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Flooded with Data. Striving for Data-driven Decisions.

Flooded with #BigData. Striving for Data-driven Decisions. Read tips to help you.

  • Data integrations are getting harder, not easier to pull off.
  • As businesses embrace data-driven decision making, it’s no longer enough to simply collect the data.
  • Gone are the days when there wasn’t data available to inform decision makers.
  • Data is increasingly distributed, both inside and outside the organization, and it’s becoming more diverse.
  • There is so much data, that instead of enabling decision making, it can sometimes do the opposite.

As businesses embrace data-driven decision making, it’s no longer enough to simply collect the data.  In fact, there is so much data, that instead of enabling decision making, it can sometimes do the opposite.

@ajlfx: Flooded with #BigData. Striving for Data-driven Decisions. Read tips to help you.

As businesses embrace data-driven decision making, it’s no longer enough to simply collect the data.  In fact, there is so much data, that instead of enabling decision making, it can sometimes do the opposite.

In a recent article, CEOs Must Up Level Their Digital-Decisions Skills, Thorton May highlights that executives need to work on improving the digital-decision making process, affirming that EVERYONE is a digital decision maker.  The underlying message being that organizations must improve digital decision making of non-IT executives.

With more emphasis on evidence-based management, getting the right data to the right people at the right time is critical to empowering everyone to be a decision maker.

The two most critical elements to quality decisions are: the amount of time available to make a decision and the information available to the decision maker.

Gone are the days when there wasn’t data available to inform decision makers. Instead, organizations now have a flood of data residing in multiple systems, in global locations, locked away in spreadsheets or in people’s heads. Now the concern is whether the data sources are credible – or even current.

As a result, data integrations are getting harder, not easier to pull off. Data is increasingly distributed, both inside and outside the organization, and it’s becoming more diverse. Structured data is still important, and now less structured data is becoming more relevant.

But, as consumers, we regularly see the how major brands are mismanaging all this new data—receiving offers that are outdated or irrelevant. Or even worse, multiple versions of the same outdated or irrelevant offer.

For example, if your business operates in the consumer market, social networks have added a layer of unstructured data that offers customer preferences that can improve targeting and boost loyalty.

Many organizations were lured by the promises of data integration that offered to combine data from several disparate sources, and provide a unified view of the data. But like many things in life, timing is critical.  Organizations need to get the right data to the right people at the right time.

In order to do this, organizations need to evaluate several key data integration factors. Below is a short list of important questions to consider.

o Business Considerations: How quickly is data available? What kind of data governance is required? Is the environment stable? How many people want access to the data and how often do they need it?

o Data Source Considerations:  What are all of the necessary data sources? Are my operational systems at capacity? What kind of data cleansing is necessary?

o Data Consumer Considerations: What format does the data need to be reported, and how much data is included in the reporting?

With more emphasis on evidence-based management, getting the right data to the right people at the right time is critical to empowering everyone to be a decision maker.

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You are absolutely right, two key factors: Time and Gathered Information. There are a lot of type of businesses. But, for the ones that fall into the Research and Development or Integrators and Developers, we find, time schedule tied to the type of project we are involved, setups that are very unique for the main purpose, test equipments, software, etc, that need a very unique data collection process, to be in the correct time schedule, and to be inside the calculated budget. Thank you for sharing your very informative post. Deeply appreciated.

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Flooded with Data. Striving for Data-driven Decisions.

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