Internet of Things (IoT) has become one of the biggest challenges for IT departments to manage today, according to Info-Tech' Research Group latest findings. With IoT solutions becoming increasingly common, organizations must move quickly to adopt new, IoT-focused ways to collect and analyze data and automate processes and actions.
The firm's research indicates that one of the most common mistakes organizations make when working with an IoT vendor is waiting to include the IT team in the process until the IoT solution is ready to go live, rather than including the team from the beginning. This causes challenges with integrations, communications, and access to data.
"Most of the solutions available are designed to perform a specific function within the parameters of the devices and applications designed by vendors," says Sandi Conrad, principal research director at Info-Tech Research Group. "As these specific use cases proliferate within an organization, the data collected can end up housed in many places, owned by each specific business unit, and used only for the originally designed purpose."
One of the primary reasons IoT management is a challenge for IT teams is that, as many devices suddenly enter the organizational environment, IT must ensure each device is inventoried, added to lifecycle management practices, and secured. The large volume of devices and lack of insight into vendor solutions makes it significantly harder to plan upgrades and contract renewals as well as guarantee that security protocols are being met.
"In order to make these dramatic shifts to using many IoT solutions, IT needs to look at creating an IoT strategy that will ensure all systems meet strategic goals and enable disparate data to be aggregated for greater insights," adds Conrad.
IoT solutions may be chosen by the business, but to be successful and meet their requirements, a partnership with IT will ensure better communications with the service provider and provide several other benefits, such as:
Info-Tech recommends that if an loT steering committee doesn't already exist, or if the committee's mandate will not include IoT, to consider creating such a committee to set standards and processes and to quickly evaluate solutions for feasibility and implementation.
Interoperability of multiple IoT systems and data will be required to maximize value.
What should I build? What are my concerns?
Where should I build it? Why does it need to be built?
| DATA MODEL | ——› | BUSINESS OPERATING MODEL | ||
| Data quality Metadata |
Persistence Lifecycle |
Sales, marketing Product manufacturing |
Service delivery Operations |
|
|—› |
BUSINESS USE CASE |
‹—| |
||
| Customer facing | Internal facing | ROI | ||
| ˆ | |
||
| ETHICS | ||
| Deliberate misuse Unintentional consequences Right to informed consent Active vs. passive consent |
Bias Profit vs. common good Acceptable/fair use Responsibility assignment |
Autonomous action Transparency Vendor ethical implications |
| ˆ | |
||
| TECHNICAL OPERATIONAL MODEL | ||
| Personal data Customer data Non-customer data |
Public data Third-party business data Data rights/proprietary data |
Identification Vendor data Profiling (Sharing/linkage of data sets) |
How do I operate and maintain it?
1. SECURITY
2. COMPLIANCE
3. OPERATIONAL STANDARDS
4. TECHNICAL OPERATIONAL MODEL
How should it be built?
This diagram shows 'Data Normalization' from physical to virtual and 'Instructions' from virtual to physical.
To learn about all phases of creating and implementing an IoT strategy, from defining your governance process to defining the intake and assessment process to preparing for a proof of value, download Info-Tech's Create and Implement an IoT Strategy blueprint.
Article published by icrunchdata
Image credit by Getty Images, Moment, Yuichiro Chino
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