Difference between revisions of "ANLY482 AY2016-17 T2 Group19"
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The IVAD was developed using transactional data in a pharmaceutical context however it is a framework that is highly generalizable to businesses with multiple points of sales and a range of customer segments. This is done by incorporating spatial analytics in the form of proportionate symbol web-maps, product tree-maps, customer segment tree-maps and purchasing pattern heatmaps, as well as reactive charting for trend analysis. | The IVAD was developed using transactional data in a pharmaceutical context however it is a framework that is highly generalizable to businesses with multiple points of sales and a range of customer segments. This is done by incorporating spatial analytics in the form of proportionate symbol web-maps, product tree-maps, customer segment tree-maps and purchasing pattern heatmaps, as well as reactive charting for trend analysis. | ||
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Revision as of 00:04, 24 April 2017
Contents
Members
Project Background
SMEs employ about 70% of Singapore’s workforce while contributing more than 50% of the country’s economic output. However, most these SMEs are either slow or not engaged in adopting big data analytics despite government initiatives aimed at improving productivity. According to a survey conducted amongst 233 SMEs in April to June in 2016, cost was the main barrier for SMEs to invest in such capabilities, followed by a lack of in-house expertise to make full use of data analytics in improving business processes.
The use of data analytics would allow SMEs to discover deeper insights regarding sales trends, customer spending patterns and operations. It also allows for newer dimensions of data to be analysed, for instance, spatial analytics could potentially allow SMEs to conduct a more refined market segmentation, consequently bringing about more precise identification of customers and targeting of sales promotions or products.
To assist SMEs in sharpening their competitiveness and to address their concerns regarding investment in data analytics, an interactive visual analytics dashboard (IVAD) was developed as a potential solution. The proposed IVAD considers the need for a holistic view of business and thus incorporates three perspectives that may prove useful in a business context: Spatial, Product, Customer; and aims to answer the questions of when, where, what, and who.
The IVAD was developed using transactional data in a pharmaceutical context however it is a framework that is highly generalizable to businesses with multiple points of sales and a range of customer segments. This is done by incorporating spatial analytics in the form of proportionate symbol web-maps, product tree-maps, customer segment tree-maps and purchasing pattern heatmaps, as well as reactive charting for trend analysis.
Motivation & Objective
Research and development efforts were motivated by the general sentiments of SMEs towards data analytics innovation across Singapore and the lack of professionals with deep computer language knowledge required to handle volume, variety, velocity of data. It aims to address the gap between research areas of institutes (e.g. University) and practical business needs through working closely with a local SME, in this case, specifically in the pharmaceutical field.
By building an interactive visual analytical tool that does not require advanced computing knowledge for data exploration, we can enable business professionals with domain knowledge to leverage on the wealth of data. With deeper understanding of how nuances between sales, customer types, products and geographic segmentation, businesses can help to drive business sustainability with greater focus.
In relevance to the business, the visual dashboard attempts to support decision making process by fulfilling the following analysis requirements:
1. To be able to display massive sales data cartographically.
2. To provide a graphical visualization framework that can display distribution of product mixes in relation to customer types over time.
3. To provide visual comparability between similar types of customers in a designated geographical context.
4. To derive insights into customer spending trends based on their respective types and geographical locations
Dashboard
Status: Completed. Refer to Methodology and Analysis to View.
Timeline with Process Flow
End of Project.
Submitted Final Conference Paper and Artifacts. Handover of deliverables to Client.
