory representation represents the entity using at least a sense of sound; wherein the entity sensory representation comprises an audio recording (1300, 1500) and the plurality of sensory representations comprises a plurality of sections (1301, 1501) of the audio recording (1300, 1500) comprising verbal instructions for performing a manufacturing operation, wherein each section represents instructions for performing a different step of the manufacturing operation; and wherein the set of scale factors is used to modify a loudness of each of the plurality of sections (1301, 1501) according to the relative importance of the manufacturing operation of each of the plurality of sections (1301, 1501). wherein the entity sensory representation comprises a plurality of sensory representations that represent a plurality of items that are part of the entity in which each of the plurality of items is associated with a set of values for a set of measurable factors of interest, wherein the set of measurable factors of interest comprises a level of importance of the plurality of items; wherein the transformer calculates a set of scale factors for each of the plurality of sensory representations based on the set of values associated with the each of the plurality of items; wherein the transformer modifies the plurality of sensory representations using the set of scale factors to form a plurality of modified sensory representations that establish a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the set of measurable factors of interest; wherein the transformer acquires the set of values continuously over time from one or more sensor systems configured to monitor the set of measurable factors of interest; wherein the transformer adjusts the set of scale factors to update the plurality of modified sensory representations in substantially real-time as the set of values changes; wherein the entity sensory representation represents the entity using at least a sense of sound; wherein the entity sensory representation comprises an audio recording (1300, 1500) and the plurality of sensory representations comprises a plurality of sections (1301, 1501) of the audio recording (1300, 1500) comprising verbal instructions for performing a manufacturing operation, wherein each section represents instructions for performing a different step of the manufacturing operation; and wherein the set of scale factors is used to modify a loudness of each of the plurality of sections (1301, 1501) according to the relative importance of the manufacturing operation of each of the plurality of sections (1301, 1501).