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Technology

Unlocking the value of IoT data analytics for your company

Untitled design 67 - Global Banking | Finance

By Alexey Chalimov, my CEO and a founder Eastern Peak.

A lot of business executives believe digital transformation is all about undergoing a hardware refresh and implementing smart devices that add business value. What really puts your company ahead of competitors, though, is the data these devices collect and the insights it brings.

Nowadays, IoT data analytics are increasingly applied in a vast number of industries. Surely, market giants have been the first to embrace data analytics with companies like Amazon, Microsoft, and Salesforce leading the pack. SMB companies, however, haven’t yet fully unlocked the value of data and its true potential.

In this article, we will talk about the benefits of IoT data analytics, and how to harness it to create a true competitive advantage. Read on to learn more!

What is IoT Data Analytics, and Why Does it Matter?

Applied in IoT, data analytics refers to the use of tools and methods for gaining insight from data generated by interconnected devices. While smart IoT sensors capture and collect it, it’s the ability to derive business-relevant info that truly defines its value.

Data analytics help gain important insights from data sets varying in volume and structure by analyzing both real-time and historic data. As such, IoT analytics are subdivided into different types, such as, for example:

Streaming analytics: This method applies when you need to analyze a situation in real-time, come up with an immediate response and take timely action. The streaming analytics method, also known as event stream processing, analyzes a large number of real-time events and helps take timely action. This data analytics type applies in urban traffic analysis or financial transactions.

Time series analytics: This type of data analytics uses time-based data to define both established patterns and emerging trends. By analysing a series of historic events, time series analytics find frequent application in weather forecasting and healthcare.

Spatial analytics: This method uses geospatial data to analyze the spatial interrelations between objects. Applied in location based IoT, spatial analytics can assist smart city app users to find parking places, or can be used in smart farming to track livestock.

Prescriptive analytics: A combination of predictive and prescriptive analytics, this method helps to define which action it is best to take in the particular situation. As such, prescriptive analytics can be used to help companies make better business decisions.

More specifically, let’s take a look at the examples of IoT data analytics applications in four different industries:

  1. Agriculture

    In smart farming, sensors and agriculture drones collect data on crop and weather conditions, help monitor livestock health, detect pest infestations, etc. IoT data analytics enables farmers to estimate optimal planting and harvest times as well as better forecast future crops and revenues.
  2. Manufacturing

    In manufacturing, IoT analytics helps companies schedule machinery upgrades, predict supply needs and increase product quality. IoT analytics is also extensively used in smart warehousing, helping reduce spoilage and cut bottom-line expenses.
  3. Smart cities

    In smart city management, IoT data analytics enables the processing of data from street sensors to redirect traffic to less congested areas, in turn, minimizing the number of accidents. Applied in energy management, IoT analytics helps optimize the energy consumption of buildings, detect leakages, and cut down on energy costs.
  4. Healthcare

    In healthcare, the timely interpretation of data from patients’ wearables helps medical personnel quickly and more accurately diagnose their patients, and prevents dangerous conditions from worsening. Analyzing individual metrics also enables physicians to prescribe individual therapy based on a patient’s specific needs.

    The Value of IoT Data for Organizations

    Applying advanced data analytics dramatically reduces the need for guesswork and helps businesses make informed decisions on various aspects of their operations. Here’s how IoT data insights translate into tangible business benefits:

    Improved product quality: companies use data collected from customers to understand their needs and create better business offerings. In healthcare, for example, an individual therapy plan based on unique patient data will prove to be far more effective than conventional, generalized prescriptions.

    Inventory and asset management: applied in asset management, IoT analytics help companies stay updated on exact stock counts and stock conditions; they also alert managers when important company assets need repairs or replacements.

    Data-driven decisions: predictive data in real-time can be used to analyze organizational processes and helps transform them into insights on strategic paths a business should take. Executives no longer have to rely on hindsight or intuition while taking important steps forward.

Improved customer relations: by leveraging sentiment analytics, a business may know exactly how its customers feel about its products and services. This will help tweak communication and marketing strategies and build stronger customer relations.

Enhanced security and fraud detection: companies who choose to integrate IoT data analytics into their security systems will improve their data integrity. Real-time data analytics help detect suspicious activity and eliminate security threats in a timely manner.

Challenges and Barriers to IoT Analytics Adoption

Business leaders are beginning to realize the importance of data analytics for IoT, and are seeking ways to implement it in their organization. However, along the way they will encounter a number of challenges, of which include

1) Infrastructure capacities

The immense amount of data from various sources has to be stored and processed for actionable insights. Enterprise-grade data analytics software needs a robust infrastructure to run on.

2) IoT integration

A lot of organizations use legacy equipment, not necessarily outdated, but it still may not integrate well with IoT devices. Integrating IoT into the company’s IT framework is yet another challenge.

3) Data management

To use IoT analytics effectively, organizations have to decide on the type of data they want to analyze. Most of the time, though, companies are not sure which metrics they want to collect and lack a consistent data strategy.

4) Tech expertise

One more thing that companies often lack is data analytics expertise. Businesses are in dire need of professionals capable of reading and effectively deciphering IoT data.

5) Machine learning challenges

Despite its huge potential, the data that comes from IoT devices is most of the time raw and unstructured. Because of its inconsistency, the cleaning, structuring and validating IoT data for Machine Learning still poses a huge challenge.

6) IoT data security issues

Along with the multitude of IoT devices, the number of security threats also escalates. Every new device is a potential doorway for perpetrators, and organizations are often wary of integrating IoT into their IT systems because of security concerns. As surveys indicate, business leaders list security issues as their top challenge in adopting IoT data analytics.

Creating a Competitive Advantage with IoT Data

Harnessing IoT data requires an infrastructure enhancement and restructuring of some of the organization’s core processes. To create a real advantage with IoT analytics, you must

– Define your business goals
Your goals will determine the type of metrics you will need for analysis and the type of hardware you will need to collect them; the more specific your goals are, the more value you may expect to gain from IoT business analytics.

– Use other data sources
Log files, social media feedback, video recordings from company stores and production sites are just some of the examples of other data that may be subject to analysis. Integrating this data with IoT data and using it to derive business insights will work to your benefit.

– Translate the insights gathered with the solution to everyday business operational tasks
Becoming data driven is actually acting on the information that data analytics can provide to all levels of an organization. Changing your everyday operations in line with the data analytics will involve a major mindset shift.

– Adapt your way of thinking about making business decisions
Your employees will likely resist change until they can truly see the positive impact of data analytics in your organization. Until they do, the C-level management must conduct consistent information policy sessions aimed at explaining the benefits of becoming data-driven and what it will ultimately bring.

Approached from this perspective, IoT data management and analytics will have a truly transformative effect.

How IoT Data Benefits Your Organization

IoT data gives you insights that transform into concrete actions and, subsequently, into distinct competitive advantages. Here’s how IoT data analytics can add a competitive edge to your organization:

Detecting inefficiencies

By monitoring your operations in the real time, IoT analytics can help you detect the bottlenecks in your business-critical processes and determine which set of actions you need to take to eliminate them.

Predictive maintenance

Not only can IoT data analytics monitor your core business processes, it can also track the state of your equipment and notify you before it actually needs maintenance. This enables you to plan for future expenses, and avoid downtime by scheduling timely repairs.

Track energy usage

Tracking energy usage is another way in which IoT analytics can help you cut bottom line costs. By leveraging predictive analytics, you can also plan for future energy consumption and estimate upcoming expenses.

Monitor customer behavior

The use of geospatial data can help you gain insights into customer behavior. For example, by tracking the signals from customers’ smartphones, they can detect which part of your store they tend to visit most, and place your discounts and the hottest sale items there.

In a nutshell, IoT analytics transform the disparate, unstructured sets of data into tons of insights and information that delivers true business value and translates into increased revenue. Partnering with a reliable IoT solutions provider to guide you towards becoming a data-driven company will help you unlock your IoT analytics potential.

Global Banking & Finance Review

 

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