Secondary Data is data or information that is already available

Secondary Data is data or information that is already available. This data is collected by a person or organization other than the use of the data. Advantages of secondary data are that it is cheap and inexpensive. It is easily accessible. It is already available. It saves time and efforts. It is unobtrusive. It avoid data collection problems and it provides a basis for comparison.Disadvantages are related to the credibility of the source who has published this info and the small nuances that may not fit into your research objectives. Another disadvantage can be that the data might be outdated. Similarly you have no control over the quality of data and you do not know how authentic the measures used for data collection have been.

The main sources of external secondary sources are (1) government (federal, state and local) (2) trade associations (3) commercial services (4) national and international institutions.

Government statistics

These may include all or some of the following: Population censuses Social surveys, family expenditure surveys Import/export statistics Production statistics Agricultural statistics.

Trade associations

Trade associations differ widely in the extent of their data collection and information dissemination activities. However, it is worth checking with them to determine what they do publish. At the very least one would normally expect that they would produce a trade directory and, perhaps, a yearbook.

Commercial services

Published market research reports and other publications are available from a wide range of organisations which charge for their information. Typically, marketing people are interested in media statistics and consumer information which has been obtained from large scale consumer or farmer panels. The commercial organisation funds the collection of the data, which is wide ranging in its content, and hopes to make its money from selling this data to interested parties.

National and international institutions

Bank economic reviews, university research reports, journals and articles are all useful sources to contact. International agencies such as World Bank, IMF, IFAD, UNDP, ITC, FAO and ILO produce a plethora of secondary data which can prove extremely useful to the marketing researcher.

In primary data collection, you collect the data yourself using methods such as interviews and questionnaires. The key point here is that the data you collect is unique to you and your research and, until you publish, no one else has access to it.

There are many methods of collecting primary data and the main methods include:

questionnaires

interviews

focus group interviews

observation

case-studies

diaries

critical incidents

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classification of data

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This, of course, makes the assumption that the past will repeat. It also assumes that any trends Quantitative forecasting techniques are generally more objective than their qualitative counterparts. Quantitative forecasts can be time-series forecasts (i.e., a projection of the past into the future) or forecasts based on associative models (i.e., based on one or more explanatory variables). Time-series data may have underlying behaviors that need to be identified by the forecaster. In addition, the forecast may need to identify the causes of the behavior. Some of these behaviors may be patterns or simply random variations. Among the patterns are:

Trends, which are long-term movements (up or down) in the data.

Seasonality, which produces short-term variations that are usually related to the time of year, month, or even a particular day, as witnessed by retail sales at Christmas or the spikes in banking activity on the first of the month and on Fridays.

Cycles, which are wavelike variations lasting more than a year that are usually tied to economic or political conditions.

Irregular variations that do not reflect typical behavior, such as a period of extreme weather or a union strike.

Random variations, which encompass all non-typical behaviors not accounted for by the other classifications.

Among the time-series models, the simplest is the nave forecast. A nave forecast simply uses the actual demand for the past period as the forecasted demand for the next period., seasonality, or cycles are either reflected in the previous period's

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As spring moves to summer, the forecast should be for warmer and sunnier weather. What is the forecast for your business? Is the outlook sunny or cloudy?Do you know what sales you can expect, whether for a team of sales people or within your own business or practice? How do you feel about putting together a forecast? How do the others in your business feel? I wonder why you have these feelings?Forecasting is vital for any business well, accurate forecasting is vital!! This is true for professional services as well as commercial organisations. How often are your forecasts accurate? Inaccurate forecasting carries all sorts of hazards. Whether there is a tendency to be too optimistic and sunny with your forecasts, or too downbeat and understating it, there are potential problems for the business. Are people encouraged, or allowed, to be pragmatic about their forecasts or do they feel as though they have to tell you they will do well? Do you tend to think that there are too many factors outside of your control and so it is not worth doing anyway?Why does it matter? Apart from the reality that sales, whether to existing or new clients, are the lifeblood of your business! Being too optimistic about potential sales can lead to various issues anticipating revenues which will not happen, planning resources such as people and products, problems with cash flow, panic management! The other end of the equation, under-estimating has its own problems too! Although it can feel good to see sales coming in which were not anticipated, think about the problems they might cause within your own business. Cash flow problems of a different sort, the need to get the resources at short notice, quality of customer or client service and response are all probabilities. Becoming more accurate with your forecasts will help you run a smoother and more profitable organisation.How do you approach forecasting sales? Tea leaves, roll of the dice, check the stars or ask others for their expectations? There are some basic principles to consider or follow and a variety of methods you can use to help and they should prove more reliable then the ideas above! Although we are presuming you are already an established business, many of the principles will apply even for new start-ups.First point look at your records for the previous couple of years and do some analysis.