What is zero-based budgeting?

Zero-Based Budgeting (ZBB) is like solving a financial puzzle. Instead of relying on the previous year’s budget, ZBB requires you to evaluate and justify every expense from the ground up, justifying its necessity and alignment with strategic goals. It’s like starting with a blank canvas and carefully selecting each budget item based on its value and contribution to your financial objectives. This approach ensures that every piece of your budget fits together harmoniously to create a clear and purposeful financial picture.

In this blog post, we will delve into the concept of zero-based budgeting, exploring its definition, advantages, disadvantages, implementation steps, and tools needed.

What is Zero-Based Budgeting? 

The zero-based budgeting process is a strategic budgeting approach that mandates a fresh evaluation of all expenses during each budgeting cycle. Unlike traditional budgeting, where previous spending levels are typically adjusted, ZBB requires individuals or organizations to justify every expense from the ground up. The aim is to optimize resource allocation by ensuring funds are allocated to activities that align with strategic objectives and generate the highest value. 

Peter Pyhrr, an accountant and consultant, is credited with developing the concept of zero-based budgeting (ZBB) in the 1970s. Pyhrr recognized the limitations of traditional methods of budgeting that relied on incremental adjustments to previous budgets. He believed that organizations needed a more rigorous approach to budgeting that would ensure resources were allocated efficiently and aligned with strategic objectives.

Pyhrr introduced the idea of starting the budgeting process from a “zero base,” meaning that every expense had to be justified from scratch. This approach challenged the assumption that previous spending levels were automatically justified, requiring individuals and departments to provide a detailed rationale for each expenditure.

By requiring a fresh evaluation of all expenses, Pyhrr aimed to eliminate unnecessary costs, identify inefficiencies, and promote a more focused use of resources. His goal was to instill a sense of accountability and ownership among budget holders, encouraging them to critically analyze and justify their budget requests.

Advantages of Zero-Based Budgeting

Zero-based budgeting offers several advantages for both businesses and individuals. Some key benefits include: 

• Cost Savings: ZBB requires a thorough evaluation of all expenses, challenging the assumption that last year spending levels are justified. By scrutinizing each line-item expense from scratch, ZBB helps identify unnecessary or redundant costs, preventing overspending. This process allows for cost-cutting and setting savings goals, leading to lower costs and improved financial efficiency. 
• Enhanced Efficiency: ZBB encourages resource reallocation towards high-impact activities. By evaluating expenses based on their value and alignment with strategic objectives, ZBB ensures that resources are allocated to areas that generate the highest return on investment. It promotes a more focused and effective cost management.
• Increased Accountability: With ZBB, individuals or departments must justify their budget requests and align them with organizational financial goals. This fosters a culture of accountability, as each expense must demonstrate its purpose and value. ZBB creates a sense of ownership and responsibility among budget holders. 
• Flexibility and Adaptability: Traditional budgeting systems often rely on historical data and incremental adjustments. ZBB, on the other hand, is not bound by past spending patterns. It allows for better adaptation to changing circumstances, emerging priorities, and new opportunities. ZBB promotes agility in resource allocation, enabling organizations to respond effectively to evolving market conditions. 
• Cost-Conscious Culture: ZBB can foster a cost-conscious culture within an organization. By instilling a mindset of questioning and justifying expenses, ZBB encourages employees to think critically about costs and seek more efficient alternatives to cut back. This culture of cost-consciousness can lead to continuous improvement and a focus on value creation. 
• Improved Decision-Making: ZBB provides a comprehensive view of expenses and their impact on organizational goals. By evaluating each expense category, decision-makers gain better visibility into the cost structure of the organization. This enables informed decision-making, as leaders have a clearer understanding of the trade-offs involved and can make strategic choices based on reliable data. 

How to implement Zero-Based Budgeting?

Implementing zero-based budgeting (ZBB) in an organization involves careful planning and execution. Here are the key steps to follow:

1. Identify Objectives: Clearly define the organization’s goals and strategic direction to establish the foundation for the budgeting process. Ensure that budget allocations align with these objectives and prioritize them accordingly.

2. Evaluate Expenses: Review each expense category, including recurring expenses such as subscriptions, and question their necessity and relevance. Scrutinize both fixed expenses like rent and utilities, and variable expenses such as marketing and travel. Identify areas where costs can be optimized and potential savings can be made.

3. Build Budgets: Create new budgets from scratch, ensuring that each item serves a clear purpose and directly supports the organization’s strategic goals. Consider the importance of each expense category, allocating resources accordingly to maximize their impact. To ensure sufficient funds are available for unforeseen circumstances an emergency fund can be set up.

4. Prioritize Resources: Allocate resources based on their importance and their contribution to the organization’s objectives. Give priority to high-value activities and projects that align with strategic goals. Take budget constraints into account and make informed decisions on resource allocation.

5. Monitor and Review: Regularly monitor the budget implementation, track expenses, and assess performance against objectives. Keep a close eye on spending and make adjustments as necessary to maintain alignment with the organization’s goals. This ongoing monitoring and review process ensures that the budget remains effective and adaptable to changing circumstances.

By following these steps, organizations can successfully implement zero-based budgeting, optimize their resource allocation, and achieve greater financial efficiency while aligning with their strategic objectives.

Disadvantages of Zero-Based Budgeting

While zero-based budgeting can be a powerful tool for organizations, there are several important considerations and potential challenges to be aware of:

• Time and Effort: Implementing zero-based budgeting can be a time-consuming process, especially short-term during the initial stages. It requires a significant investment of effort to thoroughly evaluate and justify every expense from scratch. Adequate planning, data collection, and stakeholder involvement are crucial for a successful implementation.
• Change Management: Adopting a new budgeting method like zero-based budgeting often requires a shift in organizational culture and mindset. Employees may need to adjust to a more rigorous and detailed approach to budgeting, which can lead to resistance or discomfort. Change management practices, such as communication, training, and engagement, are important to facilitate a smooth transition and ensure widespread adoption.
• Complexity: Zero-based budgeting can be more complex than traditional budgeting, especially for large organizations or individuals with diverse financial obligations. The process requires meticulous documentation and tracking systems to ensure accurate evaluation, allocation, and monitoring of expenses. Managing the complexity of ZBB may require additional resources, expertise, and technology to support the budgeting process effectively.
• Resource Allocation Challenges: Zero-based budgeting may pose challenges in resource allocation, particularly when dealing with competing priorities and limited resources. The thorough evaluation of expenses from scratch can sometimes lead to difficult decisions and trade-offs between different activities, projects, or departments. Balancing strategic objectives, budget constraints, and the need for cost optimization requires careful consideration and decision-making.
• Initial Disruption: Implementing zero-based budgeting may cause initial disruption within the organization as existing budgeting practices and processes are replaced or modified. This disruption can impact the workflow, roles, and responsibilities of individuals involved in the budgeting process. Adequate communication, training, and support are essential to minimize disruption and ensure a smooth transition.

By understanding and addressing these potential challenges, organizations can better prepare themselves for the implementation of zero-based budgeting and mitigate any potential negative impacts on the budgeting process and organizational dynamics.

What are the best tools to use for zero-based budgeting?

• Spreadsheets: Traditional spreadsheet applications like Microsoft Excel or Google Sheets can be used to create and manage zero-based budgets. They provide flexibility in organizing budget data, performing calculations, and generating reports. Spreadsheets allow for customization and can be a cost-effective option for smaller organizations.
• Financial Planning and Analysis (FP&A) Software: Offer dedicated features for budgeting, forecasting, and financial analysis. These tools provide a centralized platform for top-down and bottom-up budgeting creation, collaboration, scenario modeling, data integration, and reporting. They often come with advanced analytics capabilities, enabling organizations to make data-driven budgeting decisions.
• Enterprise Resource Planning (ERP) Systems: ERP systems integrate various financial processes, including budgeting. These systems offer modules specifically designed for budget creation, tracking, and reporting. They provide a comprehensive view of financial data, facilitate data integration, and support collaboration among different departments.
• Budgeting and Planning Software: Dedicated budgeting and planning software are designed to streamline the budgeting process. These tools provide features like budget templates, workflow automation, data consolidation, scenario modeling, and reporting. They often offer user-friendly interfaces and enable collaboration among budget stakeholders.
• Data Visualization Tools: Data visualization tools enable organizations to visualize budget data and financial insights. These tools create interactive charts, graphs, and dashboards that enhance the understanding and communication of budget information. Data visualization tools can help identify trends, patterns, and anomalies in the budgeting process.
• Project Management Software: Project management tools like Asana, Trello, or Jira can be utilized to track budgeting tasks, deadlines, and milestones. These tools help manage the workflow, assign responsibilities, and ensure accountability during the budgeting process. They enhance collaboration and provide transparency into the progress of budget-related activities.

How can IBM Planning Analytics help with zero-based budgeting?

IBM Planning Analytics is an integrated business planning and analysis solution that can greatly assist with zero-based budgeting (ZBB) initiatives. Here’s how IBM Planning Analytics stands out and provides value in implementing ZBB:

• Advanced Functionality: IBM Planning Analytics provides robust features specifically designed to support ZBB, such as data collection, analysis, scenario modeling, and budgeting capabilities. It also offers integration with spreadsheets, allowing organizations to leverage existing spreadsheet data and seamlessly transition to a more sophisticated budgeting solution.
• Collaborative Environment: IBM Planning Analytics fosters collaboration among stakeholders involved in the budgeting process. It allows teams to evaluate expenses, allocate resources, and justify budget requests based on strategic objectives. This collaborative environment enhances transparency, and accountability, and ensures that budget decisions align with organizational goals.
• AI-Infused Capabilities: IBM Planning Analytics utilizes artificial intelligence (AI) and machine learning capabilities to provide advanced analytics and forecasting. These AI-infused features help organizations gain deeper insights into their budget data, identify trends, and make more accurate predictions, enabling them to make data-driven budgeting decisions.
• Integration Capabilities: IBM Planning Analytics integrates seamlessly with other systems and data sources, such as accounting platforms or ERP systems. This integration ensures the availability of accurate financial data for budgeting decisions, eliminating the need for manual data entry and reducing errors.
• Scalability and Flexibility: IBM Planning Analytics is highly scalable and suitable for organizations of all sizes. It can adapt to changing business needs and accommodate complex budgeting requirements. Whether it’s a small organization or a large enterprise, IBM Planning Analytics can effectively support the ZBB process.
• User-Friendly Interface: IBM Planning Analytics offers a user-friendly interface that simplifies the budgeting process. Its intuitive design and interactive dashboards allow users to navigate through budget data, perform analyses, and generate reports with ease.

While there are other tools available for zero-based budgeting, IBM Planning Analytics stands out due to its powerful and flexible platform that allows for comprehensive functionality, AI-infused capabilities and user-friendly interfaces. These factors make IBM Planning Analytics a preferred choice for organizations seeking to implement ZBB effectively and achieve cost optimization and accountability throughout the budgeting cycle.

Zero-based budgeting is an innovative type of budgeting that challenges conventional financial practices. By reevaluating expenses from scratch and aligning them with strategic objectives, ZBB promotes cost optimization, efficiency, and accountability. While implementing ZBB requires significant effort and change management, the benefits of this approach can outweigh the challenges.

Source: ibm.com

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OEE vs. TEEP: What’s the difference?

Breakdowns, equipment failure, outages and other shop floor disruptions can result in big losses for an organization. Production managers are tasked with ensuring that factories and other production lines are getting the most value out of their equipment and systems.

Overall equipment effectiveness (OEE) and total effective equipment performance (TEEP) are two related KPIs that are used in manufacturing and production environments to help prevent losses by measuring and improving the performance of equipment and production lines.

What is overall equipment effectiveness (OEE)?

OEE is a metric used to measure the effectiveness and performance of manufacturing processes or any individual piece of equipment. It provides insights into how well equipment is utilized and how efficiently it operates in producing goods or delivering services.

OEE measures the equipment efficiency and effectiveness based on three factors. The OEE calculation is simple: availability x performance x quality.

What is total effective equipment performance (TEEP)?

TEEP is also a metric used in manufacturing and production environments to measure the overall efficiency and effectiveness of equipment or a production line. It includes all the potential production time, including planned and unplanned downtime.

TEEP is calculated by multiplying four factors: availability x performance x quality x utilization.

How are OEE and TEEP different?

The main difference between these two metrics is that while OEE measures the percentage of planned production time that is productive, TEEP measures the percentage of all time that is productive. 

It’s important when making these calculations of time to use the right terminology. Here are a few common ways to measure time within a production context:

• Unscheduled time: Time when production is not scheduled to produce anything (as opposed to “scheduled time”).
• Calendar time: The amount of time spent on a job order up to its completion.
• Total operations time: The total amount of time that a machine is available to manufacture products.
• Ideal cycle time: The theoretical fastest possible time to manufacture one unit.
• Run time: The time when the manufacturing process is scheduled for production and running.

OEE primarily focuses on the utilization of available time and identifies losses due to availability, performance and quality issues. It helps identify areas for improvement and efficiency optimization.

TEEP, on the other hand, provides a broader perspective by considering all potential production time, including planned downtime for preventive maintenance or changeovers. It aims to measure the maximum potential of the equipment or production line. 

OEE is typically used to measure the performance of a specific piece of equipment or a machine. It helps you understand how effectively equipment is being utilized during actual production time. OEE is commonly used as a benchmarking tool to track and improve equipment performance over time. It helps identify bottlenecks, areas for optimization and improvement initiatives.

TEEP is used to measure the overall performance of an entire production line or multiple pieces of equipment working together. It provides a holistic view of the effectiveness of the entire system. If you are interested in understanding the maximum potential performance of your production line, including planned downtime for maintenance, changeovers or other scheduled events, TEEP is the performance metric to use. TEEP can be helpful in production capacity planning and determining the capabilities of your equipment or production line.

How can OEE and TEEP be used together?

1. Start with OEE analysis: Begin by calculating the OEE for individual machines or equipment within your production line. OEE analysis helps pinpoint the causes of losses and inefficiencies at the equipment level. A digital asset management platform can provide real-time data to help with this calculation.

2. Identify bottlenecks: Use OEE data to identify bottlenecks or areas where equipment performance is suboptimal. Look for machines with lower OEE scores and investigate the underlying issues. This can help you prioritize improvement efforts and target specific machines or processes that have the most significant impact on overall performance.

3. Evaluate TEEP for the entire line: Once you have assessed the OEE for individual machines, calculate the TEEP for your entire production line. TEEP takes into account all potential operating time—including planned and unplanned downtime—providing a broader perspective on the overall performance of the line.

4. Compare OEE and TEEP: Compare the OEE and TEEP data to gain insights into the gap between actual performance and the maximum potential performance of the production line. Identify the factors contributing to the difference between the two metrics, such as scheduled maintenance, changeovers or other planned downtime. This comparison can help you understand the overall efficiency and effectiveness of the production line.

5. Address common issues: Analyze common issues identified through OEE and TEEP analysis and devise strategies to address them. This may involve improving machine reliability, procuring new equipment, integrating continuous improvement methodologies, reducing setup or changeover times, enhancing product quality or optimizing maintenance management. Implementing targeted improvement initiatives can help bridge the performance gap and maximize the overall equipment performance.

6. Track progress over time: Continuously monitor and track both OEE and TEEP metrics over time to assess the effectiveness of your improvement efforts. Regularly evaluating these metrics allows you to measure the impact of implemented changes and identify new areas for optimization.

By combining OEE and TEEP, you can conduct a comprehensive analysis of current equipment performance at both the individual-machine and production-line levels. This integrated approach provides a deeper understanding of performance factors, helps prioritize improvement efforts, and maximizes the overall effectiveness and efficiency of your manufacturing operations, allowing production managers to achieve higher throughput and maximum uptime.

World-class observability with IBM Maximo

IBM Maximo is enterprise asset management software that delivers a predictive solution for the maximization of equipment effectiveness. Maximo is a single, integrated cloud-based platform that uses AI, IoT and analytics to optimize performance, extend the lifecycle of assets and reduce the costs of outages. 

Take a tour to see how Maximo can achieve OEE improvement while reducing the operations costs of overtime, material waste, spare parts and emergency maintenance.

Source: ibm.com

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How to modernize data lakes with a data lakehouse architecture

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Some argue though that the vast majority of these deployments have now become data “swamps”. Regardless of which side of this controversy you sit in, reality is that there is still a lot of data held in these systems. Such data volumes are not easy to move, migrate or modernize.

The challenges of a monolithic data lake architecture

Data lakes are, at a high level, single repositories of data at scale. Data may be stored in its raw original form or optimized into a different format suitable for consumption by specialized engines.

In the case of Hadoop, one of the more popular data lakes, the promise of implementing such a repository using open-source software and having it all run on commodity hardware meant you could store a lot of data on these systems at a very low cost. Data could be persisted in open data formats, democratizing its consumption, as well as replicated automatically which helped you sustain high availability. The default processing framework offered the ability to recover from failures mid-flight. This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale.

Another unexpected challenge was the introduction of Spark as a processing framework for big data. It gained rapid popularity given its support for data transformations, streaming and SQL. But it never co-existed amicably within existing data lake environments. As a result, it often led to additional dedicated compute clusters just to be able to run Spark.

Fast forward almost 15 years and reality has clearly set in on the trade-offs and compromises this technology entailed. Their fast adoption meant that customers soon lost track of what ended up in the data lake. And, just as challenging, they could not tell where the data came from, how it had been ingested nor how it had been transformed in the process. Data governance remains an unexplored frontier for this technology. Software may be open, but someone needs to learn how to use it, maintain it and support it. Relying on community support does not always yield the required turn-around times demanded by business operations. High availability via replication meant more data copies on more disks, more storage costs and more frequent failures. A highly available distributed processing framework meant giving up on performance in favor of resiliency (we are talking orders of magnitude performance degradation for interactive analytics and BI).

Why modernize your data lake?

Data lakes have proven successful where companies have been able to narrow the focus on specific usage scenarios. But what has been clear is that there is an urgent need to modernize these deployments and protect the investment in infrastructure, skills and data held in those systems.

In a search for answers, the industry looked at existing data platform technologies and their strengths. It became clear that an effective approach was to bring together the key features of traditional (legacy, if you will) warehouses or data marts with what worked best from data lakes. Several items quickly raised to the top as table stakes:

• Resilient and scalable storage that could satisfy the demand of an ever-increasing data scale.
• Open data formats that kept the data accessible by all but optimized for high performance and with a well-defined structure.
• Open (sharable) metadata that enables multiple consumption engines or frameworks.
• Ability to update data (ACID properties) and support transactional concurrency.
• Comprehensive data security and data governance (i.e. lineage, full-featured data access policy definition and enforcement including geo-dispersed)

The above has led to the advent of the data lakehouse. A data lakehouse is a data platform which merges the best aspects of data warehouses and data lakes into a unified and cohesive data management solution.

Benefits of modernizing data lakes to watsonx.data

IBM’s answer to the current analytics crossroad is watsonx.data. This is a new open data store for managing data at scale that allows companies to surround, augment and modernize their existing data lakes and data warehouses without the need to migrate. Its hybrid nature means you can run it on customer-managed infrastructure (on-premises and/or IaaS) and Cloud. It builds on a lakehouse architecture and embeds a single set of solutions (and common software stack) for all form factors.

Contrasting with competing offerings in the market, IBM’s approach builds on an open-source stack and architecture. These are not new components but well-established ones in the industry. IBM has taken care of their interoperability, co-existence and metadata exchange. Users can get started quickly—therefore dramatically reducing the cost of entry and adoption—with high level architecture and foundational concepts are familiar and intuitive:

• Open data (and table formats) over Object Store
• Data access through S3
• Presto and Spark for compute consumption (SQL, data science, transformations, and streaming)
• Open metadata sharing (via Hive and compatible constructs).

Watsonx.data offers companies a means of protecting their decades-long investment on data lakes and warehousing. It allows them to immediately expand and gradually modernize their installations focusing each component on the usage scenarios most important to them.

A key differentiator is the multi-engine strategy that allows users to leverage the right technology for the right job at the right time all via a unified data platform. Watsonx.data enables customers to implement fully dynamic tiered storage (and associated compute). This can lead, over time, to very significant data management and processing cost savings.

And if, ultimately, your objective is to modernize your existing data lakes deployments with a modern data lakehouse, watsonx.data facilitates the task by minimizing data migration and application migration via choice of compute.

What can you do next?

Over the past few years data lakes have played an important role in most enterprises’ data management strategy. If your goal is to evolve and modernize your data management strategy towards a truly hybrid analytics cloud architecture, then IBM’s new data store built on a data lakehouse architecture, watsonx.data, deserves your consideration.

Source: ibm.com

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Using the metadata service to identify disks in your VSI with IBM Cloud VPC

A common use case in the cloud is attaching/removing volumes dynamically. Identifying the attached disk device in the operating system of the VSI is not always obvious.

In IBM Cloud Virtual Server for VPC, the disk that is attached to the VSI is identified by the volume attachment identifier. Every volume has a UUID, but the attachment between the volume and the VSI also has a UUID. The UUID of that volume attachment is what can be used to identify the backing disk in the VSI.

UI-based example

Listing the volume attachment identifiers is simple with the ibmcloud CLI:

Drews-MBP ~ % ibmcloud is in-vols 0727_fa4230b2-e167-4a09-8d7c-2822bdb016bf

Listing volume attachments of instance 0727_fa4230b2-e167-4a09-8d7c-2822bdb016bf under account Drew Thorstensen's Account as user thorst@us.ibm.com...

ID                                          Name                          Volume                             Status     Type   Device                                            Auto delete   

0727-7db66159-5910-4ddc-a5b4-51f9333a9c3a   secrecy-robust-anyone-agile   test-metadata-volume               attached   data   0727-7db66159-5910-4ddc-a5b4-51f9333a9c3a-4xjjc   false   

0727-4b98cbf2-4e57-4b3b-9bd2-83f2439da3bc   breath-manger-bird-axiom      test-metadata-boot-1649335137000   attached   boot   0727-4b98cbf2-4e57-4b3b-9bd2-83f2439da3bc-5jx6t   true     

This shows two volumes attached to the VSI: the boot and then a data volume. If we log in to the VSI, we can see the volume disks:

[root@test-metadata ~]# ls -la /dev/disk/by-id

total 0

drwxr-xr-x. 2 root root 200 Apr  7 12:58 .

drwxr-xr-x. 7 root root 140 Apr  7 12:51 ..

lrwxrwxrwx. 1 root root   9 Apr  7 12:52 virtio-0727-4b98cbf2-4e57-4 -> ../../vda

lrwxrwxrwx. 1 root root  10 Apr  7 12:52 virtio-0727-4b98cbf2-4e57-4-part1 -> ../../vda1

lrwxrwxrwx. 1 root root  10 Apr  7 12:52 virtio-0727-4b98cbf2-4e57-4-part2 -> ../../vda2

lrwxrwxrwx. 1 root root  10 Apr  7 12:52 virtio-0727-4b98cbf2-4e57-4-part3 -> ../../vda3

lrwxrwxrwx. 1 root root   9 Apr  7 12:58 virtio-0727-7db66159-5910-4 -> ../../vdd

lrwxrwxrwx. 1 root root  10 Apr  7 12:58 virtio-0727-7db66159-5910-4-part1 -> ../../vdd1

lrwxrwxrwx. 1 root root   9 Apr  7 12:52 virtio-cloud-init- -> ../../vdc

lrwxrwxrwx. 1 root root   9 Apr  7 12:52 virtio-cloud-init-0727_fa42 -> ../../vdb

If we want to find the data volume named test-metadata-volume, we see that it is the vdd disk. The first 20 characters of the volume attachment identifier are used for the disk id. The symbolic link shows us the name of the disk that it maps to, as well.

Simplifying with the metadata service

Most users are looking for a quicker way to identify the disk name, and these users will also likely be starting with the volume rather than the volume attachment. Fortunately, this is easy to do.

Recently, IBM Cloud VPC introduced the metadata service. This capability allows the end user to query data about itself and get identity tokens and more from the VSI. One of the use cases it can help with is helping simplify getting the disk name based off a volume name.

The steps to find the disk name within a VSI from a given volume are as follows:

◉ Deploy the VSI with metadata turned on

◉ Get an instance identity token

◉ Query the metadata service to list the volume attachments

◉ Find the volume attachment that has the volume specified

◉ Look up the disk name based off the volume attachment

Attached to this post is a script that can be used to retrieve the disk name for a given volume UUID (not the attachment UUID). The following is the sample output:

[root@test-metadata ~]# python3 scripts/find_disk.py -v 0727-7db66159-5910-4ddc-a5b4-51f9333a9c3a-4xjjc

vdd

In this case, the disk is named vdd within the VSI for volume 0727-7db66159-5910-4ddc-a5b4-51f9333a9c3a-4xjjc.

Code

The following code can be embedded into your instance or user data to help quickly identify disk names within the VSI given the volume UUID.  Be sure to remember that the metadata service must be running for this to work properly:

# ======================================================================

#    Copyright 2022 IBM Corp.

#

#    Licensed under the Apache License, Version 2.0 (the "License");

#    you may not use this file except in compliance with the License.

#    You may obtain a copy of the License at

#

#      http://www.apache.org/licenses/LICENSE-2.0

#

#    Unless required by applicable law or agreed to in writing, software

#    distributed under the License is distributed on an "AS IS" BASIS,

#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

#    See the License for the specific language governing permissions and

#    limitations under the License.

# ======================================================================

import argparse

import json

import os

import requests

import sys

def init_argparse():

    parser = argparse.ArgumentParser(

        description=("Finds a local disk by UUID")

    )

    parser.add_argument("-v", "--volume-uuid", required=True,

                        help=("The volume UUID."))

    return parser.parse_args()

def get_token():

    result = requests.put("http://169.254.169.254/instance_identity/v1/token?version=2021-10-12",

                          headers={'Metadata-Flavor': 'ibm'})

    return json.loads(result.text)['access_token']

def get_volume_attachments(access_token):

    result = requests.get("http://169.254.169.254/metadata/v1/instance/volume_attachments?version=2021-10-12",

                          headers={'Authorization': f"Bearer {access_token}"})

    return json.loads(result.text)['volume_attachments']

def get_disk_device(attachment_uuid):

    expected_path = f'/dev/disk/by-id/virtio-{attachment_uuid[:20]}'

    full_path = os.path.realpath(expected_path)

    return full_path.split('/')[-1]

def main():

    args = init_argparse()

    access_token = get_token()

    volume_attachments = get_volume_attachments(access_token)

    for volume_attachment in volume_attachments:

        if volume_attachment['device']['id'] == args.volume_uuid:

            print(get_disk_device(volume_attachment['id']))

            sys.exit(0)

    else:

        print(f"Unable to find disk by volume {args.volume_uuid}")

        sys.exit(1)

if __name__ == '__main__':

    main()

Source: ibm.com

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CMMS vs. EAM: Two asset management tools that work great together

Most organizations can’t run without physical assets. Machinery, equipment, facilities and vehicles provide economic value or benefit operations. In most cases, they are fundamental to the performance of the organization, regardless of whether they are small-scale laptop portfolios or vast transportation networks. Energy companies rely on uninterrupted power supplies, airlines aim to ensure passenger safety, hospitals must provide quality patient care, haulage companies need up-to-date data on spare parts to maintain service levels.

Organizations can’t work effectively if they don’t invest to keep their assets running cost-effectively throughout their lifecycle. To do that, technicians, facility managers, maintenance teams, reliability engineers and project managers need accurate, real-time information at their fingertips.

◉ The growing complexity and scale of operations across industries and the need to track, monitor and manage assets, have been driving the evolution of advanced asset management software. Organizations are modernizing their enterprise apps, deploying more modular, intelligent systems and AI-enhanced workflows as part of broader digital transformation.

Asset management is no exception—according to IDC, 30% of organizations are strategically addressing digital transformation in enterprise asset management (EAM) solutions with a view to longer-term change management.

Two commonly used asset management and maintenance solutions are computerized maintenance management systems (CMMS) and enterprise asset management (EAM):

◉ Computerized maintenance management system (CMMS)—also called CMMS software, platforms or solutions—focuses predominantly on maintenance—helping to manage assets, schedule maintenance and track work orders.

◉ Enterprise asset management (EAM) is an asset lifecycle management solution focused on optimizing the overall lifetime performance of assets from acquisition to end-of-life.

Depending on variables like asset type, business size and the scale of operations, each solution provides different functionalities and benefits to match an organization’s maintenance requirements. Let’s explore these in more depth.

What is CMMS and what does it do?

A computerized maintenance management system (CMMS) is a type of maintenance management software that centralizes maintenance information and facilitates and documents maintenance operations. A CMMS automates critical asset management workflows and makes them accessible and auditable.

Core to CMMS is a central database that organizes and communicates information about assets and maintenance tasks to maintenance departments and teams to help them do their jobs more effectively. They typically include modules for tracking employees and equipment certifications (resource and labor management), data storage on individual assets like serial numbers and warranties (asset registry), and task-related activities like work order numbers and preventive maintenance schedules (work order management). Other features like vendor and inventory management, reporting, analysis (e.g., KPI dashboards or MRO inventory optimization) and audit trails are also included in CMMS software solutions.

CMMS evolved in the 1960s when the growing complexity of operations in large companies started to expose the limitations and inadequacies of manual and paper-based management. Data was siloed, hidden away in a multitude of spreadsheets and filing cabinets, and carrying out tasks manually was time-consuming.

During the 1980s, 1990s and 2000s, as technology became more affordable and connected, CMMS functionality expanded to include work order management, where companies assign, monitor and complete work orders and inspection checklists in one place. Other features, such as project management and spare parts purchasing, were also added as solutions advanced. Many industries depend on CMMS to improve asset and workflow visibility, streamline operations and maintenance, manage mobile field workforces, and ensure compliance in, for example, auditing and health, safety and environment reporting.

What is EAM and what does it do?

Enterprise asset management (EAM) software provides a holistic and comprehensive overview of a company’s physical assets and is used to maintain and control operational assets and equipment throughout their entire lifecycle, regardless of location.

Typically, EAM solutions cover work orders, contract and labor management, asset maintenance, planning and scheduling, condition monitoring, reliability analysis, asset performance optimization, supply chain management, and environmental, health and safety (EHS) applications. They store large amounts of data that can be analyzed and tracked, with organizations customizing their KPIs and metrics according to their specific needs. EAM solutions can also link into other enterprise management systems and workflows like enterprise resource planning (ERP), providing a single source of asset intelligence.

EAM emerged from CMMS early in the 1990s, bringing together maintenance planning and execution with skills, materials and other information spanning asset design through to decommissioning. This broadening of scope has especially benefitted industries heavily reliant on physical assets or with complex asset infrastructures where asset management effectiveness and ROI are major contributors to the bottom line.

In the oil and gas or mining industries, for example, there is a strong need to bring safety, reliability and compliance information into workflows. In defense, there are strict regulations around tracking potentially dangerous assets, and the safety of military operations depends on the operational readiness of multiple assets in disparate locations.

Organizations use EAM to save money from being wasted on preventable problems and unnecessary downtime and to enhance the efficiency, performance and lifespan of assets. Through a combination of maintenance strategies, automation and technologies like the Internet of Things (IOT) and artificial intelligence (AI), EAM can use preventive and predictive maintenance to monitor and resolve issues before they happen, maximize the use of assets, consolidate operational applications and provide in-depth cost analyses. The result is that asset management professionals make better decisions, work more efficiently and maximize investments in physical assets.

CMMS vs EAM: What’s the difference?

CMMS and EAM software have a similar purpose—to prolong and improve asset performance, boost operational efficiency and reliability, and reduce costs through more productive uptime, less downtime and longer asset lifespans. Despite some overlap, they are not the same and have key differences in functionality, approach and business context, offering different management tools and resources. In general, while most EAM systems have CMMS capabilities, only the more advanced CMMS solutions have some EAM functionality. Some of the main differences are outlined below but the extent of these varies by provider.

CMMS is dedicated to MRO (maintenance, repair and operations) for physical assets and equipment, tracking a company’s asset maintenance activities, scheduling and costs once an asset has been installed. EAM, on the other hand, provides a greater understanding of lifecycle cost and value of assets by managing the entire asset lifecycle from beginning to end. Being able to track assets, assess and monitor them, manage and optimize their quality and reliability, and gauge where inefficiencies are occurring means a business can get the most out of its assets and avoid unnecessary disruptions that could impact the smooth running of its operations.

EAM also provides data on lifetime costs—such as purchasing, maintenance, repair and servicing—which help businesses understand the total cost of ownership of individual assets. Although CMMS solutions are becoming more sophisticated, they don’t typically include additional features like high-level financial accounting or costs associated with procurement or decommissioning.

EAM also differs from CMMS in that EAM provides multi-site support across multiple worksites and geographies. Most CMMS solutions only provide single-site or limited multi-site support. That can be a substantial advantage for industries like power or mass transportation that manage vastly distributed asset portfolios.

EAM covers a wider variety of business functions than CMMS; features like contract management, fleet management, schematics, warranty tracking, energy monitoring and industry-specific apps are not typically covered in CMMS systems. EAM can also work with a broader range of other enterprise software, such as financial analysis, supply chain management and procurement, risk and compliance and sustainability. CMMS only tends to integrate with other systems to automate repetitive tasks, though a few do include purchasing capabilities.

That said, EAM can cost more to implement than CMMS in the first instance, largely because of its greater complexity and the additional setup costs stemming from integration with other business functions. SaaS models are changing this, bringing CMMS and EAM costs closer together, which, coupled with the additional benefits of EAM, is making it an increasingly cost-effective option.

Although modern CMMS systems can offer more than just maintenance and the line between CMMS and EAM is blurring, they remain distinct solutions. CMMS can be viewed as a subset of EAM and potentially an avenue to large-scale and more robust enterprise asset management. The two are often used together or CMMS may suffice for companies with small asset portfolios and maintenance teams. When companies are looking to scale and consolidate systems across multiple departments, however, the limitations of CMMS can impact its overall value.

Ultimately, the choice of software depends on many factors, but in general, if you are looking to understand and manage high numbers of assets in multiple locations across their entire lifecycle and incorporate other business functions like HR and finance, EAM is likely to be the way to go.

IBM Maximo Application Suite

Look no further. IBM Maximo Application Suite combines the world’s leading enterprise asset management system with all the benefits of CMMS.

Get the most value from your enterprise assets with Maximo Application Suite. It’s a market-leading single, integrated cloud-based platform that uses AI, IoT and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. It gives you configurable CMMS and EAM applications that can help you manage your company assets, processes and people.

Source: ibm.com

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