At the heart of digital transformation is analytics, the means through which companies can leverage data to remain viable and succeed in rapidly changing markets, perhaps even leapfrogging their peers. The purpose of this selection guide is to help owner-operators discover how Operational Analytics can improve their business, if they chose the right technology and supplier.
Operation Analytics Selection Overview
More than ever, digital transformation is mission critical for industrial, infrastructure, and smart city organizations’ health and viability, both short- and long-term. New business processes, services, and models are being pursued.
This energy and investment are a rational response by organizations (and even countries) to digital economies that present new and very real opportunities. Digitally transformed organizations will be able to transition to and thrive in digital economies, making digital transformation a matter of “when,” not “if’.
While analytics have been in use in industrial companies for decades, many advances have been made in this field within the last 10 years, with techno-logical improvements driving step change into the market. Currently, the market is very fluid, as solutions are now offered that leverage and combine data, math, software, and even hardware in new ways. Consequently, the vendor universe has exploded as many new and legacy providers fight intently for market share.
With the availability of more tools and better methodologies, an increasing number of companies are now starting to apply Operational Analytics to production operations that were difficult in the past to justify on an ROI basis. In addition, more transition and startup sequencing technology is being integrated with control applications to provide safer and more profitable operations. Incorporating analytics in the Operational Technology (OT) applications can also prove to enhance the predictability of the production and improve overall business value.
Operational Analytics Selection Strategic Issues
The following are a few of the strategic issues specifically covered in the Operational Analytics for Industry Selection Guide:
The Pursuit of Benefits of Analytics Require Persistence
Invest, experiment, and persist in Operational Analytics. Scale and ROI will follow as wisdom accumulates, and it is likely you will need to adjust your investment strategy as you increase organizational competency.
Strategies for Operational Analytics Will Be Different from the Past
Data strategies, cybersecurity, and governance are needed, but they will look different from the past. These new policies need to account for shared data ownership among business units and IT and OT, democratized use of analysis by a broad group of users, internal and external data sources, and cyber/physical infrastructure.
Rethink Your Approaches to How You Operate Your Business
Industrial organizations need to rethink deeply entrenched approaches to how they organize their work cultures and operate their businesses. This begins with leadership, which needs to evolve beyond transactional decision-making so traditionally prevalent in industrial markets. Those that achieve success will instill a digital-first industrial work culture, accounting for (not penalizing) a workforce with different levels of digital comfort.
Additional Operational Analytics Strategic Issues
- Resolve to commit resources and invest as digital transformation requires time, patience, effort, and, most importantly, a culture shift
- Identify suppliers that match your long-term vision
- Be open to suppliers of all sizes
- Finding the correct analytics operating model
- Understanding sustainability methods
- Leveraging new technologies like Cloud, virtualization, and new licensing models
- Integration with complementary process identification tools
- Formalize organizational structures for technology and operational experts to work together
- Separate leaders from followers
Table of Contents
- Major Trends
- Industry Trends
- Regional Trends
- Strategies for Success
Partial List of Selection Criteria Topics
- Business Goals
- Data modeling and processing
- Data Collection, Connectivity and Storage
- Solution Delivery
- Future Development
Market Size and Forecast
- Revenue by World Region
- Revenue by Deployment Type
- Factors Contributing to Adoption
- Factors Inhibiting Adoption
Leading Supplier Profiles
For More Information
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