In this chapter of our continuing series of posts spotlighting the needs and interests of different types of analytics users in the enterprise, we feature Allison, an inquisitive mergers and acquisitions (M&A) analyst for an international bank who has exceptional analytical skills and domain expertise.
In previous posts, we’ve featured the unique requirements of Brian, a “business champion,” Michelle, a “management budget owner,” and Tom, an “IT influencer.”
Each person has distinct demands – Brian and his team require analytics tools that enable them to quickly spot aberrations in plant floor operations and analyze the root causes to mitigate risk to the enterprise.
Meanwhile, Michelle relies on analytics tools that can help her identify opportunities to reclaim market share for her employer, a “big box” home improvements retailer, over the next 18 months.
For his part, Tom seeks predictive analytics that relieve his team of the burden of having to generate report after report for executives at the consumer packaged goods company, while freeing his team to devote more time to strategic initiatives.
Allison, who has worked in financial services since graduate school, needs to be able to conduct deep analyses to uncover essential insights about prospective acquisition targets without having to rely on IT for the information.
Although she’s low key, Allison is well respected throughout the organization for her intelligence and ability to uncover critical insights about potential acquisition targets. A regular attendee of industry trade shows and user conferences, Allison is determined to stay on top of the latest analytics trends and tools.
Curious by nature, Allison is intent on staying current with both well-publicized and subtle shifts in the industry, including emerging characteristics of potential takeover targets (e.g., a boutique investment bank with profitable customers but inefficient management of the firm’s assets).
A self-proclaimed “statistical junkie,” Allison cares deeply about the integrity and proper use of data. And she’s adamant about developing her own models that make it easy for business leaders to take an optimal course of action.
She wants to be able to use predictive analytics tools to make it easy for business leaders to weigh the pros and cons of each potential takeover candidate.
Mindful of the highly-competitive investment banking industry, Allison also wants to be able to inspect data and have access to strong visualization capabilities in the predictive analytics tools she uses to help her discover meaningful trends, patterns, and outliers for the business community she supports.
A firm believer that most people in the bank don’t fully appreciate the value that a data scientist brings to the table, Allison wishes to see her analytical models widely distributed and used throughout the organization to solve problems and drive successful M&A strategies.
Clearly, Allison is not a casual user of predictive analytics. Because of the demands of her role and her own expectations, Allison wants real-time access to data and analytics capabilities.
Even after she creates models about potential acquisition targets for business leaders and M&A teams to pore over, she requires a predictive analytics platform that gives her the power and flexibility to quickly and effectively answer any questions that business leaders may pose regarding her research.
In our next installment, we’ll examine the analytical needs of Paula, a purchasing manager, who has been instructed to evaluate each of her company’s contracts to identify opportunities to cut costs and find attractive alternatives in the market that offer good value and no hidden costs.
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