In this issue
Thoughts from the CEO
In the previous newsletter I highlighted my top priority as realigning the business in accordance with changing markets to ensure that we remain relevant and that we use our experience and expertise to deliver the best possible outcomes for our customers. That challenge remains my top priority and the indications are that we are making progress. Over the last few months we have made a number of key appointments with these roles signalling that the company is changing and placing even more emphasis on delivering great customer outcomes.
During my first two months in the CEO role I have had the opportunity to meet with many customers and industry specialists in both New Zealand and Australia. It is apparent that technology driven change is occurring at an ever faster rate and that this is causing difficulties for many organisations as they struggle to architect, implement, and integrate new systems in a timely fashion with limited resources and funding.
In this environment automation is changing from being a nice-to-have to becoming an essential capability within IT operations for organisations of all sizes. Many of the factors driving the uptake of automation are presented in this edition of the newsletter.
AI, once thought of as only being appropriate for a small number of niche applications is rapidly becoming mainstream, an integral part of modern software and a driving factor for automation of complex environments.
Interestingly the burgeoning availability of new technology appears to have focused attention on the human, rather than technology, aspects of work and in particular the issue of company culture in the context of receptivity to change. It has long been acknowledged that most people are change adverse and so business leaders face a growing challenge – changing company cultures to fuel proactivity and innovation. This newsletter includes some interesting findings from a Gartner Survey on the topic.
Whilst the challenges ahead are significant, the power of many people to learn, to adapt, and to evolve in the current environment, continues to inspire. One such example of the successful evolution of an IT career that spans more than four decades is that of our very own Colin Grierson – refer the article below.
In conclusion I’d like to leave you with a thought provoking fact: The world’s first web page went live on the 6th August 1991. Consider what has occurred in the 27 years since then. Now imagine the possibilities in the next 27 years considering the rate of change is dramatically faster and escalating. It’s a great time to be in IT.
Why automation is becoming essential
By Ian Hight, Marketing Manager
Most IT managers face a growing problem. The amount of technology under their management has grown significantly and at the same time the sophistication of this technology has also grown. For example, network switches now have CPUs in place to deal with intelligent services used by modern networks and storage systems are no longer just storage systems they commonly have associated computers managing the storage workloads.
Products are increasingly invisible to the extent that they aren’t physical. Virtualisation and cloud computing have created a complex mix of logical and physical resources. We are seeing operating systems merged into cloud platforms and modern software applications are increasingly based on micro-services. These changes and many others mean that manual methods of management are no longer viable. Additionally CIOs are under increasing pressure to produce new services/new offerings and not spend all of their time and budget simply keeping existing systems operational.
IT automation is a large and complex topic that ranges from, single actions, to sequences, to complex AI based systems that automate decisions based on a wide variety of event triggers and programming logic.
In broad terms there are three different types of automation:
1. Workload automation is a data-driven automation event, typically used in continuous operations to achieve zero downtime.
2. Workflow automation involves intelligent routing of information to the right people or processes which results in better management of resources and increased productivity.
3. Process automation typically involves automation of multiples processes, with objectives such as improved QoS, increased capacity, and reduced human involvement i.e. Greater reliability and lower cost.
Forces fuelling automation
The changing technology landscape is a catalyst for IT operations automation. The most significant technology drivers are:
Modern applications have become dynamic – rapidly, seamlessly, and transparently adjusting resource consumption, with no human intervention. Cloud computing – be it public, private or hybrid is the answer to highly variable demand. Cloud computing also provides flexible development platforms, cloud-native applications and DevOps environments that support agile build and deployment.
Intelligence at the edge.
It is increasingly common that data intensive computing is undertaken at the edge of a cloud. (i.e. computer processing occurring at the user device rather than within a cloud) Companies are seeking to benefit from high performance, low cost, smart devices including sensors, cameras, controllers, and gateways, that are capable of managing quality, efficiency, safety, and environmental issues.
Merging of virtual and physical worlds
Increasingly physical devices are sold with digital services that maintain and optimise the devices based on both prescriptive and predictive analytics. Additionally, there are technologies such as AR (Augmented Reality) that combine virtual things with physical things.
With almost all employees now having mobile devices, organisations gain by providing access to on-demand data and advanced capabilities that empower, inform and engage them.
Cybersecurity is now embedded into a much wider range of devices and encompasses more protocols and greater intelligence enabling organisations to be more effective at managing compliance with new regulations.
Business Intelligence increasingly incorporates a combination of technology, processes, and people that enables faster, better-informed business decisions.
Reasons why automation now needs to be a priority
Widespread adoption of digital systems combined with the technology changes referenced above has created an environment where innovation can thrive, and it is. Organisations that are exploiting this environment through automation are gaining substantial advantage over their less tech savvy competitors. The benefits on offer through automation include:
Automated processes do things repeatedly and reliably. Tasks done at regular intervals like configuration and provisioning when automated can save time and cost.
Better decision making – through improved visibility
Automated processes increase visibility over IT systems. They provide an instantaneous view of what’s going wrong and where allowing you to make better decisions faster.
Automation enables a reduction in people costs not only through efficiency but also by eliminating errors normally associated with the ‘human element’ that can cause outages and rework. With IT process automation human mistakes can be significantly reduced or eliminated. A recent study found that US companies lose $700 billion a year, as a result of outages.
Innovation and agility
Automation acts as the catalyst for speedy implementation of innovative business models.
Improved staff satisfaction (by eliminating tedious work)
Instead of spending time on tasks that don’t demand their level of expertise, staff can focus their efforts on complex and strategic tasks, as well as developing their skills. Automation helps eliminate tasks that would normally occupy a lot of your human time.
Improved customer satisfaction
The benefits of automation flow on to the customer experience, by providing more reliable systems, at lower cost, faster. By automating customer support it is possible to reduce the need of getting in touch with a help desk person by providing self-service support options. Less tickets means less time and less cost.
Removing the human element of certain activities can be beneficial to operations. Humans are prone to making errors – especially when undertaking everyday, repetitive tasks.
The state of modern automation
If companies don’t take steps to automate the overall IT environment, they may well find themselves in a position of business-threatening chaos if/when things go wrong.
Modern automation must be able to build up a knowledge of what has happened across the total environment over time, and use this information to both deal with problems as they arise and to embrace any changes that are implemented on and around the environment.
What this requires is a change in approach as to how automation is undertaken. No longer is it a case of just dealing with specific cases: instead, a more full-function approach is needed that enables the automation of steps along the complete lifecycle of the application from concept through to end-of-life. This introduces the concept of orchestration. Rather than just focusing on the automation of specific tasks, orchestration tools try to take into account everything that is required to maintain a platform and its workloads without too much manual input. In the community open source world, DevOps tools such as Chef, Puppet, and Ansible have shown the way in how orchestration can help in automating many of the steps in this kind of process.
In the modern environment AI and particularly machine learning can help in identifying where a workload should be placed to gain the best overall environment based against a set of criteria. These criteria will be a mix of business and technical requirements including, cost, performance and governance, risk management and compliance. For example, take a workload that the business has decided is far more cost than performance sensitive. Machine learning could be used to build up knowledge of how much resources cost on the organisation’s own infrastructure.
Potentially automation could be used to interrogate public cloud environments and make the most of spot pricing for resources – for example, where a platform such as AWS provides compute resources at low prices during periods of low activity. Automation could then move the workload to the new environment, or redirect parts of the workload to make the most of the available resources as required.
Greater complexity will mean that AI/machine learning are the technologies required to ensure that an organisation gets the best results from automation. Modelling and managing these environments in real time will increasingly be something that humans just cannot do.
AI the new use case: Integration?
By Tony Wilson, Solution Sales Consultant
In the last year or so we have seen a great deal of increased publicity about AI. AI is an umbrella term that includes multiples technologies such as computer vision, machine learning, natural language processing, and others. It’s useful to think of AI as software that has the ability to see, hear, reason, and learn.
Recent publicity has typically been focused on use cases such as fraud detection, voice-enabled assistants, data security, image recognition, and driverless cars; but what about systems integration?
Integration is becoming increasingly important for organisations wanting to stay competitive by leveraging data and capabilities provided by third parties. Currently, integration is mostly the domain of technical specialists, undertaking their work cautiously and slowly. But therein lies a problem; businesses now want integrated capabilities on demand. AI has the potential to turn these wants into reality.
At the device level, automated integration is already here; the challenge is to provide complete systems that will automatically connect together. So how can you design for integration between ecosystems, platforms and things you cannot predict? The answer is using AI.
Let’s consider a practical example: A bank needs to transfer funds to a new trading partner. The banks AI will know which API's to connect to, and just the right information to exchange and complete the transaction, in a secure manner. No integration project, no technical team, and no big cost.
Evolution of Integration
Up until very recently, integration has mostly been something businesses have either outsourced or used in house technical teams for. The problem, however, is that the demand to connect to things digitally is outstripping the ability for human integrators to deliver; whether they are specialist in-house teams or outsourcers.
To meet this demand, integration delivery needs to be re-balanced in other ways. Enter the digital integrator. The digital integrator uses metadata analysis for improved data mapping and provides process analysis to suggest better integration, all packaged as part of a product. This approach reduces the need for integration specialists and opens up integration to a process of human-initiated needs fulfilled by AI enabled systems.
Digital integration using AI can, therefore, enable everyone to perform the integration. Humans can drive integration by using AI services to request digital outcomes. The AI engine listens to requests, then connects them together with the data and systems needed to support the requirement. AI-based integration potentially shortens the learning curve of both specialist and less / non-technical integrators to manage data and business flows, enabling almost anyone to perform integration tasks.
In many business ecosystems we now have the following actors:
- Integration specialists - The traditional integration people who generally focus on enterprise projects, bulk data processing and governance.
- Ad-hoc Integrator's - Tend to be the line of business roles and use fit for purpose tools for Mobile and API development.
- Citizen Integrator's - Are focused on personal projects, want instant gratification and integrate user data sync SaaS apps often on mobile devices.
- Digital Integrator's - Are AI and ML (Machine Learning) driven, support digital business projects and deliver automation using deep learning
This new and rapidly evolving environment is not without its challenges. The first challenge, obvious to the technically minded, is the need for common standards for AI/ML integration, as without a common standard for interconnection AI/ML will struggle. The challenge of standards, however, is a challenge in decline as increasingly the world is creating API's which in turn fuel the development of standards.
The next challenges relate to change management, security and data privacy. With the rapidly increasing use of productised API management systems, these areas are also becoming less of a challenge. Change management is enforced by API management platforms ensuring the integration actors work to guidelines and processes enforced by the API owner. Security and data privacy are also managed by policy ensuring that API consumers are not only authorised but also mandated to control access to data at a very granular level. So the technology provides the policymakers with the tools they need to enforce the policy.
When the business owner allocates an integration task, how do
s a digital integrator know which API to connect to? For a long time, API's have operated with levels of discover-able metadata. Metadata is like digital signposts that direct data consumers to APIs. With the right systems and processes in place, the API owner retains full control over what data, and services, are made available.
The most controversial challenge is; how much do we trust an AI? Most of what has been described so far are current technology, and some product vendors are actually starting to incorporate AI into their API management and integration products. So why is this whole area a candidate for wallowing in a trough of disillusionment? Basically, it’s us humans and our inherent distrust of AI. However, AI and ML, driven by citizen integrators, is now gaining social acceptability and momentum.
- AI and machine learning techniques are emerging as digital integrator technologies
- Growing criticality to leverage AI to support automation, insight and engagement
- Emerging technology innovations in AI are reducing time to integration and enabling citizen and ad-hoc integrators
- Organisations lack awareness of the emerging offerings of AI in integration platforms and the benefits of applying such new technologies
- Caution about exposure caused by high-value application and data flows used by AI
- Concerns over how to bring AI systems into the realm of reliable mission-critical system
CEO's see a need for changes to company culture
Once a year Garter undertakes a CEO and Senior Business Executive survey. This global survey comprises responses gathered from 32 countries and highlights CEO concerns, priorities and attitudes towards technology related issues.
The latest survey makes for some interesting reading. Three key findings were:
- 63 % of CEO’s said that they were likely to change their business models between 2018 and 2020
- 37 % of CEO’s see a need to make significant or deep changes to company culture by 2020
- CEOs perceive AI have the highest value potential of five big new technologies
Whilst on average the responses came from organisations larger than those typically found in Australasia, there is still some useful insights. Company culture is often the topic of discussion in the context of change projects particularly projects that incorporate the latest modern technologies, which of course are available anywhere in the world.
Outlined below are some of the key findings of the CEO survey relating to culture change. Hopefully these findings result in thought and action to assist with your own cultural change initiatives.
There has been a great deal of research about the importance of culture, particularly as it relates to the ability of organisations to undertake digital transformation, nicely summarised in the quote from Peter Drucker: “culture eats strategy for breakfast”.
So if culture change is very important, what kinds of culture change are CEO’s prioritising? The Gartner survey asked recipients to explain in simple terms the attributes of culture that they were trying to get away from, and the attributes that they wanted to get to, then summarised the findings as shown below.
The theme of the top items is toward a more entrepreneurial culture: proactive, innovative, empowered and customer centric. Better collaboration is also highly rated. The green items are technology focused – highlighting that being more tech-centric, data driven, and automation centric are all important cultural changes sought by CEO’s. Whilst this research is interesting the hard part is figuring out HOW you can bring about these cultural changes. We would welcome to hear the stories of our subscribers.
Celebrating 40 years of programming and still on top
Colin Grierson is one of NZ’s most experienced Application Programmers with 40 years of problem solving and building software solutions at SASIT.
Colin joined SASIT in 1979, when the company was a four year old computer bureau that provided customised software for each client.
For over four decades Colin has created software for a multitude of different businesses including applications related to manufacturing, distribution, sales, financials, import/export, loans and many more. Colin has also dived into the details of the IBMi operating system and developed utilities that make IBM POWER systems easier to use and connect with other applications including applications that manage backups, disaster recovery, and high availability.
Colin skills have also been recognised internationally. On several occasions he was invited to IBM in the US to assist develop documentation that has subsequently been distributed around the world by IBM.
There’s nothing Colin loves more than a challenge whether it be how to fix an application that stops working or how to make software more efficient and easier to use.
Colin’s four decade career has meant he has accumulated knowledge and skills of many programming environments, tools, and languages. Even today throughout Australasia Colin’s IBM i, DB2, RPG and Synon 2e skills are still in strong demand and is able to mentor and train some of our younger programmers who are more typically focused on .NET and more contemporary development languages.
Whilst modern application languages dominate the industry press, the reality for most organisations is that they have hybrid IT environments which bring the need for integration and modernisation. It appears Colin will remain busy for the foreseeable future.
- The world’s first web page went live on Aug 6 1991. It was dedicated to information about the World Wide Web Project, and was created by Sir Tim Berners-Lee. It ran on a NeXT computer at the European Organisation for Nuclear Research, CERN. Today there are more than 1.5 billion registered websites, and 150,000 web applications.
- Using your phone while it is on charge can damage the battery; this is why the leads for the chargers are so short.
- In general, people tend to read as much as 10% slower from a screen than from paper.
- There are computers designed for Amish people, with selling points like “No internet, no video, no music”.
- Spam mail got its name from the canned meat after a Monty Python skit that made fun of Spam as tasting “horrible and being ubiquitous and inescapable.”
- Bluetooth is named after the Danish 10th century King Harald "Bluetooth" who ate so many blueberries that his teeth stained blue. The wireless protocol is named after him because of his ability to unite warring Scandinavian factions, just as Bluetooth unites wireless devices.