erwin Expert Blog

Software Deployment Strategy: How to Get It Right the First Time

Big or Small, Enterprise Architecture Is a Key Part of a Successful Software Deployment Strategy

A good software deployment strategy could be the difference between multiple and costly false starts and a smooth implementation. Considering the rate at which emerging technologies are introduced, it’s becoming more important than ever for organizations to have a software deployment strategy in place.

But what does it involve?

Not all software deployments and investments are equal. Large-scale, big-money investments like ERP require a lot of resources and planning. Small-scale investments, like website technology, on the other hand, can be purchased, expensed and deployed with few people knowing. And of course, there are thousands of software decisions made that fall somewhere in between.

Software purchase decisions and deployments represent an opportunity to leverage the experience and knowledge of your enterprise architecture (EA) team so you can make smarter, better investments. The key here is the EA team’s complete view of your IT landscape, which can help eliminate redundant purchases, identify issues of integration and more.


Software Deployment Strategy: How to Get It Right the First Time

Small Projects Can Create Big Headaches

Here’s an example of how a small-scale software investment can wreak havoc on an organization.

There is an intense focus today on customer experience (CX). Ensuring that your website visitors have access to the information they want, and they can find it quickly and easily, is just part of your overall CX. This makes your customer-facing technologies – the ones that power your website or mobile app – critical investments, even though they may not carry the price tag of an ERP system.

Even the smallest investments need to be vetted to make sure they work with existing infrastructure and processes. One small piece of website tech that ends up degrading your online CX can cost your organization millions in a very short amount of time. There’s simply too many choices just a click away today if something isn’t working properly. Differentiating technologies are also more likely to be customized than an application like ERP, which can often use a number of out-of-the-box processes.

These are areas where a software deployment strategy involving your EA team can help guide the software purchase and deployment process. But even in a world where software deployments increasingly mean logging into a cloud-based SaaS application, a software deployment strategy is still beneficial.

Don’t Be Resigned to Failure

Many SaaS vendors like to talk about how easy it is to get up and running with their products, especially when the infrastructure elements are in the cloud. But the reality is that the network that connects to the SaaS application, the security, the integrations with existing (often on-premise) applications, the SLAs and licensing, can all benefit from a review by the EA team.

Failed software deployments are, in fact, a significant problem for many organizations. Such failures can often be attributed to a lack of planning and foresight.

Considering the costs associated with some software – including its purchase, implementation and consultancy fees/training required to get started – a good software deployment strategy could save millions … literally.

A Gartner study found that nearly half (46 percent) of respondents said their most expensive, time-intensive software deployments were not delivering. When Gartner broke the software purchases in question into deal sizes of over and under $1 million, the firm got similar results.

When your EA team has the visibility to see across your IT landscape and understand the business processes built on your technology, it can help provide a better idea of the real costs behind your software deployments and you can better estimate your time to value. When it comes to software investments, you don’t be resigned to failure.

erwin EA gives organizations a full-featured, versatile platform for enterprise architecture in its broadest sense to ensure the success of projects – regardless of their size or scope.

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erwin Expert Blog

Managing Emerging Technology Disruption with Enterprise Architecture

Emerging technology has always played an important role in business transformation. In the race to collect and analyze data, provide superior customer experiences, and manage resources, new technologies always interest IT and business leaders.

KPMG’s The Changing Landscape of Disruptive Technologies found that today’s businesses are showing the most interest in emerging technology like the Internet of Things (IoT), artificial intelligence (AI) and robotics. Other emerging technologies that are making headlines include natural language processing (NLP) and blockchain.

In many cases, emerging technologies such as these are not fully embedded into business environments. Before they enter production, organizations need to test and pilot their projects to help answer some important questions:

  • How do these technologies disrupt?
  • How do they provide value?

Enterprise Architecture’s Role in Managing Emerging Technology

Pilot projects that take a small number of incremental steps, with small funding increases along the way, help provide answers to these questions. If the pilot proves successful, it’s then up to the enterprise architecture team to explore what it takes to integrate these technologies into the IT environment.

This is the point where new technologies go from “emerging technologies” to becoming another solution in the stack the organization relies on to create the business outcomes it’s seeking.

One of the easiest, quickest ways to try to pilot and put new technologies into production is to use cloud-based services. All of the major public cloud platform providers have AI and machine learning capabilities.

Integrating new technologies based in the cloud will change the way the enterprise architecture team models the IT environment, but that’s actually a good thing.

Modeling can help organizations understand the complex integrations that bring cloud services into the organization, and help them better understand the service level agreements (SLAs), security requirements and contracts with cloud partners.

When done right, enterprise architecture modeling also will help the organization better understand the value of emerging technology and even cloud migrations that increasingly accompany them. Once again, modeling helps answer important questions, such as:

  • Does the model demonstrate the benefits that the business expects from the cloud?
  • Do the benefits remain even if some legacy apps and infrastructure need to remain on premise?
  • What type of savings do you see if you can’t consolidate enough close an entire data center?
  • How does the risk change?

Many of the emerging technologies garnering attention today are on their way to becoming a standard part of the technology stack. But just as the web came before mobility, and mobility came before AI,  other technologies will soon follow in their footsteps.

To most efficiently evaluate these technologies and decide if they are right for the business, organizations need to provide visibility to both their enterprise architecture and business process teams so everyone understands how their environment and outcomes will change.

When the enterprise architecture and business process teams use a common platform and model the same data, their results will be more accurate and their collaboration seamless. This will cut significant time off the process of piloting, deploying and seeing results.

Outcomes like more profitable products and better customer experiences are the ultimate business goals. Getting there first is important, but only if everything runs smoothly on the customer side. The disruption of new technologies should take place behind the scenes, after all.

And that’s where investing in pilot programs and enterprise architecture modeling demonstrate value as you put emerging technology to work.

Emerging technology - Data-driven business transformation