The customer is a joint venture / partnership organization between two major automobile dealerships and one of the leading US automobile manufacturing companies. The company focuses on using the data advantage from its parent organization to drive analytics-based value in retail for its dealerships. Brillio’s expertise in the digital and analytics space will help the customer perform a DPM assessment effectiveness study to identify key factors which drive success for its dealer –monitoring manager workforce.
For the task at hand the analytical problem maybe stated thus:
In any assessment of such nature the key challenge lies in collating the correct data and determining the factors to compute an index or metric of effectiveness. The current study spanned 42 DPM’s,1,957 dealers,and considered data from 10 different data sources. The need was to make sense of this vast assortment of data sources and find a tangible solution to an unmeasurable problem. The client needed assistance identifying the correct factors to generate a score / metric by using advanced algorithms developed by Brillio’s Data Science team which address the problem and rank the DPM’s.
To help assess and rank DPM’s with a single comprehensive computed metric, a three phase solution strategy was employed.The first task was data collection for 3 months post and prior the assessment period. This was collated and a ‘delta’ value served as the primary base data for further processing. Factor Analysis lead to finding out key underlying factors and individual data sources were grouped under these base factors. The factor loadings for constituents were then used to determine a normalized value/ weight or each base/ sub factor. Finally DPM Effectiveness Index is obtained at Dealer and DPM level by doing a weighted sum of the 4 sub-factor scores to come at a single value for a DPM. A schematic of the solution is depicted in Fig.
Changes in dealer operations in the 3 months pre and post DPM assessment are observed across product usage, cases, and consumer interaction metrics.
Factor analysis data reduction technique is applied to arrive as 4 sub-factors :–
a) Product usage
b) Product investment
c) Consumer interaction
d) Cases & issues
Each sub-factor score is normalized to a scale of 0-100 which is then converted to weights. Overall DPM Effectiveness Index is obtained at Dealer and DPM level by doing a weighted sum of the 4 sub-factor scores.
Studies after completion of the assessment revealed the following high business impact insights which maybe exploited for higher dealer engagement and revenue growth.
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