We often associate the use of analytics with running a successful corporation, but the truth is, its use goes way beyond that. Analytics is now increasingly playing a role in sports (Super Bowl, soccer, tennis), in the public sector and politics, and at nonprofit organizations.
City Year: Helping Students and Schools
City Year is a national nonprofit organization that mobilizes young adults to serve as full-time tutors, mentors, and role models in many of the nation’s highest …
Why is the future so difficult to predict? It is easy enough to jot down a few paragraphs on a given future topic, say the future of the retail industry and the impact that big data will have on it, but it is very difficult to have any assurance that those projections will map to anything that actually happens. Part of the problem is that we tend to see the future as an exaggerated version of the present rather than a world in which fundamental changes have occurred.
There is an old story in futurist circles, probably apocryphal, about a …
It’s the start of the year, and organizations around the world are holding kickoff meetings in order to explain new incentive systems to their employees.
These plans are typically the result of many months of painful negotiations, as corporate stakeholders debate the perfect set of incentives to support the organization’s strategy.
But every system of incentives inevitably opens up the possibility of dysfunctional behavior. Not necessarily because employees are corrupt, but because they feel pressured to “meet the numbers” – and because daring to question the value of corporate KPIs is actively discouraged.
A lot has been written on the 3 V’s of Big Data – Volume, Variety and Velocity. Yet there are two more equally, and perhaps even more important, attributes to consider—Value (business value to be derived) and Veracity (the quality and understandability of the data).
Big Data Value
Value starts and ends with the business use case. The business must define the analytic application of the data and its potential associated value to the business. Use cases are important both to define initial “Big Data” pilot justification and to build a roadmap for transformation.
This value is critical in the …
Surveys, questionnaires, and polls generate data, but survey data and hard data aren’t the same thing. I often see them treated in the same light in the context of answering business questions or delivering actionable insight, and with equal zeal and qualification. But there are definite differences.
Understanding the difference between data collected from surveys vs. data generated from transactions or operations is crucial. It will help us find the relevant answers to our questions and also save us a lot of time and money in the process.
There’s a science and methodology to developing effective surveys. Design and data …
Come holiday season and it’s normal for your promotional mail to increase four folds. But this holiday, I received a few weird offers—a hearing aid, a retirement community brochure, and a marketing call for an elderly alert system. Being in analytics myself, I wanted to understand the reason why these companies are targeting me since I assumed this didn’t result from mass marketing.
I started scanning my last few months’ purchases to understand the trigger and didn’t find anything. Finally, I found a website that listed my marketing data and this is what I found:
And the …
What is a business intelligence (BI) Strategy? Why should you care? The phrase has been increasingly used by organizations to recognize effective use of business intelligence and to take BI programs to the next level. Do you have one? If you are looking at your architecture slide, then let’s explore some of the myths around BI strategy.
Myth One: BI Strategy Is All About Technology and Architecture
BI strategy is often misrepresented as architecture diagrams with several data sources feeding into an enterprise data warehouse and shiny tools that access data from the data warehouse. The technology and architecture are …
“In preparing for battle, I have always found that plans are useless, but planning is indispensable.” General Dwight D. Eisenhower
Faced with rapid changes in marketing over the last few years, marketers are under increased pressure to be proactive and produce results within shorter time frames. They have to review their plans to meet dynamic market changes. Organizations are handling this pace of change via agile marketing.
Agility is driven by the need to serve end users. It’s about always being relevant and responsive. Developing an iterative marketing plan provides opportunities to review the plan and update it as needed …
In mobile business intelligence(BI) design, the “consistency principle” is the most powerful tool to effectively deliver a mobile user experience. Developing components that are both consistent and repeatable greatly accelerates the “mobile learning curve,” leading to higher user adoption.
We apply the consistency principle at two levels:
The macro level occurs at-the-project or engagement level and covers all resources or artifacts that are used to deliver and support implementation of mobile assets (like user guides, communication, online stores, and support). The micro level deals with the design of each individual mobile BI asset (like …