Analytics Maturity Model for IoT

Nearly every Internet of Things industry survey and market forecast has suggested that there is plenty of interest in the potential value of connecting products and even more reasons to pursue advanced IoT strategies with analytics.

Yet, candid conversations with corporate executives at many major enterprises and leading technology companies reveal that it has been a challenge to capitalize on IoT opportunities and generate substantial business value.

The Analytics Maturity Model provides the path to gaining business value from IoT

Analytics is one of the keys to getting value from IoT applications. And success with IoT analytics comes when an organization has the ability to proactively seize opportunities to drive new revenue or minimize costs.

Getting to the proactive stage in analytics is not necessarily simple and does require a process or methodology to succeed. That is where an analytics maturity model comes into play. It provides a process for how to get there. There are five key steps in the process. The faster companies move thru the model, the bigger, better, faster the return.

The Five Step Analytics Maturity Model for IoT

The Analytics Maturity Model

Figure 1. The Analytics Maturity Model

  1. Connected: The first step is to get everything connected and all the critical data ingested into an integrated system where it can be processed and analyzed.
  2. Aware: The next step is to gain insight into critical information such as machine location or maintenance history of the connected equipment
  3. Reactive: Once organizations have insight into important information, they can take advantage of the information and take action. Faster response and resolution times are examples of this.
  4. Predictive: Being able to anticipate events and take preventative action is the transformational stage of the process. Planned down time and updated maintenance schedules or a demand generation campaign based on a specific event are examples of this stage of maturity
  5. Proactive: When the system itself is able to predict and prescribe that actions be taken at critical times to prevent downtime and capture previously unrecognized value, organizations have reached the ultimate goal. A maintenance alert based on certain parameters with instructions for a technician or a purchase recommendation to a customer at the perfect time are examples of this.

Analytics are key for getting value from IoT, the Maturity Model paves the way
Business leaders are having a challenge getting their head around how to gain value from IoT.

At the same time, they need to take action to gain and maintain competitive advantage. Predictive and prescriptive analytics that drive intelligent actions are essential to driving business value from IoT. The maturity model provides the path from where many companies are today to the future of IoT analytics.

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Analytics Maturity Model for IoT

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