Stop Debating the Future of Data and Start Using It Better

2 minutes

The future of content (attributes, data, and information), is a hotly contested topic among visionaries and futurists. Convincing arguments exist for both improvement and decline. Rather than focusing on that debate, this discussion will focus on what remains constant, which is how to maximize value from content regardless of its future state.

The future of content can get better or worse in terms of quality and quantity. Do we really need to predict this future?

Maximizing How We Benefit from Content

Essentially, we need to answer three main questions whenever we work with content and Advanata was built to address these questions.

Regardless of the future state of content, three questions will always need to be answered. First, what is the need content? Second, where to find this content. Finally, is this content valid. Advanata provides the technology to answer these questions.

How Advanata Technology Handles Content

Requiring only a single forecast type significantly reduces problem complexity and content needs, while enabling problem experts without analytics expertise to help validate results.

Data effectiveness methodology provides a simple underlying structure for all solution frameworks consisting of a source, destination and rate between them. This allows for useful problem expert involvement in determining content suitability and reducing the depth of content required since only a rate is needed.

A highly flexible solution framework defines and limits the required content while supporting content from different sources.

The business problem framework contains all content requirements for the problem. The framework can be easily modified to capitalize on available content thus adjusting to different alternatives. Customer definition of the framework restrains the needed content thus reducing its breadth.

Finally, using information enables content from multiple sources while allowing the problem expert to approve the final parameters. Note that what we require is information from the future, which does not yet exist, so we can only rely on forecasts to parameterize the solution model.

The inductive approach allows for sourcing content using four different methods allowing for obtaining content from the source with the best accuracy and/or availability. Customer (problem expert) provides guidance and approval on results from the different methods.

Advanata Technology in Action

A simple yet flexible solution framework limits the required content while supporting inputs from multiple sources and ensuring the problem expert has the final say on the problem composition.

A customer would like to find the optimal warehousing solution for their manufacturing business. The solution framework constrains the options and reduced problem breadth. The framework can be adjusted according to the availability of content and the customer has final approval over the framework and the parameters.

The solution framework is composed of a simple underlying problem structure that makes the analytics problem manageable and verifiable.

A customer wants to find the best way to distribute their farm products. From the solution framework excerpt, the only needed parameters are limited and thus problem depth is reduced. Analyst can easily understand the problem and estimate these parameters. Similarly, the customer can validate these parameters and provide useful feedback due to the clear framework.

Optimal Actions Regardless of the Future

The future of content is a fascinating but ultimately irrelevant issue for solving business problems. Regardless of what happens, the same questions must be answered. They may become easier or harder, but they will remain, which is why a robust framework is needed to maximize the value of whatever content exists in solving our essential problems.

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