To uncover the root causes, we used a hypothesis-driven performance diagnostic. We worked closely with members of the key business functions to collate a series of hypotheses. We then assessed the relative importance of these hypotheses using various techniques:

Market Modelling

• We built market models for both the retail and wholesale arms of the business to enable us to assess performance relative to market
• Key variables, such as the rise of second hand and government legislation, were assessed to understand their impact on the current and potential future market
• Used a combination of competitor research, expert interviews and consumer surveys to calculate triangulation points

Internal Analysis

• We used our analytics expertise to aggregate disparate data systems across all acquisitions, enabling us to understand organic and inorganic performance
• Analysing sales performance across product and customer segments allowed us to understand the key areas which our client were winning and losing in

Competitor Benchmarking

• We analysed customer sentiment for our client and their competitors to understand how service challenges had changed customer preferences
• Conducted a price benchmarking exercise to understand the product types and regions where price competitiveness had risen

The combination of these methodologies allowed us to formulate a view on our clients performance versus market. More importantly, testing hypotheses meant that the key drivers could be assessed for their strength of impact on the performance.