Experiments in Fast Image Recognition on Mobile Devices – ReadWrite
Our journey in experimenting with machine vision and image recognition accelerated when we were developing an application, BooksPlus, to change a reader’s experience. BooksPlus uses image recognition to bring printed pages to life. A user can get immersed in rich and interactive content by scanning images in the book using the BooksPlus app.
For example, you can scan an article about a poet and instantly listen to the poet’s audio. Similarly, you can scan images of historical artwork and watch a documentary clip.
As we started the development, we used commercially available SDKs that worked very well when we tried to recognize images locally. Still, these would fail as our library of images went over a few hundred images. A few services performed cloud-based recognition, but their pricing structure didn’t match our needs.
Hence, we decided to experiment to develop our own image recognition solution.
What were the Objectives of our Experiments?
We focused on building a solution that would scale to the thousands of images that we needed to recognize. Our aim was to achieve high performance while being flexible to do on-device and in-cloud image matching.
As we scaled the BooksPlus app, the target was to build a cost-effective outcome. We ensured that our own effort was as accurate as the SDKs (in terms of false positives and false negative matches). Our solutions needed to integrate with native iOS and Android projects.
Choosing an Image Recognition Toolkit
The first step of our journey was to zero down on an image recognition toolkit. We decided to use OpenCV based on the following factors:
- A rich collection of image-related algorithms: OpenCV has a collection of more than 2500 optimized algorithms, which has many contributions from academia and the industry, making it the most significant open-source machine vision library.
- Popularity: OpenCV has an estimated download exceeding 18 million and has a community of 47 thousand users, making it abundant technical support available.
- BSD-licensed product: As OpenCV is BSD-licensed, we can easily modify and redistribute it according to our needs. As we wanted to white-label this technology, OpenCV would benefit us.
- C-Interface: OpenCV has C interfaces and support, which was very important for us as both native iOS and Android support C; This would allow us to have a single codebase for both the platforms.
The Challenges in Our Journey
We faced numerous challenges while developing an efficient solution for our use case. But first, let’s first understand how image recognition works.
What is Feature Detection and Matching in Image Recognition?
Feature detection and matching is an essential component of every computer vision application. It detects an object, retrieve images, robot navigation, etc.
Consider two images of a single object clicked at slightly different angles. How would you make your mobile recognize that both the pictures contain the same object? Feature Detection and Matching comes into play here.
A feature is a piece of information that represents if an image contains a specific pattern or not. Points and edges can be used as features. The image above shows the feature points on an image. One must select feature points in a way that they remain invariant under changes in illumination, translation, scaling, and in-plane rotation. Using invariant feature points is critical in the successful recognition of similar images under different positions.
The First Challenge: Slow Performance
When we first started experimenting with image recognition using OpenCV, we used the recommended ORB feature descriptors and FLANN feature matching with 2 nearest neighbours. This gave us accurate results, but it was extremely slow.
The on-device recognition worked well for a few hundred images; the commercial SDK would crash after 150 images, but we were able to increase that to around 350. However, that was insufficient for a large-scale application.
To give an idea of the speed of this mechanism, consider a database of 300 images. It would take up to 2 seconds to match an image. With this speed, a database with thousands of images would take a few minutes to match an image. For the best UX, the matching must be real-time, in a blink of an eye.
The number of matches made at different points of the pipeline needed to be minimized to improve the performance. Thus, we had two choices:
- Reduce the number of neighbors nearby, but we had only 2 neighbors: the least possible number of neighbors.
- Reduce the number of features we detected in each image, but reducing the count would hinder the accuracy.
We settled upon using 200 features per image, but the time consumption was still not satisfactory.
The Second Challenge: Low Accuracy
Another challenge that was standing right there was the reduced accuracy while matching images in books that contained text. These books would sometimes have words around the photos, which would add many highly clustered feature points to the words. This increased the noise and reduced the accuracy.
In general, the book’s printing caused more interference than anything else: the text on a page creates many useless features, highly clustered on the sharp edges of the letters causing the ORB algorithm to ignore the basic image features.
The Third Challenge: Native SDK
After the performance and precision challenges were resolved, the ultimate challenge was to wrap the solution in a library that supports multi-threading and is compatible with Android and iOS mobile devices.
Our Experiments That Led to the Solution:
Experiment 1: Solving the Performance Problem
The objective of the first experiment was to improve the performance. Our engineers came up with a solution to improve performance. Our system could potentially be presented with any random image which has billions of possibilities and we had to determine if this image was a match to our database. Therefore, instead of doing a direct match, we devised a two-part approach: Simple matching and In-depth matching.
Part 1: Simple Matching:
To begin, the system will eliminate obvious non-matches. These are the images that can easily be identified as not matching. They could be any of our database’s thousands or even tens of thousands of images. This is accomplished through a very coarse level scan that considers only 20 features through the use of an on-device database to determine whether the image being scanned belongs to our interesting set.
Part 2: In-Depth Matching
After Part 1, we were left with very few images with similar features from a large dataset – the interesting set. Our second matching step is carried out on these few images. An in-depth match was performed only on these interesting images. To find the matching image, all 200 features are matched here. As a result, we reduced the number of feature matching loops performed on each image.
Every feature was matched against every feature of the training image. This brought down the matching loops down from 40,000 (200×200) to 400 (20×20). We would get a list of the best possible matching images to further compare the actual 200 features.
We were more than satisfied with the result. The dataset of 300 images that would previously take 2 seconds to match an image would now take only 200 milliseconds. This improved mechanism was 10x faster than the original, barely noticeable to the human eye in delay.
Experiment 2: Solving the Scale Problem
To scale up the system, part 1 of the matching was done on the device and part 2 could be done in the cloud – this way, only images that were a potential match were sent to the cloud. We would send the 20 feature fingerprint match information to the cloud, along with the additional detected image features. With a large database of interesting images, the cloud could scale.
This method allowed us to have a large database (with fewer features) on-device in order to eliminate obvious non-matches. The memory requirements were reduced, and we eliminated crashes caused by system resource constraints, which was a problem with the commercial SDK. As the real matching was done in the cloud, we were able to scale by reducing cloud computing costs by not using cloud CPU cycling for obvious non-matches.
Experiment 3: Improving the Accuracy
Now that we have better performance results, the matching process’s practical accuracy needs enhancement. As mentioned earlier, when scanning a picture in the real world, the amount of noise was enormous.
Our first approach was to use the CANNY edge detection algorithm to find the square or the rectangle edges of the image and clip out the rest of the data, but the results were not reliable. We observed two issues that still stood tall. The first was that the images would sometimes contain captions which would be a part of the overall image rectangle. The second issue was that the images would sometimes be aesthetically placed in different shapes like circles or ovals. We needed to come up with a simple solution.
Finally, we analyzed the images in 16 shades of grayscale and tried to find areas skewed towards only 2 to 3 shades of grey. This method accurately found areas of text on the outer regions of an image. After finding these portions, blurring them would make them dormant in interfering with the recognition mechanism.
Experiment 4: Implementing a Native SDK for Mobile
We swiftly managed to enhance the feature detection and matching system’s accuracy and efficiency in recognizing images. The final step was implementing an SDK that could work across both iOS and Android devices like it would have been if we implemented them in native SDKs. To our advantage, both Android and iOS support the use of C libraries in their native SDKs. Therefore, an image recognition library was written in C, and two SDKs were produced using the same codebase.
Each mobile device has different resources available. The higher-end mobile devices have multiple cores to perform multiple tasks simultaneously. We created a multi-threaded library with a configurable number of threads. The library would automatically configure the number of threads at runtime as per the mobile device’s optimum number.
To summarize, we developed a large-scale image recognition application (used in multiple fields including Augmented Reality) by improving the accuracy and the efficiency of the machine vision: feature detection and matching. The already existing solutions were slow and our use case produced noise that drastically reduced accuracy. We desired accurate match results within a blink of an eye.
Thus, we ran a few tests to improve the mechanism’s performance and accuracy. This reduced the number of feature matching loops by 90%, resulting in a 10x faster match. Once we had the performance that we desired, we needed to improve the accuracy by reducing the noise around the text in the images. We were able to accomplish this by blurring out the text after analyzing the image in 16 different shades of grayscale. Finally, everything was compiled into the C language library that can be used with iOS and Android.
How Emerging Technology Is Helping Teams Save on Development Costs
Software developer pay spans a notoriously wide range, but few would argue that U.S.-based development costs are “cheap.”
According to a U.S. News & World Report analysis, the median U.S. software developer earned $120,730 in 2021. Experienced devs can easily command $200,000 per year in cash compensation alone, with incentive pay and company benefits adding significantly to that total.
You most likely know this already. You also most likely know that complex software development projects take months and involve multiple developers and engineers. “Cost spiral” doesn’t begin to describe the situation.
You don’t need to be reminded how important it is to cut DevOps costs wherever possible. Your bosses and shareholders (perhaps one and the same) remind you enough.
Fortunately, emerging technologies and tools are making it easier than ever to reduce software development expenses without compromising output, efficiency, or quality. It’s no exaggeration to say that these new capabilities are revolutionizing software development and helping DevOps teams save money across the board.
Let’s take a closer look at four types of emerging capabilities: next-generation project management tools, cloud computing services, task automation tools, and ephemeral development environments. Each offers potentially game-changing opportunities for teams looking to work faster, smarter, and more efficiently.
Using next-generation project management tools to drive software development efficiency and collaboration
Signs of bad project management include missed deadlines, poor quality control, and infighting within teams that need to collaborate closely. These and other direct results of poor project management are harmful to the broader organization (and to the careers of those responsible for them).
Yet poor project management has a direct financial cost as well. This goes back to what we’ve already discussed: the high cost of labor in a product development environment and, specifically, the very high cost of labor in a software development context. Every day that passes without an anticipated deliverable is a day that brings unanticipated costs. And while every project budget has some built-in wiggle room, said costs eventually become unacceptable.
The good news is that software development teams can turn to an already-existing library of scalable, easy-to-use project management tools that easily map to DevOps use cases. Your team may already use some basic project management tools to manage workflows and keep track of deliverables, timeframes, and responsibilities. Still, if you haven’t surveyed the landscape and assessed individual tools’ capabilities relative to your team’s needs, you’re likely not maximizing their potential.
Look for project management tools with the following capabilities:
- Use cases specifically designed for your specific development framework. For example, Jira’s project management tool is specifically tailored to Agile development teams.
- Relevant integrations with third-party apps, from general-purpose tools like Google Docs (where your spreadsheets likely live already) to DevOps, cloud storage, and even CRM software.
- Sophisticated calendar views that enable visual-oriented team members to “see” their project responsibilities at a glance.
- Powerful developer APIs that allow you to customize the project management interface to your needs and produce efficiency-oriented outputs.
Ideally, your team relies on one core project management tool to manage everything it’s working on together, with individual developers free to use additional tools to manage their personal workflows.
That may require you to cut out a less optimal tool (or several) and disrupt legacy use cases, but it’s better to rip off the Band-Aid now before a bona fide productivity crisis hits. Further down the road, untangling competing and deeply entrenched workflows will surely prove more costly and more disruptive.
Leveraging cloud computing services for projects with multiple stakeholders
Like project management software, cloud computing services no longer count as revolutionary. If your team is small, it might use GSuite for cloud-based storage and collaboration. If it’s larger, it might use Microsoft Azure or Amazon Web Services (whose incomprehensible value only underscores the critical importance of cloud computing).
And so you’re already aware that cloud computing services make development more efficient by enhancing collaboration, reducing duplication of effort, and sharply cutting reliance on onsite database hosting, file storage, and data processing.
Your team can and should use cloud computing services in additional ways that even more directly improve DevOps efficiency and cost control:
- Containerization: Containerization enables software deployment on any computing infrastructure. Bundling app code and file libraries in a self-contained, platform-agnostic unit eliminate the need to match platform-specific software packages (i.e., Windows-compatible) with the correct machines. Containerized deployment is more portable, more scalable, and more resilient — and it’s only possible in the cloud.
- Microservices (vs. monolithic architecture): Microservices break up the development architecture into many small, agile units that communicate via API. Rather than an inflexible “monolith” that needs to be reworked as it scales, microservices can be scaled internally (or new ones created) as needs arise. Like containerization, it’s a much more flexible, agile, and ultimately low-cost way to manage complex DevOps workflows.
Automating repetitive tasks throughout the development lifecycle
Task and workflow automation tools are improving at an incredible clip, and the advantages of next-generation automation are particularly impressive for DevOps teams. As just one example, telecom giant Ericsson drove significant cost savings by automating key aspects of their software development pipeline and transitioning to a continuous deployment model, according to a study published in Empirical Software Engineering.
Transitioning to continuous deployment is a time- and cost-intensive process that may not be practical for smaller teams, at least not in the near term. But your team can leverage task automation in many other ways.
Testing automation deserves special mention here. Automated testing and QA solutions like Robot Framework and Zephyr (respectively) reduce the need for repetitive, labor-intensive poking and prodding by human devs whose efforts are better spent elsewhere. By finding bugs and quality issues earlier in the development workflow, they also reduce the need for costly and time-consuming fixes further along in the process.
Increasingly, code generation itself is automated, thanks to tools like Eclipse. These generative tools will only improve as processing power increases and training sets expand. Consequently, this sets the stage for a near-future scenario where devs will need to manually write far less code. That, in turn, will allow DevOps teams to stretch dev resources further. Additionally, it will free up person-hours for more creative or problem-focused work.
Utilizing ephemeral environments to improve development speed and quality
Finally, software development teams can achieve efficiency and cost improvements at virtually any scale by utilizing ephemeral environments. These are temporary staging environments that can be created at will, generally for a single-purpose feature test or bug fix, and then eliminated when no longer needed to keep costs low.
Ephemeral environments offer clear advantages for development teams. They reduce pull request backlogs, a notorious sticking point (and cost driver) for larger teams. They’re isolated, which reduces the risk of bug-inducing branch conflicts. They’re fully automated, which frees up engineers to deal with more important matters. And because they enable more targeted, granular testing, they speed up the development process overall. They also reduce the risk of an unacceptable issue breaching the main code branch. Repairs on the main code branch are much more time-consuming and costly.
The result is a faster, more efficient workflow that scales with your team in response to demand. For example, Uffizzi’s on-demand ephemeral environment tool helped Spotify add 20% more features to every release of its popular Backstage developer portal platform. Backstage grew rapidly after initial open-sourcing in 2020 and now averages some 400 active pull requests per month. The transition to ephemeral environments slashed average pull request completion times across the platform.
Ephemeral environments can also help smaller development teams achieve the same economies of scale as larger teams. For example, moving to a continuous deployment model might seem out of reach for small teams under the old “bottlenecked” shared environment framework. Start by streamlining this process and freeing up department resources for longer-term strategic work. Ephemeral environments (and other process automation tools) make such shifts possible.
It’s no accident that Uffizzi’s out-of-the-box ephemeral environment solution supercharges the continuous integration/delivery process.
Opportunities abound now, with more to come
Change is already here for software teams accustomed to the old way of doing things. These four emerging or expanding technologies and tools —
- Next-generation project management software
- Expansive and flexible cloud computing services
- Increasingly intelligent and capable task automation tools
- Scalable, on-demand ephemeral environments for better testing and QA
— are making life easier and development faster for DevOps departments around the world. Their capabilities and use cases will only expand as time goes on.
These four technologies aren’t the only emerging opportunities for software developers and the companies that employ them, however. Around-the-bend and over-the-horizon capabilities could change the tech industry in even more fundamental ways:
- AI-driven platforms for developers, like TensorFlow, that promise to dramatically speed up development timeframes and allow teams to do much more with much less
- Infrastructure as Code (IaC) capabilities that break down silos between DevOps teams and the rest of an organization and create trusted, reliable code frameworks that ultimately reduce developer and maintainer workloads
- Low- and no-code application development, which — while possibly overhyped in the short term — could further break down barriers and enable faster, more collaborative action
- Augmented reality tools and apps, whose potential impact remains speculative but which will likely play an increasingly important role in software and product development over the next decade
In the coming years, odds are you’ll integrate all four of these capabilities into your DevOps workflows by then. You’ll most likely take advantage of other emerging technologies and tools in the near future too. These may even include some we don’t yet know about. As the pace of innovation accelerates, staying one step ahead of the competition — and doing right by your firm’s stakeholders, financially and otherwise — means watching closely for new tech that can speed up your development timelines and reduce overall DevOps costs.
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Featured Image Credit: Photo by Pixabay; Pexels; Thank you!
Eco-Friendly Fleet Maintenance Trends and Strategies
As the world becomes increasingly aware of the impact of climate change, many businesses are seeking ways to mitigate their carbon footprint and embrace more sustainable practices. In the transportation industry, fleet maintenance is a key area where businesses can make significant strides in reducing their environmental impact.
The Big Issues With Today’s Fleet Maintenance
There are several environmental issues associated with today’s fleet maintenance practices. Here are some of the biggest:
Greenhouse Gas Emissions
Fleet vehicles are a significant source of greenhouse gas emissions, contributing to climate change. The emissions from fuel combustion and the use of heavy-duty vehicles can have negative impacts on air quality, water quality, and human health.
Hazardous Waste Disposal
Many fleet maintenance activities generate hazardous waste, such as used oil, solvents, and other chemicals. If not disposed of properly, these can contaminate soil and water, posing a risk to human health and the environment.
Fleet maintenance requires significant resources, including energy, water, and raw materials. The extraction and processing of these resources can have negative impacts on the environment, including habitat destruction, deforestation, and water pollution.
Fleet maintenance activities can be noisy, especially in urban areas. This can have negative impacts on wildlife and human health, contributing to stress and hearing damage.
Land Use and Habitat Destruction
The construction and maintenance of fleet facilities, such as maintenance yards and parking lots, can require significant amounts of land. This can lead to habitat destruction and loss of biodiversity.
Overall, fleet maintenance has significant environmental impacts, and addressing these issues will require a comprehensive approach that includes the adoption of sustainable practices, the use of alternative fuels and technologies, and the implementation of environmentally responsible waste management practices.
7 Eco-Friendly Fleet Maintenance Tips
Aligning a company’s fleet maintenance approach with larger green initiatives and eco-friendly mission statements has never been more practical. Here are several helpful tips and strategies to get you started:
1. Switch to Alternative Fuels
One of the most effective ways to make fleet maintenance more eco-friendly is to switch to alternative fuels. Traditional gasoline and diesel-powered vehicles produce a significant amount of greenhouse gas emissions. Alternative fuels, like electricity, biofuels, and even hydrogen, produce fewer emissions and can help reduce a company’s carbon footprint.
Electric vehicles (EVs) are becoming increasingly popular as a sustainable transportation option. EVs produce zero emissions and are typically much cheaper to maintain than traditional vehicles. Hydrogen fuel cell vehicles are also an option, producing only water as a byproduct. Biofuels, which are made from renewable sources like corn and soybeans, can also be used in some vehicles.
2. Use Sustainable Products and Materials
In addition to alternative fuels, businesses can also make fleet maintenance more eco-friendly by using sustainable products and materials. Here are some examples:
Biodegradable cleaning products: Traditional cleaning products can contain chemicals that can be harmful to the environment. Biodegradable cleaning products are a more sustainable alternative as they are made from natural, non-toxic ingredients that break down quickly and safely.
Recycled materials: Using recycled materials, such as oil and tires, can help reduce waste and conserve natural resources. Recycled oil can be re-refined and used again, while recycled tires can be turned into rubberized asphalt, which can be used to pave roads.
Eco-friendly lubricants and fluids: Using eco-friendly lubricants and fluids, such as biodegradable hydraulic fluids and biodegradable grease, can help reduce pollution and protect the environment.
Sustainable packaging: When purchasing products and materials for your fleet maintenance, look for sustainable packaging options, such as products that are shipped in recyclable or biodegradable packaging.
By using sustainable products and materials in fleet maintenance, you can help reduce your environmental footprint and promote sustainability.
3. Conduct Regular Preventive Maintenance
Fleet maintenance software can be a powerful tool for managing preventive maintenance as part of a green fleet management strategy. Here are some steps to help you use fleet maintenance software to perform preventative maintenance:
Set up a preventative maintenance schedule: The first step is to set up a maintenance schedule in your fleet maintenance software. This schedule should include regular maintenance tasks such as oil changes, tire rotations, and other routine maintenance tasks that will help keep your vehicles running efficiently and reduce emissions.
Track vehicle usage: Your fleet maintenance software should be able to track vehicle usage, including mileage, hours of operation, and other relevant data. This information can help you schedule maintenance tasks based on actual use rather than just time intervals, which can help reduce unnecessary maintenance and waste.
Use eco-friendly parts and materials: When performing preventive maintenance, make sure to use eco-friendly parts and materials whenever possible. This can include using recycled oil, eco-friendly tires, and other environmentally friendly products.
Monitor fuel consumption: Your fleet maintenance software should also be able to track fuel consumption for each vehicle in your fleet. By monitoring fuel consumption, you can identify inefficiencies and make adjustments to improve fuel economy, which can help reduce emissions.
Analyze data and adjust your strategy: Finally, use the data collected by your fleet maintenance software to analyze your fleet’s performance and adjust your strategy as needed. For example, if certain vehicles are consistently underperforming or require more frequent maintenance, consider replacing them with more fuel-efficient models.
The good news is that implementing fleet management software into your company’s strategy isn’t nearly as challenging or intensive as you might think. Thanks to artificial intelligence and machine learning, the upfront setup is much faster and more efficient than you may realize. This allows you to get up and running quickly.
4. Implement More Efficient Routing
Efficient routing is another strategy for making fleet maintenance more sustainable. By optimizing routes, businesses can reduce the amount of fuel their vehicles consume and the emissions they produce. This not only helps the environment but can also save the company money on fuel costs.
GPS and fleet management software can help companies optimize their routes and reduce fuel consumption. These tools can provide real-time data on traffic patterns, road closures, and weather conditions, allowing businesses to make informed decisions about their routes.
5. Promote Better Driver Education
Another important aspect of eco-friendly fleet maintenance is promoting driver education. Drivers who are trained in eco-friendly driving techniques can help reduce fuel consumption and emissions. This includes techniques such as reducing idling time, avoiding sudden accelerations and braking, and maintaining a steady speed.
In addition to driver education, businesses can also encourage their drivers to adopt sustainable habits, such as carpooling and using public transportation when possible. This not only reduces the company’s carbon footprint but can also save employees money on commuting costs.
6. Use Telematics Technology
Telematics technology refers to the use of wireless communication systems and GPS technology to transmit data from vehicles to a remote location. This technology allows businesses to track and monitor the performance of their fleet vehicles, including fuel consumption, emissions, speed, and location.
By collecting this data, telematics technology can help businesses optimize their fleet operations to make them more energy-efficient and green. Here are some of the ways that telematics technology can be used to improve fleet sustainability:
Route Optimization: Telematics systems can provide real-time traffic updates, road closures, and weather conditions to help businesses optimize their vehicle routes. By choosing the most efficient route, fleet managers can reduce fuel consumption and emissions while ensuring on-time deliveries.
Fuel Efficiency Monitoring: Telematics technology can track fuel consumption in real-time, giving fleet managers insights into how their vehicles are performing. By identifying patterns of inefficient driving or idling, businesses can take steps to reduce fuel consumption and emissions.
Maintenance Alerts: Telematics technology can also alert businesses when a vehicle is due for maintenance or repairs. By staying on top of maintenance, businesses can ensure that their vehicles are running at peak efficiency.
Driver Behavior Monitoring: Telematics technology can monitor driver behavior, including acceleration, braking, and speed. By identifying patterns of inefficient driving, businesses can provide coaching and training to drivers to help them improve their driving habits.
7. Reduce Vehicle Weight
Reducing the weight of fleet vehicles can also make maintenance more eco-friendly. The heavier a vehicle is, the more fuel it requires to move, which means it will produce more emissions. By reducing the weight of their vehicles, companies can reduce the amount of fuel they consume and the emissions they produce.
This can be achieved by removing unnecessary equipment and cargo from the vehicles, as well as using lightweight materials for vehicle maintenance. For example, aluminum wheels and carbon fiber parts can be used to reduce the weight of the vehicle.
Turn Your Fleet Green
Implementing eco-friendly fleet maintenance practices not only benefits the environment. It can also help businesses save money in the long run. By reducing fuel consumption and emissions, companies can lower their operating costs and improve their reputation as a sustainable business.
Use the tips highlighted above to reorient the way your business approaches fleet maintenance in 2023 and beyond.
Image Credit: by Lê Minh; Pexels; Thanks!
5 Essential Benefits of Choosing an Efficient ERP System
The corporate world is changing at a fast pace, and advanced technologies such as ERP system is at the epicenter of the ongoing digital revolution. Businesses are more dependent on technological tools and enterprise software than ever before. In fact, these tools and software are enabling businesses to drive greater success by enhancing business processes. Are you ensuring that you have the right software and tools to help your business advance swiftly?
There is a plethora of software and solutions to choose from, and each of them comes with its own merits. But what is making a real difference is the integration of Enterprise Resource Planning (ERP) systems that can streamline processes across various verticals in an enterprise.
The use of ERP systems defines a new trend altogether in the modern workplace.
Gone are the days when only multinational companies subscribed to ERP solutions for managing processes at the entire enterprise level. Nowadays even small businesses are bridging ERP systems onboard to facilitate business advancement. To validate, as per statistics, the global market size for ERP software is expected to reach USD 96.7 billion by 2024. Finances Online further explains that more than 52 percent of organizations are highly satisfied with the decision of integrating ERP systems.
Probing further, vertical ERP, small business ERP, generalist ERP, and Open Source ERP is among the most common types of ERP software that businesses are integrating. Moreover, it is also notable that most organizations are showing a keen interest in Cloud-Based SasS ERP systems, given the edge they have over traditional ERP.
All in all, the integration of ERP systems has become one of the most sought-after change management activities in the corporate world. The question is, what are the advantages of ERP software that businesses are subscribing to ERP solutions? Let us find out in this blog.
Key benefits of ERP Systems for businesses
1. Massive optimization of productivity
The ultimate objective of every enterprise is to drive the highest productivity across every vertical. However, when your employees work on recurring and repetitive tasks, not only their individual productivity takes a hit, but the efficiency of the entire organization takes a setback. This explains why businesses increasingly spend on automation tools to streamline repetitive tasks like invoicing. Even marketing automation is one of the thriving corporate trends.
All in all, the greater the automation in an enterprise the higher will be the productivity. Having said that, this is where we must look at one of the greatest benefits of integrating ERP systems. To substantiate, ERP systems come with incredible and reliable automation capabilities that can help your organization achieve its business objectives at a greater pace.
Moreover, with AI integrations as per the latest developments, the automation capabilities of ERP systems are much higher than ever before. To substantiate, as per Netsuite, employers are now happily investing in advanced ERP solutions that come with intelligent AI or machine learning capabilities.
Needless to say, artificial intelligence is the way forward for enterprises, and the blend of ERP and AI is worth embracing. This combination will certainly give your business an unparalleled competitive advantage.
2. Real-time analytics
Having timely access to analytics that can help you constantly enhance processes is nothing short of having a competitive advantage. In fact, everything in the modern enterprise world revolves around analytics. From analytics on customer engagement to analytics on inventory management gaps, you need analytics at almost every step.
This is where ERP comes up with another great feature that you should definitely not ignore. An efficient ERP system can generate real-time quantitative analytics that can lead to better planning, execution, and monitoring. Besides, the best part is that with an ERP, you can create data analytics capabilities in your businesses without even having to hire a dedicated team for data analytics.
Moreover, real-time analytics will also ensure that there is a smoother workflow management and will also aid in effective collaboration between teams. Especially if your project teams work remotely, it is essential that there is real-time sharing of data analytics for project success. ERP does not only automate data generation but also data reporting in a presentable and lucid form. However, in the ultimate sense, the positive impact of ERP is subject to the efficiency of your change management process.
3. Greater cost-efficiency in operations
Irrespective of whether you are a budding startup or an established business, operational costs will always be a top concern for you. The correlation is quite simple, the lower the operational costs the higher will be the profitability. Now, the question is, can ERP help you in bringing down operational costs? Well, the answer is a big yes and it is time you acknowledge that.
To validate, as per Datix, ERP solutions can help organizations reduce operational costs by 23 percent. This clearly indicates that you can save a major chunk of operational costs by investing in the best-in-class ERP solution. The sooner you bring ERP onboard, the greater the savings.
4. Magnification of data security
It is a well-known fact that the contemporary corporate world has a massive dependence on big data. Every business process in the modern corporate world has data engineering and analytics at the forefront of things. Data security has become a top concern, especially when cyber-attacks and data breaches are more advanced than ever before.
One of the most compelling reasons why your business needs ERP is the set of advanced data security features. When an ERP is integrated into business processes, you can set controls for accessibility to confidential data. To explain, you can control who can access sensitive information and who cannot.
Otherwise, in the absence of an ERP system, you will have to spend fortunes on cyber security and data security solutions. ERP gives you multidimensional benefits of optimized business processes along with credible data security measures.
5. Enhanced flexibility
Does your organization have a traditional on-site working style or a hybrid working style? Are you planning to move your employees to permanent work from home? ERP gives you great flexibility irrespective of your organization’s working style. Simply put, ERP can be easily integrated even in remote working cultures or hybrid cultures and will also help you to avoid employee burnout (seodiggerz dotcom “help employees avoid burnout). You can implement an ERP system with great ease and put it to work from the word go.
Besides, ERP systems also offer great flexibility in terms of future scalability. If your business is expanding and you want to add more users in the future, ERP systems offer the room to do so. Room to expand has to be the most important feature you should be looking for when you choose an ERP system. Not every ERP system may come with an effective scope of future scalability. Still, you will find a lot of ERP systems that do offer scalability features and you must choose from them.
ERP systems are changing the way businesses approach their operations and key objectives. Besides, ERP is much more than a planning resource and offers immense value in terms of optimizing business processes.
Integrating ERP for your business can be a real game changer. The sooner you subscribe to it, the more advantageous it will prove to be for your business. Make sure you choose an ERP software that is best suited for your enterprise.
Featured Image Credit: Photo by Erik Mclean; Pexels; Thank you!