A business plan, in its essence, is the process of mapping out with as much accuracy as possible, what the future of an enterprise or business initiative will be. To forecast effectively, the business plan strategist must intelligently evaluate and synthesize available industry and market data into a plan of action supporting credible market and financial projections. To do so effectively, it is paramount to efficiently differentiate between business data and business intelligence.
Data, in an Internet world, is the vast collection of web pages, online databases, list programs, research reports, think tank and scholar academic white papers and presentations and the like that is available via simple Internet searching and browsing. While much of this data has credible value, its mere abundance creates significant challenges when attempting to synthesize it into meaningful business intelligence. Quite simply, in a world where data is ubiquitous, proper interpretation and analysis of this data into business intelligence that can be acted is paramount.
How does one accomplish this? Growthink's recommendation is to first clearly define the key business questions about which one seeks guidance. These are questions such as:
1. What is the decision-making process/decision-weights for a prospective customer for my product/service?
2. What specifically will my company need to do to motivate a buyer to switch from their current vendor/procurement channel to my offering?
3. How many customers exist in the marketplace for my product/service offering?
4. What is their demographic/psychographic makeup?
5. How price sensitive, (both in response to price increases and decreases), are they?
With a thorough business question list firmly in hand and prioritized, the next step is to set a timeline for the collection of data. This is critically important as the very nature of research in an Internet environment is its intrinsic open-endedness. On virtually any business intelligence question, the Internet creates an information-gathering dynamic that will naturally expand itself well-beyond its allocated resource. As such, the importance of placing a time deadline on data collection efforts is a necessity in driving the process toward results that move entrepreneurs, and their potential customers, to action.