<img src="https://secure.leadforensics.com/133892.png" alt="" style="display:none;">

Organizations that have not yet moved to the Cloud are concerned about security and accessibility. The bigger issue—and one that isn't as obvious as the other two—is a lack of clarity about the ownership costs of on-premises versus the cloud.

We'll look at both the obvious and hidden total costs of ownership-on-premises and cloud-based solutions in this blog. Our goal is to:

  • Equip you with the necessary insights into the cost of cloud vs. on-premises to make a well-informed decision
  • Help you gain a competitive edge through scaled-up innovation and growth

The iceberg image below illustrates a comparative analysis of the complexities involved in implementing an on-premises system versus a Cloud-based one:

On-premises vs. Cloud-based

Source: https://www.peoplehr.com/blog/2015/06/12/saas-vs-on-premise-hr-systems-pros-cons-hidden-costs/

Cost comparison between cloud-based solutions and on-premises infrastructure:

  1. Setting up and implementation
    a. Traditional on-premises software:
    • Involves both software and hardware expenses, which drive up cost of on premises software
    • On-premises costs are expensive since it requires upgrades and maintenance
    • On-premises can cost nearly a million dollar to install, implement. Another side effect, is wastage of valuable resources

    b. Cloud-based software:
    • No hardware or software purchase is required. On-premises can cost nearly a million dollar to install, implement. Another side effect, is wastage of valuable resources On-premises can cost nearly a million dollar to install, implement. Another side effect, is wastage of valuable resources
    • Cloud services providers handle infrastructure- and upgrades-related costs. Upgrades happen seamlessly over a weekend or during off-business hours
    • Subscribers of the cloud have the flexibility to start, end or modify subscriptions according to their needs compared to on-premises solutions
  2. Cloud vs. On-Premises Security- breaches and integration
    a. Traditional on-premises software:
    • Close proximity of servers’ compromises on-premises security
    • Legacy data centers are threatened because of outdated security measures and software, leaving on-premises software open to attacks
    • Integration is complicated, laborious and requires meeting many parameters-based criteria to obtain accurate results

    b. Cloud-based software:
    • Cloud security is better when compared to on-premises. Since, physical data breaches due to negligent employees are less likely to happen since data is stored on the Cloud
    • Cloud service providers invest in cloud security protocol and software to prevent data breached and cyberattacks
    • Computing to the cloud comes with several built-in functionalities to support quick and seamless integrations
  3. Scalability
    a. Traditional on-premises software:
    • Being bound by limited physical space to accommodate hardware adds up the costs of maintaining an on-premises software
    • Handling of new infrastructure needs a larger workforce. This means hiring new employees which is an additional cost for a company

    b. Cloud-based software:
    • Cost of maintaining cloud-based software is economical in the long run since physical space constraints do not apply in this case
    • Cloud based service providers offer technical support (setting up plus maintenance)—in comparison to on-premises systems—so there is no additional cost on that score

Measurable success

"If you can't measure it, you can't improve it." – Peter Drucker, Eminent management consultant

To gauge whether you should (or should not) migrate to the Cloud, you need full visibility into your metrics. If you choose to stay with a traditional on-premises system, you are likely to endure unexpected expenditures related to maintenance, support, hardware and software (to meet unplanned requirements).

Cloud-based-ERP-supports-better-business-outcomes

Source: Aberdeen Group studies

Migrating to the Cloud not only allows your business to lessen capital outlay and operating costs, but it also provides reliability and scalability.

With technology evolving even as this piece was being written, the Cloud is proving to be the most viable option for businesses of all sizes across industries from a flexibility, enhanced security, and significant cost and time savings perspective.

At Columbus, we have been helping organizations make the journey to the Cloud for more than three decades. We specialize in offering the best packaged solution to organizations depending on their unique needs. Please write to us to learn more at us-marketing@columbusglobal.com.

Next Read: [Webinar] Cloud Migration Best Practices

Topics

Discuss this post

Recommended posts

Achieving a deeper understanding of the information that's already available to you can trigger major breakthroughs for your business, helping you exceed your goals and propelling you toward opportunities that you might not have even considered. The key to those breakthroughs is figuring out how to unlock the hidden insights in your data. That can seem like a daunting task, given the truly dizzying amounts of data available to businesses in the Industry 4.0 era — especially if they're getting real-time data from thousands of IoT devices. Connecting the dots isn't so hard when you've got a small and manageable set of dots to connect. But as the number of data points increases, the possible connections between them grow exponentially, and it takes a lot of computing power to precisely map all those connections and surface the important patterns and trends. That's part of why the neural networks that power AI and machine learning are so transformative. They make it possible to cut through the noise and detect patterns that would otherwise get missed. How AI Provides Superior Insights You might also think of AI as functioning a bit like a pair of 3D glasses: It helps you see things that would be unclear without it. By using Microsoft's Power BI dashboards, for example, you can draw on the power of AI to monitor your data, surface the important metrics, and then tell the story through powerful and easy-to-understand visualizations. These robust data dashboards can help you do everything from detecting security breaches to figuring out which products are most successfully driving your revenue. Boosting Sales with Better Product Pairings Some product pairings are obvious: syrup with pancakes, or paintbrushes with cans of paint. But others are more subtle and may not be apparent without the powerful combination of a strong foundational set of data and AI-powered analytics, which can help identify those less obvious complementary sales products. For instance, using AI can highlight that when you position product A alongside product B, you can experience a substantial boost of 5% in sales—a significant advantage for your business. How Machine Learning Helps Stop the Churning Spotting and addressing customer churn is another great example of what machine learning can do. It costs more to acquire new customers than to hold on to the ones you have, so the ability to use analytics to detect customers who are drifting way, or at risk of being captured by your competitors, is potentially game-changing. Using predictive analytics, you can reach out to those customers whose interest is waning with well-timed discounts and promotions, or even develop subscription-based models or loyalty programs to help keep them in the fold. Defeating Downtime with Predictive Insights We frequently see manufacturing facilities that are depending on one or two mission-critical machines that do 80% of their business — and those machines are often running 24/7. If one of those machines goes down, the result is painful downtime that can lead to production delays, revenue losses, and unhappy customers. Both your bottom line and your top line wind up taking a hit. But thanks to machine learning and IoT sensors, you can draw on real-time data to identify equipment that may be getting too hot, going out of tolerance, or at risk of developing other kinds of diagnosable hiccups and coughs. And then you can step in to make sure those sine qua non machines continue to function on schedule, protecting your balance sheet and keeping your customers happy. Data That's More Than a Fair-Weather Friend MRP is another place where predictive analytics can help put you ahead of the game. Maybe you're using a kind of "brute force" accounting to decide how to allocate costs among ten different product lines — 20% here, 5 percent there, etc. But with predictive analytics, you can get more sophisticated. You can identify trends like seasonality and other less-apparent cycles, so you can change allocations dynamically to match trends you wouldn't have otherwise known about. Machine learning allows you to factor in a lot of external data that goes beyond what's in your own ERP. Like weather data, for example. Suppose you have a product line that's very sensitive to heat or humidity. You might be able to draw on weather data to augment your existing data, so you can change the chemical properties of the product to make it more humidity resistant. Columbus recently worked with a retail organization that sells high-end outdoor products as a major component of their business. They found that some sizes and products sold better in certain stores than others, and they wanted a better understanding of the optimal product mix in each store. That's the kind of complicated data picture that machine learning can help you bring into focus. One of the other key questions they needed to answer was weather-related: when to bring out the heavier gear, like winter gloves or insulated vests and jackets. So, the ability to analyze weather trends and patterns offered an opportunity to achieve better timing and improve their margins. There are plenty of other ways that the capabilities of AI can help you make it rain — or provide an umbrella to get you through downturns and disruptions. To learn more, schedule a call with Columbus so we can help your organization tap into the full capabilities of AI.
As we begin 2024, it's no longer a question of whether to adopt AI-driven tools and strategies. These days, forward-thinking business leaders are actively considering how to adopt and implement AI successfully, in order to minimize risks and maximize the strategic rewards.
Some of the most exciting capabilities of current ERP systems — the ones with the potential to put ambitious new business goals within your reach — are the ones that leverage the impressive recent advances in artificial intelligence. Experienced leaders know that to reap the rewards of new technology, you need to be clear-eyed and fully aware of the potential rewards and opportunities, as well as the pitfalls that need to be avoided. What do you need to know to take full advantage of the fusion of ERP and AI, without running into unexpected obstacles and dangers? Ultimately, there's no substitute for careful planning, forethought, and guidance from ERP experts. How Do ERP and AI Work Together to Benefit Business? One of the most important ways that AI boosts the capabilities of ERP systems is by helping companies recognize patterns and make predictions. With AI-powered ERP software, you can forecast everything from sales and cashflow to supply chain disruptions and the need for preventive maintenance of equipment. This pattern detection plays out in all kinds of valuable ways. With visibility into open purchase orders, for instance, AI can spot when a supplier with multiple orders is late with one of them, assess the implications for the other orders, and call that to your attention so you can communicate with the supplier as needed. You may be able to resolve the situation easily with a two-minute email, where previously it might not have come to your attention until it was too late. It's especially helpful to have AI monitoring things like potential shipping disruptions. Whether it's a ship blocking the Suez Canal or ports closing due to the outbreak of war, it can make a huge difference to have a system that keeps track of shipping details and alerts you to possible delays an extra day—or even an extra week—in advance. How AI Boosts Workplace Productivity Another of AI’s real superpowers is its ability to help team members spend less time on tedious drudge work and more time on higher-level tasks. AI is tremendously effective at bypassing writer's block, for example. It can expedite critical tasks like summarizing business meetings, generating sales or purchase agreements, and writing business correspondence along with other business documents. Consider the new Microsoft Copilot, which is integrated with Dynamics 365. It combines the power of language models with your business data—including all your Microsoft 365 apps, documents, and conversations. It can help you: • Write documents in Word by generating text and suggesting edits • Analyze and visualize data quickly in Excel • Bring ideas to life impactfully in PowerPoint • Create efficient communications in Outlook … and much more. How AI Helps Elevate Customer Service AI can take customer service to a higher level by helping customers get the information and help they need in a timelier manner. It can also ensure that customers get their deliveries faster by solving or preventing supply chain and logistics issues. Automatic certain customer service tasks with AI means less waiting and happier customers. What Key Trends Are Driving the Adoption of AI in ERP systems? One of the most potent factors fueling interest in AI right now is the success of tools like OpenAI's ChatGPT, DALL-E, Midjourney, and Adobe Firefly. These tools have democratized AI by making it widely accessible in an easy-to-use format. In just the last couple years, the average person’s eyes have really been opened to AI’s possibilities. But contrary to what most people think, AI didn't just burst on the scene overnight— it’s been under the hood of many business software programs for years, slowly developing its capabilities and enabling more sophisticated tools. Microsoft in particular has been at the forefront of this. Remember Clippy in MS Office? That was an early example of an AI-powered assistant. Cortana was another step along the path. ERPs have been drawing on the power of AI for years now to analyze patterns and trends and make better forecasts and predictions. Microsoft's Dynamics 365 has been a leader in this effort as well. These days, Microsoft's Power Apps are a great example of how Microsoft helps companies harness the power of AI to boost and extend their abilities. With Power Automate, for example, you can easily make use of robotic process automation (RPA) and digital process automation (DPA) to automate recurring tasks and create automated workflows using low-code drag and drop tools. With Power Automate, you can even explain a problem in English and have it create a solution for you. So instead of needing to know how to write a SQL query, you can just say something like, “Hey, I want a list of all customers that spent at least $100,000 worth of product from us in the past, including something from this particular product line, but haven't bought from us in the last six months" — and Power Automate will know how to build that query and then either display it in a Power BI view, use it to feed a mass mailing, or do other useful things with it. Which makes it possible to get what you need out of systems without having to understand all the bits and bytes involved. Likewise, the power of predictive analytics, and the machine learning and forecasting tools that are built into ERPs like D365, mean you don't need to be a data scientist to analyze and visualize data in new and powerful ways — helping you see the road ahead so that you can run your business in a proactive (rather than reactive) way. Setting Guardrails: Navigating Potential Risks With power comes responsibility, of course, and a need to be clear-eyed about the possible downsides and pitfalls of leveraging AI within an ERP system. Navigating these issues successfully comes down to making sure you have the right guardrails in place and that they aren't circumvented. One of the most critical issues is to make sure that your data is tagged correctly by setting up good IT governance. What data should only be used within the walls of the company? What should be limited to people with specific levels of access? For example, consider a publicly traded company. If their financial results are inadvertently released before their 10-K is published, the SEC could punish them for it. AI could accidentally leak that kind of data if the right guardrails aren't in place to prevent it. Making sure data is correctly tagged can be a complicated process, and a lot of companies, especially smaller ones, may not have the necessary skills in house. That's an area where a partner like Columbus can step in and help. Copyright and intellectual property is another area where strong guardrails need to be set up. The Writer's Guild strike recently drew attention to this issue. For businesses, the question is: How do you make sure that your data and intellectual property aren't appropriated and leveraged without your permission? This is another reason why data needs to be carefully tagged and protected before it's released. There's a major change management component to this issue as well. It's vital to make sure that employees are aware of the risks and understand the proper procedures to safeguard data, as well as which tools are appropriate to use and which aren't. Policies also need to be created to make sure that employees don't circumvent the guardrails, intentionally or unintentionally. Making sure team members are trained in a consistent and ongoing way is crucial. How Can Enterprise Businesses Prepare for a Future Shaped by AI and ERP? With all of the above in mind, you can’t let the risks of new technology dissuade you from moving forward. Your competitors will be taking advantage of these tools, and you can't afford to be left behind. The key is to implement these tools in a disciplined and measured way, staying cognizant of the rewards and possibilities, as well as the potential pitfalls. This is another area where having an experienced partner like Columbus by your side can help you steer the ship successfully. Want to learn more about how Columbus can help your organization harness the full capabilities of AI? Get in touch with us today.
Right now, companies in the food and beverage industry have a lot on their plate. A key question how to meet all demands and at the same time reach all your business goals? Unifying your technology platform, business strategy and operations is necessary to stay ahead of your competitors. Companies have to keep up with increasing consumer demand for products that are healthy, ethical and environmentally friendly while at the same time meeting regulatory standards and minimizing food waste. And, of course, they still have to do the usual work of keeping margins high, preparing for emergencies, ensuring product quality, staying innovative and minimizing risk at every stage of production.
Like other industries, food & and beverage companies must initiate strategy planning and change management at the very start of bringing their business systems to the cloud. That’s the best way to avoid additional costs, effort, and business interruption. And the trick is to define value with a people mindset.
right-arrow share search phone phone-filled menu filter envelope envelope-filled close checkmark caret-down arrow-up arrow-right arrow-left arrow-down