Welcome to STRYVE, the first Demand-Driven Maintenance (DDM) software. STRYVE seeks to revolutionize the way you build and manage your budget by connecting the business with maintenance. It is not just another Computerized Maintenance Management System (CMMS) or Reliability tool. Nor is it a simple dashboard or spreadsheet. It is an intelligent software, designed specifically for asset heavy industries, that optimizes your maintenance performance to the specific demand of your production unit in multiple ways.
STRYVE operates dynamically in the past, present, and future to give you the most complete picture of your performance.
Key benefits
How it works
STRYVE is unique in the way that it uses data you already have to draw insights that you can’t see in any other system. STRYVE integrates at the cloud level of your IT infrastructure. The robust data model that supports this integration allows STRYVE to link these systems at the lowest common level, typically individual equipment. We support upload of data through basic spreadsheets, with options to fully integrate into existing Enterprise Resource Planning (ERP) and CMMS software.
The cost data from ERP systems is utilized to trend, analyze, and visualize trends. STRYVE imports existing equipment data from your CMMS and replicates your global asset hierarchy. It also imports and analyzes any equipment maintenance strategies you have, in order to build cost forecasts and future budgets. Reliability data is uploaded and utilized for failure probability distributions, risk forecasting, and asset strategy adjustments. Our optimization algorithms dynamically adjust to the specific constraints you set for your business.

The analytical capabilities of STRYVE are powered by intelligent algorithms and Qlik Sense Data Analytics ©. These algorithms provide data insight and allow STRYVE to forecast even further into the future than your generated data. For the first time, your site, business line, and even entire company can manage costs before they are incurred with STRYVE´s smart data model and intelligent algorithms.
Why are Demand Driven algorithms needed to solve these problems?
The Demand Driven Maintenance algorithms developed exclusively for STRYVE use a variety of maintenance task specific inputs to optimize existing equipment strategies based on the overall asset strategy of the site or unit. Assets with a high demand on mechanical availability and variable maintenance cost will often choose to decrease PM / PdM task intervals in order to ensure a higher degree of reliability, despite the increase in overall maintenance cost. Assets with a lower demand or margins, or more rigid maintenance targets, may opt for increased PM / PdM task intervals to decreased planned cost at the expense of a higher risk of failure.
As demand increases, so does the maintenance effort in the plant. This should increase availability, when using a data and risk driven approach. In many cases, demand increases or decreases, but the maintenance effort (spend) remains be stable. This means additional maintenance effort is being put into plants in order to achieve near 100% availability when only 70-80% is needed. In some rare cases clients take cost-cutting measures, resulting in even higher repair cost and lower reliability because of the deferred maintenance tasks.

With STRYVE, processing units can forecast these increases in demand and make early investments to avoid these misaligned cycles. Changes to asset and equipment strategies can occur well in advance of the increase in demand. Units become more profitable as their ability to forecast and adapt to these changes increases. All decisions are backed by data rather than intuition. While we leverage the experience of the users in creating these equipment and asset strategies, our optimization algorithms will take the manual calculation and guess work out of your short and long term planning.
Frequently Asked Questions

What is STRYVE and what is it not?


What are the short term and long-term benefits of implementing STRYVE?
A few long term benefits of STRYVE include:
STRYVE helps identify gaps in CMMS Data. Improvements to OEE lead to an increase in asset availability and reduced life cycle cost of assets. All recurring tasks stay in the system and are automatically applied to future budgets given the assigned time intervals. All future budgets are created automatically, so users can focus on selecting the right tasks and optimizing the asset. Moving to SMRP’s recommendation of proactive vs corrective spend. With the right proactive tasks now, corrective cost will decrease into the future.
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How will Maintenance benefit from STRYVE?

How will Operations benefit from STRYVE?

What is STRYVE replacing?

What input data is needed for STRYVE?

Why do we need maintenance plans and how do they influence the budget?

How does STRYVE forecast or predict corrective maintenance?

What limitations are presented from poor historical data?

Is STRYVE customizable for my organization?

How often should STRYVE be used and updated?
Featured Insights

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When it comes to maintenance budgets, many companies plan on the basis of the previous year. The problem with this tactic is that old budget figures don’t reveal much, if anything, about current and future maintenance needs.
Managing Maintenance as a Value Center
Maintenance managers must take it upon themselves break out of the cost center mold and start measuring and communicating their value as business partners.
Applying a capital process in routine maintenance for risk mitigation
How long-term risk-mitigating techniques can be used to bridge the gap between condition monitoring and high-risk, intrusive preventive maintenance tasks.
RCM Strategies for the Rapidly Unfolding Market Recovery
There are several reliability-centered maintenance actions that asset management leaders can do to prepare themselves for the rapid transition from COVID-imposed constraints to an extended period of maximum production