IoT and analytics are here today – when do you embrace?

Imagine a car that never breaks down. Imagine that it does not need service just in case. Imagine that your car would notify you, based on its real condition, when it is time to take it to service…

Is IoT the driver of our economy?

The above car example paints a picture of what IoT enables. IoT, which is short for Internet of Things, and is sometimes also referred to as the Internet of Everything, is one of the biggest hypes right now – and for a reason. By collecting and analyzing data from processes and devices, and using it in the right way, huge efficiency benefits can be gained.

However, it is estimated that only less than half of the Finnish companies have taken some action regarding IoT. Most companies are still trying to understand the scenarios and figure out how IoT will impact their industry, and how to grab this challenging opportunity.

But there is no time to wait! So roll up your sleeves and get busy!

Technology leaps that change business processes, or even entire business models, always require a solid knowledge base, familiarization and strategic decisions. Proceeding step by step is more often wiser than a big jump forward.

Data is already being generated from lots of different sources – devices, production processes, services, products, users, environments, etc. The challenge is to enrich the data and turn it into information that serves the business and improves process efficiency. On the other hand results must be shown as soon as possible – it is not an alternative to wait until the following strategy cycle.

A real-life example on how to put IoT into practice in an agile and fruitful way

In the pulp and paper industry, a critical business factor is the maintenance time of the pulp machine: by optimizing the timing and the content of the maintenance, the efficiency and the production costs of the entire production line are effected. Valmet - the leading global developer and supplier of technologies, automation and services for the pulp, paper and energy industries – did early on identify that analyzing and optimizing the maintenance of the pulp machine is an opportunity to add value for the customer.

Houston Analytics’ and Valmet’s joint project resulted in a significant growth of Valmet’s customers’ efficiency. This is possible by producing continuous analytics about the pulp machines.

”Thanks to Houston Analytics’ approach we were able to quickly identify the problems and the solutions. In addition, we were able to combine the knowledge of both parties in the project.”

Director Pekka Linnonmaa

The steps towards an automated data-driven leadership:

  1. Understanding the current situation with the help of analytics
  2. Fast results by building an agile model for data-driven leadership
  3. Efficiency by automating the approach.

Get the picture of the situation using analytics

The right and easiest way to start proceeding towards an automatic data-driven leadership is a deep dive into the existing data. The objective is clear and simple: to find and enrich the data and turn it into information that supports business decision making. In this way business critical questions can be answered and efficiency-increasing prediction models can be understood.

Time needed for the situation-mapping will range from a few weeks up to one month, depending on the extent of the environment. This deep dive brings the facts of the situation to the table, which makes it easier to form a common view on the way forward. As a bonus this work will identify the bottle necks of the processes.

Fast results with agile progress

For most people IoT, and especially the use of analytics, brings to mind large-scale automation processes and years of efforts – before seeing any results at all.

A strong belief carries surely even a very long project all the way to the finish-line, but from a business perspective fast results and an agile approach confirm the belief that the progress is on track.

After mapping the current situation, it is time to build the data-driven leadership model. In order to succeed, a close co-operation between the business and analytics is needed. In the implementation phase, agility is key: critical information can be made available for the business processes immediately without an automation process. Prospecting models enabling more efficient operations, for example in maintenance or other processes, are accessible straight away after the modeling process.

Automation brings efficiency

When the model for a data-driven leadership has been created, the automation of the approach can be done step by step. The basic principle “the big wins are made early, the small ones can be made later on” is also a good guideline for the automation project. The mission of this phase is to make information easily accessible for the business decision maker.

In a successful IoT project the right information is made available to predict and streamline processes. Best practice is to proceed with one unit at a time, listening to the user’s needs.

Juha Raunama is the Solution Director of Houston Analytics [P1] . He has extensive experience in using information for business decision making in different industries.

Houston Analytics is an analytics company started by experts on data-driven leadership. By linking data to business decision-making Houston Analytics is guiding its customers to market leaderships in their industries.