Our Approach to Project Management
Context - The reason for constructing any forecast stems directly from context, in most cases, client decisions. The type of client, the nature of the decision, and the characteristics and particulars of the technologies and markets studied provide context. If a forecast is the answer, the model is the question. Of course, how that question is phrased will ultimately determine the appropriateness and accuracy of the answer. Context is an expression of the quantitative and qualitative characteristics of a market as defined by the client, and is manifested in choices about metrics, taxonomies, and methodologies.
Collaboration - Designing and developing market forecast models requires two sets of complementary core competencies, those of the Model Builder encompassing the mathematical, computational, and forecast methodologies, and those of the Knowledge Analysts encompassing qualitative assessment of the factors and trends influencing the products/services and markets being modeled.
The very best Knowledge Analysts are extraordinary people, experts in their area, and as such, think at levels of abstraction that are not easily quantifiable. They often develop their understandings intuitively rather than computationally. The single most important task of the Model Builder is to build a bridge between the Knowledge Analysts qualitative assessments of the market and the quantitative requirements of the model.
Clarity - Making choices from the large and growing inventory of available methods, approaches, and mathematical models requires that the Model Builder develop and maintain a clear understanding of the nature of these tools, their assumption, limitations, and strengths. Attaining and maintaining clarity requires the application of knowledge from five different domains:
- Management of the collaborative design and development process.
- Technology markets, products or services.
- Forecasting methodologies.
- Mathematics and statistics.
- Modeling Application (Excel, Access, VBA, SPSS, etc.)
Daniel Research Group constructs the most appropriate models and forecasts by applying an analytical framework to guide the choices about taxonomies, metrics, method, as well as model architecture and topology.