Has Historical Benchmarking Become Obsolete

 The movement of goods from one point to another is complex - the transportation industry is a blend of the networks, infrastructure, equipment, information technology, and employee’s necessary to transport a large variety of products safely and efficiently throughout the nation and around the world. Although generally considered separate transportation entities, trains, planes, ships and trucks are actually part of an integrated network.

With such varieties in how company’s ship their goods, its impossible for two organizations to have the exact same supply chain profile. For this reason, to compare data from one shipper to the next, it can cause misguided recommendations and expectations. Benchmarking data versus industry wide historical rates or against other shippers does not account for future trends and predictive modeling.

In the Big Data Era, companies in a variety of industries, including transportation, more acutely feel the need to collect information most relevant to their businesses. They want to find a way to make decisions based on accurate information at the right time. To achieve this, the development of systems that can transform the data collected information from which to generate actions that benefit the business directly.

Some of these benefits may be:

  • Identifying growth opportunities – internal and external data analysis can help to shape and forecasting business results, allowing identification of the most profitable growth opportunities, as well as some differentiators for business
  • Improving business performance – data analysis facilitates agile planning, forecasting more accurate budgeting and improved planning is an important tool for decision making
  • Better management of risk and regulatory requirements – data analysis allows improved reporting procedures, identification of risk areas such as compliance violation, fraud or reputation damage
  • Using emerging technologies – can identify new opportunities for obtaining information relevant to business management, based on new technologies

Very few companies use the full potential of predictive analysis. On the other hand, this approach often comes into conflict with trying to keep under control and lowering IT costs. Therefore, identifying and capitalizing on available information and identifying information sources that can support the generation of new opportunities have become the main challenge.

Effective integration of predictive analysis in business management has a measurable impact on performance because it allows better planning, weather clearer and more informed decisions, resulting in increased profits, reduce risk and increase business agility.

Using predictive analytics is useful transport companies to ensure that all relevant functions involved in the process so as to obtain an overview and to minimize information leakage. Information about consumers are a typical example in this respect: sales have billing addresses data and record transactions, marketing has information obtained from the analysis of feedback coming from consumers and the logistics department has details on concrete deliveries. All this information can sometimes double or vary from one department to another.

A coherent analysis of all these data can be a challenge, but an accurate analysis and enhanced business can generate added value. 

Stop living in the past and jump on the predictive analysis train…or truck…or ship.

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