Let’s get real. What office worker hasn’t heard of Office 365? Unless you still use a typewriter, you probably spend a great portion of your day in Microsoft Office applications. There are, after all, about 155 million active business users of Office 365, making it the most widely used cloud service by user count.
55% of businesses say that the biggest ongoing issue for Office 365 is persuading users to manage and share content in Office 365 and not elsewhere.
Another key issue is how to connect all relevant data, be it structured business data, or unstructured documents.
The Sensitive Document Problem
According to the AIIM 2018 Industry Watch Office 365 Revolution Impact on Governance and Process Automation, 46% of an organization’s sensitive documents are contained in Office documents. The unstructured documents make it hard to manage business critical and sensitive data.
And, to make matters worse, it is estimated that as much as 90% of all data is unstructured, and that unstructured data is stored in at least four different content repositories.
M-Files to the Rescue
According to feedback from our customers, there are five main challenges they face with Office 365 implementations.
Permissions are role-based and easily managed with metadata. Archiving is automated with AI-driven tools. Content outside of Office 365 can still be managed from the familiar Office interface, e.g. Teams. Best practices are enhanced with automated workflows and processes. And M-Files can help you gain access and edit content from different places in one common view.
Bridging the Gap between Structured Business Data and Unstructured Documents
Our unique approach manages information based on what it is rather than where it lives. M-Files connects several business systems and external repositories and allows you to manage information from any repository.
You can easily get a 360-degree view of your business without the pain of migration. Rather, you can gradually migrate the most critical data to M-Files and manage it there. And additionally, allow people to access it through their daily tools.
3 Steps to Increased Efficiency and Convenience
M-Files for Office 365 approaches the challenges of information management on three levels, making office work both more efficient for the business, and more convenient for employees.
Free IT from the pain of migration and integrations. There’s no need for migration as information can be found, accessed, and managed regardless of its origin.
Let people use their familiar daily tools even for document management. Employees can use their daily tools — like Teams or Outlook — to access and manage all documents and data.
Let people focus on value-adding tasks. Employees do not need to waste time looking for information or tagging it as AI can eliminate routine tasks.
There aren’t many things in maintenance that are predictable. One of them is equipment maintenance logs. You know the drill: Work gets done, a log gets updated. It’s a routine you can count on.
This article is all about how to use that predictability to your advantage by taking the information you’re collecting anyway and turning it into the assetdata you’ve been looking for.
How to create a great equipment maintenance log
Getting accurate, reliable data from an equipment maintenance log starts with how you build it. The way you structure your maintenance logs is going to depend on a variety of factors that are specific to your team and facility, but any log should keep three key questions in mind:
Simplicity is your best friend here. Don’t make it hard for technicians to complete the log.
“It’s best to keep your descriptions short and have all the key details laid out plainly,” says Jason Afara, a solutions engineer at Fiix.
“My rule of thumb is to put the same amount of effort into your logs that you’d want if you were trying to fix an asset and reading the log for the first time.”
Above all, make sure you have a process that ensures accuracy. There are three simple rules that will help you keep the data in your logs are as accurate as possible:
Use a standard template for every asset. Equipment should be tracked and measured from the same baseline to avoid errors and make data analysis easier.
Keep your logs in a designated location. Bonus points for making them available on a digital-knowledge-hub/”>digital platform for quick access and a lower risk of damaging or losing them.
Create a routine for exchanging logs between shift changes. Keep everyone in the loop on completed or outstanding work, problems, safety risks, and other useful information.
Equipment maintenance log template
The template below is similar to the one Jason used during his time managing a maintenance team.
“We wanted a log that gave us everything we needed to know to get a historical base for our decision-making, but was simple enough to fill out and read,” says Jason, “If it felt like the effort of filling it in or reading it was not worth the result, it wasn’t going to be used appropriately.”
Make your team’s log its own. Customize it as much as you want as long as it captures the most important information is a way that’s easy to interpret.
Six ways to use the data in equipment maintenance logs
Well-kept equipment maintenance logs are great for looking into the past, but they can also help you create a better future for assets, the maintenance team, and the organization as a whole.
#1 Maximize equipment ROI
Equipment maintenance logs allow you to compare the record of equipment from different suppliers and see which one is more reliable. Choosing the more reliable vendor for future equipment purchases reduces the frequency of breakdowns, which means less spending on maintenance and more production.
Logs can also be the first indicator that equipment should be replaced rather than repaired. It’s possible to see if an asset is breaking down more often and compare the cost of the extra maintenance to the cost of a new asset.
A log is also proof that an asset has been maintained properly, which increases its resale value.
#2 Optimize preventive maintenance schedules and tasks
Well-kept logs tell you if a piece of equipment is breaking down right after scheduled maintenance or before its next scheduled maintenance date. If this becomes a pattern, it’s time to rethink how you’re performing preventive maintenance on that asset and tweak it to prevent breakdowns. Equipment maintenance logs also provide the information needed to make PMs quick, easy, and effective. For example, it tells technicians how past issues were resolved or if changes were made and how they impacted equipment.
#3 Track preventive maintenance compliance
You can plan as much maintenance as you want, but an equipment maintenance log can tell you if the work is actually being done. Logs clearly show when maintenance is scheduled and if any action was taken on that day. There’s no guessing and no searching. Logs are an early warning system for poor preventive maintenance compliance. It’s easier to solve the problem and avoid unplanned downtime when you can see the red flags from a mile away.
Create a routine for exchanging logs between shift changes. Keep everyone in the loop on completed or outstanding work, problems, safety risks, and other useful information.
#4 Identify opportunities to upgrade your maintenance strategy
You probably have a maintenance strategy for every piece of equipment. Maybe you settled on it after a lot of thought or perhaps that’s just the way it’s always been done. Whatever the case, equipment maintenance logs can help you find opportunities to improve this strategy. For example, are you using preventive maintenance when run-to-fail could be just as effective with lower costs? Is the asset a good candidate for condition-based maintenance? Looking for patterns in equipment maintenance logs is a way to answer those questions with data instead of hunches.
#5 Improve accountability and communication
Equipment maintenance logs bolster accountability and communication, two of the most important elements in a successful maintenance program.
“Logs are an additional form of communication and accountability for the maintenance team,” says Jason.
“They put people’s names beside the work and allow for the necessary communication between staff working different shifts.”
#6 Make training and onboarding easier
Detailed and well-organized maintenance logs help new technicians get up to speed quickly. Working with unfamiliar machines usually means a lot of time shadowing an experienced worker and a fair bit of trial and error. Not only is this unproductive, but it can also lead to more mistakes and breakdowns. Equipment maintenance logs provide new technicians with critical information about an asset, like age, common problems, and where to go if they need more details. They can learn faster, make decisions with confidence, and stay safe in the process
How to get data from an equipment maintenance log
There’s a lot of data in equipment maintenance logs, but that doesn’t mean all that data is useful. The most valuable information is accurate, quickly accessible, and laid out in a way that’s easy to understand. Using CMMS software is one way to check all those boxes.
A CMMS, especially a mobile CMMS, allows you to access equipment maintenance logs on any internet-connected device at any time, from anywhere
The software records and syncs data with other systems automatically so the information is always accurate and up-to-date
The CMMS connects to the maintenance calendar, which makes it easier to track who did what and how efficient the job was
Information from equipment maintenance logs are searchable on a CMMS, which means you can filter work by asset, tasks, date, technicians, and more
Data is securely stored in the cloud, so there’s no chance it’ll be lost or damaged, unlike paper records
You can attach pictures or videos to the maintenance log on a CMMS, making information more clear than just a written description
There’s more than meets the eye with equipment maintenance logs
Yes, equipment maintenance logs can be boring and repetitive. But with a small shift in thinking, they can also be used to unlock key insights and lead to higher assetperformance through data-driven maintenance. It all starts with a well-built template, strong processes, an understanding of what is possible, and the tools to act on your plan. When all those ingredients come together, equipment maintenance logs offer a way to use the past to create a better future for your facility and its assets.
Artificial intelligence (AI) is the cool kid at the lunch table. Peer pressure has the business collective telling each other, “Come on. Do some AI. Everyone’s doing it.” But are they doing it well? Jury’s out. According to the 2019 MIT SMR-BCG Artificial Intelligence Global Executive Study and Research Report, nine out of ten companies have made an investment in AI, yet 70% say they’ve seen minimal or no impact from AI to date.
It seems we may still be a few years away from feeling the real impact of AI — and a more realistic assessment of the value of AI. Forrester Research VP Srividya Sridharan says: “We believe 2020 will be the year when companies become laser-focused on AI value, leap out of experimentation mode, and ground themselves in reality to accelerate adoption.”
There are several AI trends on the horizon this year for IT leaders — and business leaders, at-large — to follow.
AI will be the sexy, new career path for IT professionals
There will be 133 million new jobs created by AI by 2022, according to the World Economic Forum’s (WEF) 2018 Future of Jobs report. The share of jobs requiring AI skills has grown 4.5 times since 2013. And for those worried about automation and it’s net effect on job displacement, by 2020, AI will eliminate 1.8 million jobs and create 2.3 million, according to VentureHarbor. Hiring for artificial intelligence pros of various titles has increased 74% annually over the last four years, according to LinkedIn.
All of these statistics speak to a new demand in the marketplace for AI and machine learning (ML) professionals — a demand that will spur up-and-coming IT practitioners to focus on AI as a main course of study.
Privacy and governance will come front-and-center in the AI conversation
When we talk AI and privacy, the discussion will center on facial recognition. In 2019, Facebook attempted to nullify a lawsuit that claimed the company had illegally collected and stored biometric data for millions of users without their consent, but a federal appeals court rejected it. Furthermore, the ACLU is prepared to pursue organizations using facial recognition for uses that could possibly jeopardize the constitutional privacy rights of individuals.
As far as data governance, 2020 will be about operationalizing AI, making governance a top priority. Forrester states in its 2020 AI predictions report that the problem for AI lies in “sourcing data from a complex portfolio of applications and convincing various data gatekeepers to play along.”
The focus will shift from simply having AI to measuring the impact of AI
Having AI for AI’s sake is passé now. Companies have made the investments and now they will use 2020 to figure out if that investment will bear fruit. “’When you do AI right, it generates value and ROI for the enterprise’ is an excellent premise, however the full potential of AI hasn’t been attained,” says AJ Abdallat, CEO of Beyond Limits. “Many conventional AI systems are merely machine learning, or neural networks, or deep learning. They’re good at handling large sets of data but lack situational awareness or the ability to navigate around missing or incomplete data. They get stuck.”
AI research will reduce speed
No one thinks that the research will come to a screeching halt, but the question is: Can it continue at the steep pace it has been? The demands that AI places on data and processing power may be too much to scale AI objectives, in some use cases — think self-driving cars. We’re still a way off. In an interview with Wired, last month, Facebook AI VP Jerome Pesenti said deep learning research may “hit the wall.”
Pesenti stated, “Clearly the rate of progress is not sustainable. If you look at top experiments, each year the cost is going up 10-fold. Right now, an experiment might be in seven figures, but it’s not going to go to nine or ten figures, it’s not possible, nobody can afford that.”
Closing thoughts
M-Files has pushed a lot of chips into the middle when it comes to AI in information management. We can verify that AI has risen to the hype, at least in our sector. It will remain a prominent focus of the IT community for years to come, no doubt. IDC figures that by 2025, embedded AI functionality will be incorporated in at least 90% of new enterprise application releases. To temper a bit though, IDC says that comes with a caveat: Truly disruptive AI-led applications will be only about 10% of this total.
AI ain’t going anywhere. But we’re still in a nascent stage, with lots of exciting innovation and healthy disruption to come.
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