Data And Why It Is Important

Data are actually just bits of factual information. Numerical data are bits of factual information stated as numbers – indicating quantities, such as counts or measurements. Data that are somehow related to each other, enough so they can be compared, can be statistical data.

Business Decisions and Data

Today, changes occur rapidly. To take advantage of these changes, decisions with long-term implications must often be made quickly. Information is vital. Farmers, for example, must be conscious of market needs and must determine how to react to changing economic, political, and social situations to maintain a competitive advantage and remain profitable.

The question is whether our decisions, based on the information we receive, are making things better, having no effect, or making things worse. We will argue that decisions based on numerical information or data, if the data are collected and processed correctly, typically make things better.

Consider the following situations where decisions seem to naturally depend on data.

A survey of customers indicates that a bank should improve the quality of its customer service. What should the bank do? The first step might be to concentrate on the teller-customer interaction. To improve service, the bank might use data on the lengths of time for teller transactions, the number of customers waiting in line, the teller error rates, the costs of handling exceptional requests, the amount of teller turnover, and so forth. These data could then be used to examine the entire process of providing customers with exceptional service.

Capital for company projects can be raised by selling bonds or issuing additional shares of stock. The choice of one or the other (or some combination of the two) depends, to some extent, on the likely behaviour of interest rates, inflation, tax policy, and other economic variables. These variables are described by sets of numbers or data. Interest rates may be given by a set of short-term (6-month certificate-of-deposit) and long-term (10-year Treasury note, 30-year Treasury bond) rates. Tax policy may be characterized by a set of tax brackets.

A drug company has developed a drug for combating the HIV virus that, according to the company, is more effective than current drugs and has fewer side effects. Before the company can produce and market the drug, however, it must receive government approval. Approval from the Medical Council requires that the company successfully complete a set of clinical trials. That is, the proposed drug must be tested, under carefully controlled conditions, on groups of human subjects. Data on the effectiveness and side effects must be collected, analysed, and reported as part of the company's case. As part of its review, the Medical Council must decide whether the company's claims are sound. Were the data collected properly? Were the data interpreted correctly?

Sound decisions involve the collection of pertinent data and the application of appropriate techniques for extracting the information contained in the data.

Agricultural Data Collection

The process of gathering information, such as profit margins per cultivar, pest and disease infestations, weather and climatic information, rainfall, costs, economic conditions – and analysing it to be able to find patterns that will help us work more efficiently, sustainably and profitably on a farm.

Agricultural data could be any of these items listed below:

• Occurrence of pest and disease infestations
• Weather and climatic information – year on year
• Rainfall & Soil sample data
• Costs of agricultural inputs
• Yield data
• Prevailing economic conditions in the sector, country and internationally.
• Production costs per crop
• Soil and fertilisation costs and applications
• Pest and Weed Control application programs and statistics
• Non-target species data
• Crop quality margins
• Agronomic data
• Profit margins per cultivar / per crop / per block / per orchard / per Hectare
• Agricultural photographic data

The Reasons Why We Would See To The Accurate Collection Of Agricultural Data And Report On It

Patterns of the environment include rainfall, climate, dry cycles, original vegetation, seasons, movement patterns of animals, etc. Processes of the biophysical environment include the interaction and the relationship between food webs, human activities, soil, climate, water, plants, animals and solar energy.

It is always useful to have detailed records and data in order to ensure that we make optimum decisions in order to maximise profits, production and quality, whilst keeping risks and problems to a minimum. Detailed records of data need to be integrated, compared and correctly and accurately reported on, in order to make data useful and applicable in an agricultural setup.