Most trading companies depend on a large amount of data for their trade operations. For the proper management of such a large business data trading companies uses wide range of software programs, such as Excel, Access and different database applications in various departments throughout their organization.

In a very broad term, Trade Intelligence represents the standard tools and systems that play a key role in the tactical planning process of an trade organization. These systems let a company to gather, store, access and analyze corporate data to aid in decision-making. Generally these systems will illustrate trade intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few.

Trade intelligence is a very broad topic of study. For a successful trade it is important to understand the factors of trade intelligence and learn how analyze and use the data created by this methodology. Here is some more information on how these factors helps in the decision making process of a businesses.

Customers: No business company can survive without a customer. Companies are required to sell their products and services. In such as scenario, the concept of trade intelligence helps companies to understand their customer in a better way, looking at their preferences, helping businesses adapt to their customers demand.

Competitors: It should be noted that satisfying the needs of customer is not enough for a business company; they also have to keep an eye on the market competitors. In today’s world, a firm must constantly evaluate the effectiveness of their competitors and choose smart schemes that not only hold their competitors at bay, but also grow their own businesses market share.

Trading Partners: Trading partners are one of the very important factors in the establishment and success of any essential to any company, whether it is suppliers, payment processing companies, customer support companies or delivery companies that help your business throughout its cycle. One should make sure that all businesses partners associated with business are in balance.

Economic Environment: Another way that trade intelligence can help an organization is by taking into consideration key economic indicators such as consumer spending, inflation, unemployment, upturns and downturns in the economy, etc. Without trade intelligence, your organization can't process information effectively in order to modify strategies that fit the current economy.

Internal Operations: Internal operations are basically related with the day to day operations of an
organization. For a success trade it is important for an organization to evaluate strength and weakness on a daily basis. Without decent foresight, you might make hasty decisions such as commit to new spending or paying off debt when your business could allocate those funds some where else. Proper analysis of internal operations also helps a trading company to evaluate how much profit a company is making.

The Five Key Stages of Trade Intelligence

The key factor of a trade intelligence of are as follows-

1. Data Sourcing

2. Data Analysis

3. Situation Awareness

4. Risk Assessment

5. Decision Support

Data sourcing: Trade intelligence is about extracting information from multiple sources of data. The data might be: text documents - e.g. memos or reports or email messages; photographs and images; sounds; formatted tables; web pages and URL lists. The key to data sourcing is to obtain the information in electronic form.

Data analysis: Trade intelligence is about synthesizing useful knowledge from collections of data. It is about estimating current trends, integrating and summarizing disparate information, validating models of understanding, and predicting missing information or future trends. This process of data analysis is also called data mining or knowledge discovery. Typical analysis tools might use:-

• Probability theory - e.g. classification, clustering and Bayesian networks.

• Statistical methods e.g. regression.

• Operations research - e.g. queuing and scheduling.

• Artificial intelligence - e.g. neural networks and fuzzy logic.

Situation awareness: Trade intelligence is about filtering out irrelevant information, and setting the remaining information in the context of the business and its environment. The user needs the key items of information relevant to his or her needs, and summaries that are syntheses of all the relevant data (market forces, government policy etc.). Situation awareness is the grasp of the context in which to understand and make decisions. Algorithms for situation assessment provide such syntheses automatically.

Risk assessment: Trade intelligence is about discovering what plausible actions might be taken, or decisions made, at different times. It is about helping you weigh up the current and future risk, cost or benefit of taking one action over another, or making one decision versus another. It is about inferring and summarizing your best options or choices.

Decision support: Trade intelligence is about using information wisely. It aims to provide warning you of important events, such as takeovers, market changes, and poor staff performance, so that you can take preventative steps. It seeks to help you analyze and make better business decisions, to improve sales or customer satisfaction or staff morale. It presents the information you need, when you need it.

Tools of Trade Intelligence

1. Digital Dashboards also known as Trade Intelligence Dashboards, Enterprise Dashboards, or Executive Dashboards, these are visually-based summaries of business data that show at-a-glance understanding of international trade conditions through metrics and Key Performance Indicators (KPIs).

2. Online Analytical Processing, commonly known as OLAP a capability of some management, decision support, and executive information systems that supports interactive examination of large amounts of data from many perspectives.

3. Reporting software generates aggregated views of data to keep the management informed about the state of their business.

4. Data mining - extraction of consumer information from a database by utilizing software that can isolate and identify previously unknown patterns or trends in large amounts of data. There are a variety of data mining techniques that reveal different types of patterns. Some of the techniques that belong here are Statistical methods (particularly Business statistics) and Neural networks as very advanced means of analyzing data.

Contact Information

Mr. Prashant kumar  
Tel: Direct : 91-11-40703045
Tel: Board : 91-11-40703000
Fax: 91-11-40703060
Email: intelligence-reports@infodriveindia.com