Operational Digitalisation of Financial Trends & Indicators
g&m’s growth in operational digitalisation has not met the CEO’s expectations in the past few years. This may result in challenges in the company’s ability to scale, grow and compete due to the inherent issues it faces under the current mode of operations, including a saturated motor insurance market, which is a price sensitive market where intermediaries compete based on prices and hefty referral fees that limits its competitiveness.
While the management has a good sensing of the business and knows it needs to disrupt the BAU in order to grow, the company does not yet have the wherewithal to deal with the data it possesses such that it could effectively leverage on the data insights to drive its business goals.
Students have delivered the following, in line with g&m’s objectives:
A data governance dashboard that aims to help g&m improve its data quality over time so that it is in a good position to derive actionable insights from its data. The dashboards provide visualisations on data completeness and data validity. These serve to alert Management on missing and/or invalid data, which are crucial to derive business insights and trigger prompt corrective actions.
A financial dashboard that aims to inform Management on financial trends and indicators. The financial dashboard is built in close consultation with the CEO and CFO to track what matters to g&m, e.g. revenue and costs trends, referral fees trends, etc. These aim to keep Management abreast of key financial information so that the CEO/CFO can assess if g&m’s growth plans are on track or if there is a need to cut back on unnecessary costs.
Both dashboards are built on Microsoft PowerBI which g&m has agreed to adopt.
Two predictive models, the Market Basket Analysis (MBA) and Customer Segmentation (CS) models are built using Python. The MBA identifies combinations of products that are purchased together frequently while the CS model provides insights on the profiles of customers segmented by low, medium and high values. MBA and CS models can be used as standalone analysis tools or as a complement to each other for marketing promotions. Both models provide insights that Management can use in conjunction with its existing business knowledge to increase cross-selling opportunities.