Recently, we’ve been running a series of posts highlighting the needs and interests of different types of analytics users within the enterprise.
For instance, Brian, is a “business champion“ for a discrete manufacturer with international facilities who oversees a department that performs use-case activities. Brian needs real-time insights about emerging operational and market trends.
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, a management budget owner for a “big box” home improvements retailer, is looking for analytics tools that can help her identify opportunities to reclaim market share from global competitors over the next 18 months.
In her case, Michelle needs analytics tools that can help her discover growth opportunities that may otherwise slip under the radar.
Michelle also needs predictive analytics that can help her to see the big picture – despite organizational data silos that exist within the company that make it difficult to evaluate the full spectrum of customer and market data that’s available.
In this chapter, we feature Tom, an IT influencer for a Fortune 500 consumer packaged goods company, who wants to ensure that he’s providing senior management with the tools and information they need to make the best possible decisions quickly.
Tom, a VP of IT who runs a four-person business intelligence team for the CTO, is in search of an analytics solution that relieves his team of the burden of having to generate report after report for the business as well as frees them up to devote more time to strategic initiatives.
Still, Tom is also skeptical of vendor promises – he wants to validate the functionality of analytics platforms through testing before making a selection while ensuring there aren’t any hidden costs, such as add-on training and support fees.
In his search for the right analytics solution for the business, Tom is constantly scouring the technology landscape by reviewing white papers, demos, webinars, and trade shows to keep abreast of emerging trends and new technologies that are coming down the pike.
Tom wants to combat the firm’s view of IT as a commodity by ensuring that his team is delivering unique value through the adept use of the company’s ever-expanding data assets. Still, Tom must also ascertain that the company’s use of data complies with internal and external data governance policies.
In his team’s evaluation of vendors, Tom is adamant about identifying a predictive analytics platform that can grow with the company and meet the complex needs of different types of business users (senior management, line of business leaders, product managers) without being limited to a single class of users (power users, neophytes).
Keeping a close eye on the budget, Tom insists on landing favorable contract terms with technology providers, which is one of the reasons he and his team are exploring the viability of a cloud-based analytics platform that can be used to deliver real-time, scalable insights to business leaders quickly and affordably.
Multi-faceted predictive analytics tools can allow Tom and his team to enable the company’s business leaders to keep up with the frenetic pace of business.
Powerful analytics tools that are easy to use permit executives to discover actionable insights to customer and market trends quickly – a critical requirement in the high-pressure, low margin consumer packaged goods industry.
Every decision that’s made about product pricing, tailoring product offers, and identifying new product opportunities can make a huge impact in vaulting the company ahead of the competition.
In our next installment, we’ll explore the analytical needs of Allison, a mergers and acquisitions analyst for an international bank who needs to be able to conduct deep analyses – often with statistical models – to uncover essential insights about prospective acquisition targets without having to rely on IT for the information.
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