Via Nigel Eccles and Mat Fogarty, the Predictify blog, Mashable, and VentureBeat.
NewsFutures, Consensus Point and Inkling Markets were self-funded, are now profitable, and are continuing to address their customers’- problems with a continually improved technology. These 3 prediction market software vendors are proving that you can create a sustainable business without the need to get “-funded”- by angel investors or VCs. With the money from those guys also comes the pressure to “-monetize”- every thing. It’-s not always a good thing to have the suits running the show. NewsFutures, Consensus Point and Inkling Markets are still in the hands of their founders, and they are still free to execute their vision —-the way they want.
What’-s your view, folks?
Previous blog posts by Chris F. Masse:
- A second look at HedgeStreet’s comment to the CFTC about “event markets”
- Since YooPick opened their door, Midas Oracle has been getting, daily, 2 or 3 dozens referrals from FaceBook.
- US presidential hopeful John McCain hates the Midas Oracle bloggers.
- If you have tried to contact Chris Masse thru the Midas Oracle Contact Form, I’m terribly sorry to inform you that your message was not delivered to the recipient.
- THE CFTC’s SECRET AGENDA —UNVEILED.
- “Over a ten-year period commencing on January 1, 2008, and ending on December 31, 2017, the S & P 500 will outperform a portfolio of funds of hedge funds, when performance is measured on a basis net of fees, costs and expenses.”
- Meet professor Thomas W. Malone (on the right), from the MIT’s Center for Collective Intelligence.
what the company does-
how it does it-
who actually does the work.
Read the previous blog posts by Chris F. Masse:
- I get a kick each morning out of spying on the rich, famous, and powerful people updating their LinkedIn profile and connections. (Go to “InBox”, and click on “Network Updates”.)
- ??? BetFair bet-matching logic ???
- Eliot Spitzer has simply demonstrated once again that those who rise to the top of organizations are very often the most demented, conflicted individuals in any group.
- Business Risks & Prediction Markets
- Brand-new BetFair bet-matching logic proves to be very controversial with some event derivative traders.
- Jimmy Wales accused of editing Wikipedia for donations.
- What the prediction market experts said on Predictify
Wikipedia (on Business Intelligence):
Business intelligence (BI) is a business management term which refers to applications and technologies which are used to gather, provide access to, and analyze data and information about their company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions. Business Intelligence should not be confused with competitive intelligence, which is a separate management concept.
Wikipedia (on Competitive Intelligence):
“-Competitive Intelligence (CI) is both a process and a product. The process of Competitive Intelligence is the action of gathering, analyzing, and applying information about products, domain constituents, customers, and competitors for the short term and long term planning needs of an organization. The product of Competitive Intelligence is the actionable output ascertained by the needs prescribed by an organization.”-
Key points of these definitions:
1) Competitive Intelligence is an ethical and legal business practice. (This is important as CI professionals emphasize that the discipline is not the same as industrial espionage which is both unethical and usually illegal).
2) The focus is on the external business environment.
3) There is a process involved in gathering information, converting it into intelligence and then utilizing this in business decision making. CI professionals emphasize that if the intelligence gathered is not usable (or actionable) then it is not intelligence.
The term is often viewed as synonymous with Competitor Analysis but Competitive Intelligence is more than analyzing competitors — it is about making the organization more competitive relative to its existing set of competitors and potential competitors. Customers and key external stakeholders define the set of competitors for the organization and, in so doing, describe what could be a substitute for the business, votes, donations or other activities of the organization. The term is often abbreviated as CI, and most large businesses now have some Competitive Intelligences functions with staff involved often being members of professional associations such as the Society of Competitive Intelligence Professionals. CI activities often use a “-Competitive Intelligence Solution”-, usually via their intranet and internal alerts, which can also lead to Competitive Response Solution.
The Society of Competitive Intelligence Professionals (SCIP) is an organization for those who are interested in learning more about Competitive Intelligence. Established in 1986, they provide education and networking opportunities for business professionals, and provide up to date market research and analysis. “Members of the SCIP have backgrounds in market research, strategic analysis, science and technology.”
Wikipedia (on Business Intelligence):
When implementing a BI programme one might like to pose a number of questions and take a number of resultant decisions, such as:
– Goal Alignment queries: The first step determines the short and medium-term purposes of the programme. What strategic goal(s) of the organization will the programme address? What organizational mission/vision does it relate to? A crafted hypothesis needs to detail how this initiative will eventually improve results / performance (i.e. a strategy map).
– Baseline queries: Current information-gathering competency needs assessing. Does the organization have the capability of monitoring important sources of information? What data does the organization collect and how does it store that data? What are the statistical parameters of this data, e.g. how much random variation does it contain? Does the organization measure this?
– Cost and risk queries: The financial consequences of a new BI initiative should be estimated. It is necessary to assess the cost of the present operations and the increase in costs associated with the BI initiative? What is the risk that the initiative will fail? This risk assessment should be converted into a financial metric and included in the planning.
– Customer and Stakeholder queries: Determine who will benefit from the initiative and who will pay. Who has a stake in the current procedure? What kinds of customers/stakeholders will benefit directly from this initiative? Who will benefit indirectly? What are the quantitative / qualitative benefits? Is the specified initiative the best way to increase satisfaction for all kinds of customers, or is there a better way? How will customers’- benefits be monitored? What about employees,…- shareholders,…- distribution channel members?
– Metrics-related queries: These information requirements must be operationalized into clearly defined metrics. One must decide what metrics to use for each piece of information being gathered. Are these the best metrics? How do we know that? How many metrics need to be tracked? If this is a large number (it usually is), what kind of system can be used to track them? Are the metrics standardized, so they can be benchmarked against performance in other organizations? What are the industry standard metrics available?
– Measurement Methodology-related queries: One should establish a methodology or a procedure to determine the best (or acceptable) way of measuring the required metrics. What methods will be used, and how frequently will the organization collect data? Do industry standards exist for this? Is this the best way to do the measurements? How do we know that?
– Results-related queries: Someone should monitor the BI programme to ensure that objectives are being met. Adjustments in the programme may be necessary. The programme should be tested for accuracy, reliability, and validity. How can one demonstrate that the BI initiative (rather than other factors) contributed to a change in results? How much of the change was probably random?