Enterprise Software Explained

Understanding Enterprise Software Architecture (Anatomy)

The common building blocks of a modern enterprise cloud computing platform are:

• Infrastructure-as-a-Service (IaaS) – the hardware and operating systems software used to house software applications
• Platform-as-a-Service (PaaS) – the software platform used to design, deploy and operate applications
• Software-as-a-Service (SaaS) – the runtime applications used by stakeholders to capture, process and output data

Types of Software found in the Enterprise Architecture

While no organization can function without enterprise software these days, how they design their software platform varies enormously. There are normally four layers to the enterprise applications software stack:

Systems of Record

These are large and expensive software applications used to process mission-critical data to serve common back-office functions such as financial management, manufacturing, human resources, and customer relationship management. These systems deliver value to businesses by enforcing standards in how data is processed and by being extremely reliable to ‘keep the lights on.’ Investments in Systems of Record are in the tune of 60 to 75% of total enterprise software spend.

Business Model Orchestration also known as Situational Applications

The gap that exists between the processing of standard back-office functions and the total data processing needs of the enterprise to fulfill its business model and serve up its customer value represents 10 to 20% of the total enterprise applications platform

Onboard, Embedded and Sensor-based Applications

These are use cases for software embedded into hardware such as smart devices used to manage assets and read-back customer activities and behaviors. Today, these represent 3-8% of the total enterprise stack but, thanks to trends towards increased use of Internet of Things (sensor-networked) technologies, this category is dramatically on the rise.

Personal Data Processing also known as desktop applications.

These are applications created by individuals and small teams to capture, cleanse, process, analyze and share information. This is where the demand for ‘citizen developer’ applications software largely comes from. Whilst it represents just 7-15% of total enterprise applications in terms of spending, it represents an important genre as these applications very much drive user and stakeholder experiences. Expectations on the quality of applications in this genre are extremely high because of the consumerization of IT; the realization of users that applications can be ‘that good’ as the result of using manual coding.

Check out our easy read guides.  Each is crammed with facts and insights on the hottest topics in enterprise IT.

Guide to Digital Transformation

Guide to Hyper Automation

Guide to Digital Ideation

Guide to Customer Data Platforms

Guide to No-Code Platforms

Enterprise Software Architectures and Digital Transformation

Many businesses today are considering the potential of advanced technologies – such as artificial intelligence, the Internet of Things, big data, cloud computing, 3D printing, drones, blockchain, and virtual reality – to transform how. they create value for their customers.

Low Code, No Code and Codeless

When formalizing their digital transformation framework, many leading chief information officers are recognizing that traditional IT methods and tools are too slow, inflexible and costly to use. For this reason, they are turning to agile software development tools and platforms (either code lite, low code, or no code) to author prototypes rapidly, fail fast and bring new app solutions to market faster.

Encanvas offers the easiest to use and most complete toolkit for live wireframing and rapid applications development. It equips DevOps teams with the digital transformation tools they need to outperform competitive rivals.

Enterprise Software and Data Driven Businesses

With a general recognition that business success is increasingly derived from the ability of an enterprise to master and leverage its data value, senior management teams are increasingly exploring ways to make sense of their operational performance through data. The ability to re-use data – to harvest, cleanse, rationalize, and analyze it – has become a mission-critical need.

Short-comings in Enterprise Software Architectures

Not all, but many present-day enterprise software architectures have some key issue areas. They include:

Suffering from legacy
Some businesses have been hoarding applications for years, ignoring many of them that are ‘good enough.’ With the pace of change in markets increasing every year, companies are constantly revising their business models. Legacy systems costs represent a major distraction, drain on resources and an anchor on innovation.

Too many applications
Access to Software-as-a-Service applications and the slow pace of internal software development has led many organizations to democratize their IT spend to departmental heads. A consequence of this trend has been the proliferation of SaaS tools.

The statistics around SaaS are unnerving. According to a recent report by Blissfully, a New-York startup that operates a platform to track SaaS adoption, the average company with 200 to 500 employees uses about 123 Software-as-a-Service (SaaS) applications these days. For mid-sized companies, there are an average of 32 different billing owners for the SaaS subscriptions. On average, an employee uses eight SaaS applications!

A continued ignorance towards the existence of shadow systems and the need for situational applications

Organizations turn a blind eye to self-authored desktop applications created using simple apps like spreadsheets because they don’t have the bandwidth to care. These applications are effectively being managed not by IT but by business professionals with other jobs to do (like running departments). Worse still, these unregulated apps are known to be unreliable in managing data quality, they scale badly. But that’s not the end of the story. These apps process and save data (so-called shadow data) that’s invisible to IT, yet it can contain private data, confidential company financial data, legal contracts, and competitive information that might place an organization at risk.

The gap that exists between Systems of Record and complete Digital Ecosystems to support Business Models

In most organizations, a gap exists between inflexible Systems of Record – used to enforce good practice in common core back-office processes such as financial management, human resources, and customer relationship management – and the demand for applications from departments, users, teams, customers, suppliers, and other stakeholders to support the fulfillment of a business model orchestration.

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