Company Sponsor: g&m Pte Ltd
g&m Pte Ltd (“g&m”) is an insurance broker, which has embarked on a digitalisation transformation journey in 2020, aiming to become a data-centric company. Through this project, g&m hopes to increase its bottom line by deriving insights from its data to increase cross-selling opportunities, as well as financial insights that can improve their management decisions.
Title: Building A Data Centric Future
Project Team: Chen Huifang, Chiang Hai Yin, Chua Wan Rong, Goh Shun Min, Guo Yusheng Ryan and Leong Yihua
Through the course of this project, we worked closely with g&m management to ensure that our objectives and understanding were aligned. We also leveraged on our diverse experience and professional expertise to recommend viable solutions to address the immediate issues faced by g&m in its current stage of development.
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.
Our group has 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.
Team Reflection
The team demonstrated the value of open communication, both within the team itself as well as with the customer. g&m was open, receptive and forthcoming with their difficulties and this allowed us to focus on solving the issues faced as both g&m and the team had a clear vision of the future and common objectives on the outcome of this project. If they had not been honest regarding the mistakes made and errors committed along the way, we may not have thought of the necessary tools to aid in their digital transformation. We also took pains to ensure that we did not always focus on the limitations of their current processes. Instead, we adopted a forward-looking approach to identify opportunities in which they could do better and proposed positive changes in that regard.
At the same time, the selective deployment of tools created helped in messaging as well. It was not so much about throwing every single item that we developed at g&m, but more about rationalising which tools would help g&m the most at this point of their data journey and providing a path to data maturity. If management attention was distracted by too many tasks at hand, scarce resources would be allocated too thinly and without focus. It was thus critical that we identify the key building blocks for g&m to kickstart their digitalisation.
