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The business of running businesses is getting a wake-up call. From flattened hierarchies to an explosion of information, Big Data is reinforcing some old business assumptions and upending others. If you’ve got a business degree, and you haven’t figured out how to apply Big Data to administration, you’re vulnerable. In this opening session, Strata chair Alistair Croll sets the stage for JumpStart with an overview of business in a data-driven economy.
by Nolan Goldberg
Emerging technologies – such as big data – can change both the scope and practical impact of the law. For example, a Court in California recently held for the first time that a zip code was personally identifiable information within the meaning of the state’s Song Beverly Credit Card Act. Prior case law treated zip codes as identifying only groups of people at best and therefore zip codes were not personally identifiable information and requesting zip codes at the point of sale did not appear to be prohibited. The California Court, however, was forced to depart from precedent after acknowledging that easily accessible de-anonymization technologies now enabled retailers to use zip codes to determine exact home addresses. Accordingly, the well established practice of asking for zip codes at points of purchase needed to stop (and a flood of new lawsuits followed). Putting the above example aside, Big Data technologies have the potential to require changes in important areas of the law, such as intellectual property, e-discovery, data ownership and privacy. This session will explore both the potential impact of big data on the law generally and some of the specific legal issues of concern when monetizing big data.
by Cathy O'Neil
Data management teams need strong cloud computing and database management skills, and proficiency with tools like Hadoop, mapreduce jobs and SQL queries. The analysts need to be deep thinkers and creative modelers with experience in machine learning and financial modeling—ideally both. Being model- and data-driven means overnight data-crunching to produce daily data reports, which often lead to more overnight questions. There are also inherent difficulties in talking to clients and internal stakeholders when inherently unstable data and statistics are key tools for decision-making.
From a process standpoint, we need start asking new kinds of questions that Big Data is opening up for the first time. Speaker Cathy O’Neill will use her unique experience in finance, which is the field that is the most developed in terms of modeling, to explain how she sees today’s business world as relatively unsophisticated and ””spoiled for data.”” She’ll explain various techniques that financial analysts employ to improve models, and reconsider the practice of A/B testing in a model-driven world.
The abundance of data made it easy to collect and analyze data from online user behavior and discussions. Although it is encouraging to see businesses using such data and making data-driven decisions, we often see decisions based on flawed analyses, or simply using data that measure the wrong things. Panos will illustrate cases, where simple reading of available data points into one conclusion, while a deeper study uncovers a different truth. Examples will be drawn from online reputation systems, online reviews, crowdsourcing, and other case studies.
Life is all about competition whether nation states, organisations or individuals. This competition invokes a process of evolution and whilst the future cannot be predicted with any certainty, patterns are emerging. Two of the latest patterns include the use of ecosystems in the warfare between organisations and how open source is increasingly becoming deployed as a tactical weapon. This talk will explore these patterns, the underlying process of evolution, the new management practices that are appearing and the importance of big data in this new environment.
by Hiten Shah
Lean Startup principles are based on the idea that startups are working in an environment where there is an unknown problem with an unknown solution. They are built to learn from the start. Applying these principles to companies later in their lifecycle can be challenging but rewarding. Hiten will walk you through how these principles can be applied to your later stage startup or even within a large organization to unlock growth and innovation.
Customers are the reason you’re in business. To earn their continued love and loyalty, you must strive to enhance their experiences across all touchpoints. To earn a larger share of their pocketbooks, you must also target them with offers that suit their specific profiles, needs, and propensities. To these ends, leading-edge organizations have implemented “next best action” (NBA) technologies, such as “Big Data” analytics, within their multichannel customer relationship management programs. In this session, Forrester senior analyst James Kobielus will provide a vision, case studies, ROI metrics, and guidance for business professionals evaluating applications of NBA in their organizations.
See how to turn otherwise commodity products into timely solutions to unique customer needs by wrapping them with a tailored blanket of information based value-added services. Most customers have needs that go beyond just the basic product; learn to identify those needs and deliver customized value-added services to meet those needs. Customers will pay an additional 2 – 4 percent (and sometimes more) for these services because they are simply sharing some of the greater value you deliver to them. Mr. Hugos uses specific case studies and techniques from his own experience to demonstrate how to combine products, data and supply chain services to earn an increased gross profit for your company. Supply chain management is a profit center, not a cost center, if you do it right.
Few disciplines in business have changed as much as marketing. The cost of transmitting a message has dropped to zero, and the flow of content has flipped from one-way broadcast to two-way interaction. Consumers expect genuine interactions; marketers need to scale their numbers efficiently while still targeting with laser precision. In this session, Jennifer Zeszut, a 15-year veteran of marketing at brands like Proctor and Gamble, eBay, and Cost Plus who honed her tech skills at Razorfish and launched sentiment analysis pioneer Scout Labs, looks at the new marketing in a world of numbers and analysis.
Google does HR by the numbers. The company’s ambitious Project Oxygen initiative compiled management data across managers and employees, then analyzed and applied its findings to make teams more effective. In this session, Kathryn Dekas, a manager in Google’s People Analytics department and Project Manager for Google’s annual employee survey, looks at what it means to use data to drive decisions and action in the HR function, and examples of how this process can transform organizations.
At many companies, the total amount of data processed each year will double in less than two years. And the need to share that data—with employees and with partners, vendors, and customers—is growing. The odds that corporate information will leak is growing rapidly; we’ve already seen dramatic examples from the US State Department, and a number of visible banks.
Most executives’ first reaction to such leaks is to lock things down: “Make sure this doesn’t happen to me.” But at some leading-edge companies, CIOs are realizing that their job is no longer about information technology; rather, it’s about how the information itself moves within the organization. By asking “what needs to be protected?” and “what are the upsides of sharing?” they’re reconsidering the idea of leakage.
There’s never been a better time to reconsider transparency and talk about strategic leaking. In this session, Michael Nelson— whose career has taken him from the White House to the boardrooms of the Fortune 500—looks at the naked corporation and what information can do when it flows intentionally between companies and their ecosystems. His new report for the CSC Leading Edge Forum Research examines how radical transparency can be a powerful business tool, with companies sharing the previously unthinkable—salary, pricing, project roadmaps, and more.
by DJ Patil
Given the importance of data to critical decision making, the demand for Data Scientists is at an all time high. Yet, what does it really mean to be a Data Scientist and to build a team of Data Scientists? It’s a new world with startups to well established organizations struggling daily to recruit and structure their teams to best leverage those that can extract valuable insights from data. Unfortunately most organizations don’t realize all the places where a good Data Science Team can make an impact. In this talk we’ll walk through different organizational structures, how to empower, and key technologies required to establish a great Data Science team.
19th September 2011