Utilizing Data-Driven Approaches in Business

Source: MBAGRADSCHOOLS. Edited for style.

Using a  data-driven approach in business decision-making will be standard practice by 2025. Intelligent workflows and seamless interactions between humans and machines will be as common as the corporate balance sheet. Most employees will have to use data to optimize nearly every aspect of their work.

Most businesses struggle to harness the power of their data effectively. The root causes often boil down to a need for more understanding of data’s value, the absence of the right tools, and inadequate processes. The concept of “data maturity” delineates how proficiently a company utilizes data for decision-making. Data-mature businesses prioritize data-driven decisions over gut instincts, leading to significantly better business outcomes. Unfortunately, many companies are still in the initial stages, failing to leverage their data’s potential for impactful decision-making.

In this context, the expertise of P.K. Kannan, associate dean for strategic initiatives at the University of Maryland’s Robert H. Smith School of Business, comes to the fore.

Kannan, via an MBATUBE video, says he firmly believes in the transformative potential of data, particularly from the vibrant world of social media. He points out that social media platforms provide a wealth of data through user actions like clicks, likes, and comments. (00:27)

Insights from social engagement data are helpful for advertising, product innovation, and proactive risk management. By leveraging social media data, brands can reinforce their positioning in the market. Such data allows brands to tailor content, predict trends, and enhance customer satisfaction based on interactions and perceptions.

In the realm of data-driven decisions, the work of Kannan stands out. This article will focus on his key findings from two papers published recently in The Journal of Marketing: “Identifying market structure: A deep network representation learning of social engagement” (with Smith Associate Professor of Information Systems Kunpeng Zhang) and “Measuring the real-time stock market impact of firm-generated content.”

We’ll explore the core concepts and implications of Kannan’s research, providing a deeper understanding of how data shapes market dynamics and brand relationships today.

Identifying market structure: A deep network representation learning of social engagement

In this study, Kannan and his coauthors analyzed a staggering 140 million data points to decode the intricacies of market structures through the lens of social engagement. Their work used artificial intelligence (AI) to uncover unexpected and actionable insights from consumer data. These findings reveal the unexpected connections consumers establish between brands on social media.

Understanding these connections is key for businesses trying to overcome data challenges. By identifying potential collaborations, they can more effectively target and engage with their audience.

For instance, Southwest Airlines, Disney Cruise, and Hyatt Hotel were clustered together, indicating potential cross-promotion opportunities. The team created a visualization of the intricate web of brand relationships that’s available to explore.

Moreover, the analysis wasn’t a static market snapshot. Kannan’s research includes how brands’ positions evolve in response to factors like new product introductions. He uses Tesla’s shift from luxury to mainstream markets with the introduction of the Model 3 as an example of the fluidity of market dynamics. (04:35)

Empowering insights through AI-driven data analysis

At the heart of the data-driven revolution lies artificial intelligence. Analyzing massive datasets manually is an impossible task. However, AI using deep learning techniques can efficiently process vast amounts of data.

Kannan says, “AI can handle a lot of information. It can, in essence, pick up the most important relationships that are there in the data and forget about all the noise that appears in the data. Then come up with a central structure.” (02:48)

This capability of AI not only makes data processing feasible but also extracts actionable insights that businesses can integrate into their strategies.

Measuring the real-time stock market impact of firm-generated content

In this compelling study, Kannan and his coauthors moved into the financial realm, examining how companies’ Tweets (posts on social platform X, formerly known as Twitter) impact stock prices.

Kannan’s research offers insights for crafting tweets that generate meaningful and lasting investor responses. By emphasizing clear communication and positive valence, companies can shape investor perceptions favorably. Addressing competition also has positive effects on stock prices. These insights are particularly relevant in an era where AI-augmented trading algorithms shape market movements.

He emphasizes AI’s significant role in analyzing the microsecond-by-microsecond movements of stock prices associated with tweets. “AI bots are scouring the social media sites to see what information is out there about a particular firm, and then immediately they start acting on it,” Kannan notes. (07:37)

Even a single tweet can sway market sentiment in today’s digital age. AI’s prowess in this domain ensures that businesses must quickly gauge and react to these market shifts.

Global collaborations at Robert H. Smith School of Business

The Robert H. Smith School of Business at the University of Maryland is committed to cutting-edge research beyond U.S. borders. Faculty members like Kannan engage with international institutions and contribute to a global body of knowledge.

He says faculty members “don’t just bring the experiences of a local market, but they also bring in experiences in the international market and bring all those findings and make it very useful for students.” (20:09)

Translating research of data-driven approaches into real-world impact

Kannan’s research seamlessly integrates cutting-edge insights into his teaching, benefiting MBA candidates taking his classes at the Smith School. He equips students with practical knowledge by transforming complex research findings into digestible content. His engagement with industry leaders and real-world business challenges ensures his students are well-prepared to navigate the dynamic marketing and data analysis landscape.

Additionally, Kannan’s collaborations with industry giants like Marriott Hotels showcase the tangible impact of his research. One of the cutting-edge techniques Kannan has extensively researched is multi-touch attribution, which traces the different touchpoints a consumer interacts with before purchasing.

“I’ve done a lot of work in multi-touch attribution and, actually, worked with Marriott on a consulting project with my student,” Kannan explains. (14:28)

This hands-on experience ensures students aren’t just learning theory but are also understanding its practical implications.

Such collaborations don’t just end with understanding a concept; they offer students a front-row seat to the challenges and intricacies of the business world. As they engage with these challenges, students learn to harness analytical techniques effectively, sharpening their problem-solving skills.

Kannan’s work is a beacon in an era dominated by data, highlighting the immense potential of integrating artificial intelligence with business strategies. His teachings, research, and insights collectively underline the transformative power of a data-driven approach in understanding markets, consumers, and the dynamic interplay between them.