January 2022
Beginner to intermediate
240 pages
5h 25m
English
Content preview from AI-Enabled Analytics for Business
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CHAPTER 11Use Case: Incremental Improvements to Gain Insights
It may seem counterintuitive, but growth companies are often slow to adopt AI and analytics, especially high-tech industries. Part of this is driven by high margins and part by high growth that masks underlying inefficiencies that cause under-optimized planning. The culture is about meeting demand to grow market share at any cost, since cost is less of an issue when margins are not an issue.
This is the story of Jonathan Morgan, senior director of demand, inventory, and spare parts at Palo Alto Networks (NASDAQ:PANW), a Santa Clara $3.4 billion revenue manufacturer of cybersecurity hardware and software to enable digital transformation across 80,000 customers in 150 countries.1 Jonathan was at the beginning of the Roadmap to achieve insights from data and was incrementally progressing toward the data-driven Analytics Culture.
Jonathan's scope of responsibilities covered the S&OP process, demand planning, supply planning, inventory management, and spare parts planning.
STARTING ANALYTICS
Jonathan's AI-enabled analytics journey began with reporting data and progressed to the analysis of data for information. In the latter, data visualization and budgeting tools are often used to replace reporting previously done in spreadsheets. From there, desktop statistics and some visualization tools can start providing insights from low-level analytics. Many companies, like PANW, follow this road.
In about 2018, Jonathan was ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.