An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
This or that?
By and large, I think marketers and market researchers underestimate the fundamental role of comparison and contrast in the way we make judgments about products. As Professor Tripsas makes clear, humans (consumers included) rely on categorization to understand the world. Looking at a new, discontinuous product, we’re likely to ask, is it this or that?
Everything on the wiki
Individual end-users must use collaborative tools consistently throughout the project. This goes beyond updating their own availability or progress. If the organization uses SharePoint, for example, then it needs to be the epicenter of the project. Unless the material is confidential or politically sensitive, all project plans, test scripts, requirements, and training materials need to go on the wiki. Period.
Shooting for standard data
Can you modify every operational system to have a clean, standard extract file on Day 1? Of course not. But as new systems are built, …
An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
This or that?
By and large, I think marketers and market researchers underestimate the fundamental role of comparison and contrast in the way we make judgments about products. As Professor Tripsas makes clear, humans (consumers included) rely on categorization to understand the world. Looking at a new, discontinuous product, we’re likely to ask, is it this or that?
Everything on the wiki
Individual end-users must use collaborative tools consistently throughout the project. This goes beyond updating their own availability or progress. If the organization uses SharePoint, for example, then it needs to be the epicenter of the project. Unless the material is confidential or politically sensitive, all project plans, test scripts, requirements, and training materials need to go on the wiki. Period.
Shooting for standard data
Can you modify every operational system to have a clean, standard extract file on Day 1? Of course not. But as new systems are built, extracts should be built with standard data. For every operational system, a company can save hundreds or even thousands of hours every week in development and processing time. Think of what your BI team could do with the resulting time—and budget money!
The elusive matter of greatness
Some observers like the author Jim Collins think great companies are all about culture, not a singularly great leader. Collin’s “built to last” case study companies included Circuit City and Fannie Mae, both of which have been catastrophic failures. His “portfolio” has underperformed to S&P. It is convenient to think you can take greatness and bottle it up and sell it in a book. In fact, life is unfair: there are geniuses and then there are the rest of us. When great leaders go away, so does the greatness of their companies.
The business rules technology market
The market for business rule technology is fragmented and wide. Traditionally focused in application development, packaged applications, application integration and specialty apps like fraud or claims processing. Emerging sectors include Complex Event Processing (CEP), BPM, Intelligent Decision Management (what I call Decision Management) and governance/compliance.
Now about that energy bill
In most cases in the federal government, the agency CIO does not have to share in the energy bill. The CIO gets energy for free. So energy costs have never been a driver in CIO decisions. Now, even if CIOs do not have to pay for energy, they are going to be measured by energy efficiencies. This will give them more reason to modernize. By selecting newer multi-core servers and newer storage devices (like Solid State Disk [SSD]), dramatic energy efficiencies can be gained in ways that also dramatically increase performance. They will also be encouraged to virtualize more, and will also be encouraged to build in more collaborative technologies that let humans interact across great distances. All this will increase performance.
Let’s data share
Funding agencies are more focused on data managing efforts such creating institutional infrastructure and repositories rather than data sharing. The authors suggest that although such centralization efforts provides economy of scale, institutional memory, and reusable capability, in the long term they also find a substantial direct cost that may compete with research funding.