Augmenting Decision Making via Interactive What-If Analysis

09/13/2021
by   Sneha Gathani, et al.
28

The fundamental goal of business data analysis is to improve business decisions using data. Business users such as sales, marketing, product, or operations managers often make decisions to achieve key performance indicator (KPI) goals such as increasing customer retention, decreasing cost, and increasing sales. To discover the relationship between data attributes hypothesized to be drivers and those corresponding to KPIs of interest, business users currently need to perform lengthy exploratory analyses, considering multitudes of combinations and scenarios, slicing, dicing, and transforming the data accordingly. For example, analyzing customer retention across quarters of the year or suggesting optimal media channels across strata of customers. However, the increasing complexity of datasets combined with the cognitive limitations of humans makes it challenging to carry over multiple hypotheses, even for simple datasets. Therefore mentally performing such analyses is hard. Existing commercial tools either provide partial solutions whose effectiveness remains unclear or fail to cater to business users. Here we argue for four functionalities that we believe are necessary to enable business users to interactively learn and reason about the relationships (functions) between sets of data attributes, facilitating data-driven decision making. We implement these functionalities in SystemD, an interactive visual analysis system enabling business users to experiment with the data by asking what-if questions. We evaluate the system through three business use cases: marketing mix modeling analysis, customer retention analysis, and deal closing analysis, and report on feedback from multiple business users. Overall, business users find SystemD intuitive and useful for quick testing and validation of their hypotheses around interested KPI as well as in making effective and fast data-driven decisions.

READ FULL TEXT

page 1

page 3

research
12/27/2022

Predictive and Prescriptive Analytics in Business Decision Making: Needs and Concerns

Business users make data-informed decisions by understanding the relatio...
research
03/05/2020

Bayesian A/B Testing for Business Decisions

Controlled experiments (A/B tests or randomized field experiments) are t...
research
03/08/2018

QREME - Quality Requirements Management Model for Supporting Decision-Making

[Context and motivation] Quality requirements (QRs) are inherently diffi...
research
06/13/2017

Recommendations for Marketing Campaigns in Telecommunication Business based on the footprint analysis

A major investment made by a telecom operator goes into the infrastructu...
research
09/29/2020

Towards Intelligent Risk-based Customer Segmentation in Banking

Business Processes, i.e., a set of coordinated tasks and activities to a...
research
03/23/2019

Online Decision Process based on Machine Learning Techniques

This paper analyses role of internet in marketing and its influences on ...
research
01/07/2015

Roman Urdu Opinion Mining System (RUOMiS)

Convincing a customer is always considered as a challenging task in ever...

Please sign up or login with your details

Forgot password? Click here to reset