Both business and strategic planning are changing at lightning speed. If your company follows a BIG DATA strategy, the second quarter of 2018 is the perfect moment to review it and make the necessary changes!

 

  • Keep in mind that strategic planning in 2018 will no longer be the same. Implementing plans requires reviewing them over time and making adjustments.
  • Today, strategic planning evolves at the same pace as business. Managers must constantly return to plans in light of business and market changes.
  • Now is already an excellent moment to analyze your 2018 big data plan. Use our tips.

 

Here are five areas to pay attention to:

1. Data storage for technology.

Data storage for new technologies

As companies collect data from drones, sensors and similar technologies, internet bandwidth limitations will mean storing data locally rather than trying to transmit all data in real time to a central location. In 2018 it was widely believed that much of the collected information would be sent to public clouds for storage. That is still the case, but bandwidth limitations also affect cloud storage. Adjusting the strategy for many companies will mean a return to traditional distributed storage, in which collected data is stored on servers and/or drives.

 

2. Working with cloud service providers

Working with cloud providers

Especially among small and medium-sized companies that move their applications to cloud hosting and limit their on-site data center to maintaining infrastructure and networks. With this shift, disaster recovery plans for large data sets also need to change to assure business partners that providers meet corporate governance standards and are able to perform disaster recovery and failover when needed.

 

3. Defining your company's ROI

Defining ROI in a Big Data strategy

Given the pace of business change, there is no longer any point in setting return on investment (ROI) once and for all. Until now it was set at the start of considering or buying technology, and then the return on investment was checked again. You should be constantly prepared for change, especially if ROI starts to decline. Let's trace an example of using IoT technology that tracks foot traffic in brick-and-mortar stores and helps sales managers by placing the most sought-after products in visible areas of the store. This technology no longer delivers the same effect, because customers are "moving" from brick-and-mortar to online stores. Validating ROI is now a continuous IT process that should be reviewed at least once a year and that must be included in the company's strategic plan.

 

4. How company effectiveness is assessed

Assessing effectiveness and implementing AI

Like ROI, the measurement of BIG DATA key performance indicators may also change. For example, internal research may reveal that instead of assessing customer satisfaction through social media, the company may notice an increase in the number of product defects. An IoT sensor alerts about product defects in order to improve customer satisfaction. Continuous vigilance in this area should be written into the strategic plan. Ideally, performance assessment should be reviewed at least once a year.

 

5. Implementing artificial intelligence

Everyone knows how artificial intelligence can help their companies, but only a few brands successfully introduce this technology into their business processes. Leaders must identify business use cases in which these technologies can deliver growth in results, and then test the technology in small pilot projects. This research and development goal should be written into the strategic plan.

Summary

Big Data is evolving from simple information collection into a strategic tool that requires continuous updating. In 2018, approaches to data storage are shifting toward distributed solutions, the role of cooperation with cloud providers is growing, and cyclical ROI verification is becoming more important. It is also becoming necessary to flexibly define business performance indicators, which can quickly become outdated, and to pilot the implementation of artificial intelligence in key processes. Success will go to those companies that make these areas part of a continuous strategy rather than a one-off plan.