How To Choose The Right ERP Deployment Destination

Should you run your ERP system on-premise or in the cloud? Which approach is best for your business? If you’re tasked with formulating the IT strategy for your company, the advice on offer can seem conflicting and less than helpful.

Well, sorry to muddy the waters a bit more, but the truth is, it’s not a straightforward choice between cloud or on-premise deployment. There are numerous models, combinations, and hybrid solutions to consider. However, rest assured that your organization can find the right fit.

Over the coming weeks, i will be looking at the pros and cons of the available deployment approaches. Let’s start by looking at the three categories of deployment destination.

Public cloud

A public cloud service is potentially the most economical, because the service providers host many organizations on the same stack:

• Physical infrastructure (including utilities, security, and disaster recovery)
• Operating systems (OS)
• Database systems (DBMS)
• Application systems (the ERP application itself)

Although your data is kept separate, you share everything else with other customers.

Because your software vendor manages the infrastructure and application for you, you can get up and running quickly and scale up or down when needs change. With regular updates managed by the software provider, you can take advantage of the latest features and innovations without getting bogged down with maintenance. And with subscription-based licensing and no need to purchase hardware, this option requires minimal up-front investment and predictable costs that can usually be accounted for as an operating expense rather than a fixed asset.

Standardized ERP packages enable you to implement best-practice, streamlined processes across every business function, including finance, HR, customer relationship management, and supply chain logistics. As a result of all this, public cloud is often the best choice for startups, smaller companies, and subsidiaries.

The same standardization that drives down costs, however, also leads to less flexibility. Public cloud ERP will typically not allow modifications or support all industry-specific workflows or the varying processes of individual business units. Some organizations might not even be able to run ERP according to a standardized approach.

Infrastructure as a service (IaaS)

Another option is to run ERP on an infrastructure provider such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform. They provide the physical infrastructure and leave the OS, DBMS, and ERP to you. In other words, you share the physical infrastructure running your applications, but your organization is the sole user of the database and ERP software. Essentially, you go public in one part and private in the other.

In this case, your organization is responsible for software setup, maintenance, and updates. Why would you want to take on this work when there are vendors that will manage it for you? Because you have more control. For example, updates typically happen every quarter with public cloud ERP. This might seem like a good thing at first, but perhaps your organization cannot absorb such rapid change with ERP. Also, you might want to run industry solutions not available in the public cloud, or customize processes beyond what public cloud can support. Instead, you can manage the updates and customize processes according to specific business needs.

While it won’t be as economical as the public cloud, running ERP on IaaS allows you to commoditize infrastructure, yet maintain almost as much control as an on-premise deployment.

On-premise

If you want complete control, an on-premise deployment is for you: You’re in charge of managing your entire ERP environment from the physical layer on up. You can adapt the software as required to respond to the business, and customize it to fit processes intrinsic to your industry and business units.

With this more traditional approach, of course, the responsibility to deploy and maintain the software and IT infrastructure is up to you, with or without the help of a third-party systems integrator. And it is more difficult to scale the system up or down.

There’s another variation on this theme to keep in mind: using a hosted data center offered by a company like IBM or HP. With this, you outsource the physical layer to get capabilities beyond what your own IT team can provide, especially with disaster recovery. Many companies also offer various application management packages as well, to perform maintenance and upgrades with more efficiency than you could do on your own.

Keeping your options open

While it might indeed seem complicated, once you weigh the options and consult with your stakeholders, you can map the strategy that’s right for your organization. A way to simplify all this for ERP is to consider your choices over five major dimensions:

	Public Cloud	Infrastructure as a Service (IaaS)	On-Premise/Hosted
Economics	Best	Better	Most costly
Business processes	Core processes, standardized	All processes	All processes
Customization	Within boundaries only	Open for ERP, within boundaries for infrastructure	Completely open
Maintenance	Done by vendor	Done by vendor and customer	Done by customer
Innovation pace	Quarterly updates, done by vendor	Annual updates, done by customer	Annual updates, done by customer

What’s right for one part of the business may not work for another. Many companies create a multi-tier environment, combining two or more deployment methods in a hybrid approach. For example, an organization might run subsidiaries on public cloud, but on-premise for headquarters.

What’s crucial is that the solutions work together. But beware: Many don’t.

Look for ERP that offers consistency in the code line, data model, and user experience, whether you choose cloud or on-premise. Your employees, whether based in an overseas subsidiary or the head office, should have the same user experience and be able to share information, run reports in the same format, and follow the same steps to complete tasks. This way, you can eliminate organizational silos and establish an integrated digital foundation for the future.

Here Are The 5 Microsoft Skills Data Analysts Need To Know

Microsoft programs are so commonplace in most business environments that sometimes being incredibly proficient in their use can be overlooked. Despite spending more time than you’d like to think about using Excel and Powerpoint, there are a ton of tips and tricks you’re likely not using yet. If you know how to dig deep into advanced functionalities with these programs, you'll vastly improve the way you do your work.

If you work with data regularly, you'll find the Microsoft Data Analysis Bundle incredibly helpful to your everyday workflow. And even if you don't crunch numbers for a living, being a data-driven employee and candidate only increases your value and employability. This shows you how to use Microsoft Power BI, Advanced Excel, Advanced VBA and Advanced Microsoft Access with total proficiency.

More specifically, these are a few of the skills to learn:

How to make your data interactive: Spreadsheets can do more than help you organize information. One of the best use cases of Advanced Excel is automating the development of advanced graphs, creating a visual that's powerful enough to be actionable from a business standpoint.

How to develop compelling data visuals: Data can tell a story and Microsoft Power BI gives you ways to present your data in compelling formats, performing complex data modeling relationships and generating dashboards that you can share with colleagues and clients.

How to automate complex tasks: We all have to do mundane, tedious tasks sometimes. With Advanced VBA, you can write and implement Excel events, which automates these tasks. It's also CPDUK-accredited, so it looks good on your resume (especially when you say you're a lifetime learner).

How to hone advanced techniques: Whether you have a basic knowledge of Microsoft programs or consider yourself a power user, there are ways to streamline your workflow and be more efficient with your time. Using Microsoft Access, you'll learn how to create and maintain macros and even discover advanced options for the use of forms.

How to solve complex problems: Whether you're a data analyst or just want to find ways to use data to do your job more efficiently, this bundle helps you find ways to use Excel to figure out answers to complex business problems, whatever they might be.

Digital Transformation will kill ERP

It is a strong statement but at this time nothing is more certain than change. When giant corporations are created from a basement in San Francisco or a student hall in Harvard, it is not hard to question the future of a software. If Digital Transformation can “disintegrate” enterprises why could not destroy a concept? 

Forget about ERP and the way we run enterprises for years, despite technological changes, everything is kept in a book. The book of transactions called general ledger. Payable, receivables, cash flow, fixed assets and purchasing.

Why? In a simple sentence? Because we need to know if we can take money home! And does not matter if is a small-one-owner or a large shared public company. It is the same. But if there is not a centralised book? We need to know if we can take the money home still. But if there is no money? 

It is a technology for a new generation of transactional applications that establishes trust, accountability and transparency while streamlining business processes.

It is a design pattern made famous by bitcoin the reason I used in this text but its application go far beyond. With it, we can re-imagine the world’s most fundamental business interactions and open the door to invent new styles of digital interactions.

It has the potential to vastly reduce the cost and complexity of cross-enterprise business processes. The distributed ledger makes it easier to create cost-efficient business networks where virtually anything of value can be tracked and traded—without requiring a central point of control.” 

Edge Computing vs. Cloud Computing: What’s the Difference?

You are likely hearing a new term now, edge computing. Technologists (and the press, let’s be honest) we to throw a word around before it is well-defined, and in that vacuum come a variety of guessed definitions, of varying accuracy.

The term cloud computing is now as firmly lodged in our technical lexicon as email and Internet, and the concept has taken firm hold in business as well. According to my observation “no cloud” policy will be as prevalent in business as a “no Internet” policy. Which is to say no one who wants to stay in business will be without one.

Edge computing is a term you are going to hear more of in the coming years because it precedes another term you will be hearing a lot, the Internet of Things (IoT). You see, the formally adopted definition of edge computing is a form of technology that is necessary to make the IoT work.

And again as a victim of the same, let me brand edge computing is a “mesh network of micro data centers that process or store critical data locally and push all received data to a central data center or cloud storage repository, in a footprint of less than 100 square feet.” I think I did not lose you.

Meet Edge Computing, processing data at the edge of the network  where it is taken in has a number of benefits, starting with reducing the latency and makes connected applications more responsive and robust. Some applications might need immediate response, such as a sensor for failing equipment or for detecting a break-in.

It also takes the computation load off the data center if data can be processed and reacted upon at the point of origin rather than making the round trip to and from the data center. So it reduces the burden on both the data center and the network.

You may hear edge computing referred to by other names than micro data centers. They include fog computing and cloudlets. Fog computing, or “fogging,” is a term used to described a decentralized computing infrastructure that extends the cloud to the edge of the network.

Cloudlets are mobility-enhanced micro data centers located at the edge of a network and serve the mobile or smart device portion of the network. They are designed to handle resource-intensive mobile apps and take the load off both the network and the central data center and keep computing close to the point of origin.