Tag Archives: continual improvement

AI, ITSM

Three AI truths with IT Service Management

August 5, 2024 Doug Tedder Leave a comment

There’s no question that introducing AI capabilities can have a dramatic impact on IT Service Management (ITSM). Done well, AI adoption will free up ITSM professionals to do the work for which humans are uniquely qualified, like critical thinking, contextual understanding, and creative problem-solving. Furthermore, AI will enable organizations to realize many of the theoretical benefits of ITSM. For example, the use of AI and machine learning can leverage comprehensive in-depth data, not just a small recent sampling, for cause analysis, problem detection, and impact determination of problems. Another example is the use of AI can increase the data of the IT environment and automate the remediation of incidents.

But AI is not a “magic wand” for ITSM.

Before introducing AI capabilities into ITSM, organizations must first consider these three AI truths.

Truth #1 – AI needs good data

For the use of AI to be effective, it needs data. Lots of data. But, if that data is inaccurate, lacks integrity, or is not trustworthy, then the use of AI will only produce inaccurate or poor results.

Data quality is an issue that many organizations will have to tackle before realizing the complete benefits of introducing AI to their ITSM implementations. These means that organizations will have to step up their technology and data governance posture. According to this recent Privacera article, a fundamental principle of data governance is having a high-quality, trusted data source. Having trusted data sources enables capabilities like ITSM to make accurate and reliable decisions regarding service management issues. But if the data sources used by ITSM tools contain data that is unregulated, the ability to automate responses is significantly hindered.

Truth #2 – AI doesn’t mean process design goes away

The need for effective ITSM processes and procedures doesn’t go away with AI adoption. Machine learning can be used to detect data patterns to understand what was done to resolve an issue. But what machine learning doesn’t do is determine if what is being done is the best approach. Machine learning doesn’t consider organizational goals and objectives with the adoption of ITSM. Machine learning cannot determine what processes are missing or need improvement to gain needed effectiveness and efficiency with ITSM.

Truth #3 – AI doesn’t replace knowledge

“Reducing cost”, often in the form of headcount reductions, is frequently used as the justification for AI investment, as the use of AI will enable ITSM activities to be automated. And it’s true – many of the ITSM activities currently performed by humans can and should be replaced with AI-enabled capabilities, such as the automated fulfilment of service requests, automated response to incidents, and problem data analysis. But one of the hidden costs of using AI to justify headcount reductions is the form of knowledge loss – the knowledge inside people’s heads walks out the door when their positions are eliminated. And this is the knowledge that is critical for training the chatbots, developing the LLMs needed, and to the continual improvement of AI and ITSM.

While AI can provide the “how” for “what” needs to be done, it cannot answer the “why” it needs to be done.

Good Governance facilitates AI-enabled ITSM

Without governance, AI can do some serious damage, not just with ITSM, but to the organization. As the role of IT organizations shifts from being data owners (often by default) to being data custodians, having well defined and enforced policies regarding data governance is critical. This means that the frequently found approach to governance consisting of an IT track and a corporate track is becoming untenable. As organizational processes and workflows become increasingly automated, enabled by AI capabilities, governance must become cross-functional[i] , with sales, marketing, HR, IT, and other organizational functions all involved. Organizations must consider and address data-related issues such as compliance with data privacy laws, ethical data use, data security, data management, and more.

An effective approach to governance enables organizations to define their digital strategy[ii] to maximize the business benefits of data assets and technology-focused initiatives. A digital strategy produces a blueprint for building the next version of the business, creating a bigger, broader picture of available options and down-line benefits.[iii] Creating a successful digital strategy requires an organization to carefully evaluate its systems and processes, including ITSM processes. And as ITSM processes are re-imagined for use across the enterprise in support of organizational value streams, effective governance becomes essential.

Getting ready for AI-enabled ITSM

What are some of the first steps organizations should take to get ready for AI-enabled ITSM?

Formalize continual improvement. One of the most important practices of an effective ITSM implementation is continual improvement. As organizations are continually evolving and changing, continual improvement ensures that ITSM practices evolve right alongside those business changes. And just like service management, AI adoption is not an “implement and forget”; in fact, AI will absolutely fail without formal continual improvement.
Answer the “why”. To say that there is so much hype around the use of AI within ITSM would be an understatement. Before jumping into AI, first develop and gain approval of the business case for using AI within ITSM. How will success be determined and measured? What opportunities for innovation will emerge by relieving people from performing those tedious and monotonous tasks associated with the current ITSM environment? What returns will the organization realize from the use of AI within ITSM? What new business or IT opportunities may be available because of the use of AI within ITSM? A good business case establishes good expectations for the organization regarding AI and ITSM.
Begin thinking about how AI can be leveraged by ITSM process designs. As discussed in this recent HBR.org article, AI will bring new capabilities to business (and ITSM) processes. With these new capabilities, organizations will need to rethink what tasks are needed, who will do those tasks, and the frequency that those tasks will be performed. The use of AI will enable organizations to rethink their ITSM processes from an end-to-end perspective, considering what tasks should be performed by people and what tasks should be performed by machines.

The concept of augmenting ITSM with AI is a “no-brainer”. However, success with AI in an ITSM environment requires a lot of up-front thought, good process design, solid business justification, and considering these three AI truths.

[i] https://2021.ai/ai-governance-impact-on-business-functions

[ii] https://www.techtarget.com/searchcio/definition/digital-strategy

[iii] Ibid.

AI, GenAI, ITSM

4 things IT can do to improve Business-IT Alignment – and enable AI success

May 20, 2024 Doug Tedder Leave a comment

A few years ago, I thought that we had finally moved beyond the conversation of “business-IT alignment”. I thought that business processes and technology had finally become integrated; if not integrated, then at least the boundary between business processes and technology was significantly blurred.

Well, I was wrong. Business-IT alignment – or the lack thereof – is still a thing.

We’re still struggling with business-IT alignment

This recent CIO.com article discusses seven hard truths of business-IT alignment. Here are a few of those hard truths:

“The business is not your customer.” I agree. For IT to act like non-IT colleagues are ‘customers’ simply drives a wedge between the IT department and the rest of the organization. This behavior also provides IT with an excuse for not understanding the business of the business.
“Like it or not, you are responsible for business outcomes.” That’s true. The real value from the use of technology is for the organization to realize business outcomes and value. But too often, IT sees and measures success in terms of projects getting done, or laptops being delivered, or contacts at the service desk being resolved.
“The business really does need to understand what you do.” That’s also true. While the IT department is responsible for the installation and maintenance of digital technology, IT must be more than just a technology caretaker. IT organizations must help the rest of the organization understand how the use of technology supports business strategy.
“You’re probably talking about the wrong things.” Couldn’t agree more. Many of the measures and reports that are being produced by IT are only because the tools being used by IT make it easy to produce these measures and reports. Do these measures have any meaning or relevancy to the rest of the organization?

Why is this a problem?

Business-IT alignment is not just a catch phrase or buzzword. The digital era is amplifying the importance of having strong business-IT alignment. But within many organizations, business-IT alignment is missing. How does the lack of alignment impact IT and the rest of the business?

First, IT is unable to respond to business demands at the speed of business. Consider the challenge that every modern business faces – serving the digital customer. The digital customer is demanding that businesses provide services at anytime from anywhere. In response, businesses want to leverage emerging technologies such as chatbots and GenAI to meet that demand. But because IT hasn’t been involved in those business strategy conversations, it is forced to play “catch up” to meet these demands – demands for which IT is usually unprepared. IT is not prepared because no one has been trained, much less involved in the selection of this technology – but then IT is expected to make it work as well as fit with existing systems and infrastructure. When IT is forced to play catch up, in-flight projects get delayed as IT resources are shifted to meet new demands.

But this behind-the-scenes work is rarely visible to the rest of the business. To the rest of the business, IT is a barrier to responding to the digital customer.

Secondly, the rest of the organization continues to look at IT as just a cost center. What those outside of IT may not realize is that IT must deliver warranty (security, resiliency, continuity, capacity, performance) as part of its services – regardless if that’s been communicated or specifically requested. Delivery of an expected level of warranty costs money – costs that may not be apparent to non-IT colleagues.

Why ITSM hasn’t helped

Wasn’t ITSM adoption supposed to address issues like the above and align the IT organization with the rest of the business? True, business-IT alignment is a goal of ITSM adoption…but for many organizations, it didn’t happen. Why?

ITSM was (and continues to be) an IT initiative with little to no involvement from non-IT colleagues. The initial ITSM project focused internally on IT processes and infrastructure management and excluded defining services and business-IT strategy. Making things worse, IT didn’t map how what it does supports business results or delivers business value. There was (and is) no link established between ITSM goals and objectives and organizational goals and objectives.
The ITSM initiative only focused on implementing a tool. This is a suboptimal approach for two reasons. A technology-only focus excludes how ITSM impacts people – both within and external to IT, as well as processes, suppliers, and partners. Secondly, the IT organization only took actions that facilitated use of the tool, not necessarily align with business needs.
ITSM is only focused on IT operations – or even worse, just the IT service desk. ITSM is viewed only as a way to deal with end-users of IT products and systems, never considering how technology could be used strategically to deliver business value or results. As a result, not only is ITSM not aligned with the business, IT is not internally aligned.

Successful AI adoption requires Business-IT Alignment

Businesses continue to experience the impact of the digital economy. In the digital economy, the “store” is always open, and customers expect that systems are “always on”. Customers can (and will) do business whenever and from wherever they want – using any internet-accessible device. Customers expect a differentiated, frictionless experience that provides value. Encountering system downtime or a poor experience is simply out of the question.

And organizations are turning to new capabilities enabled by emerging technologies, like chatbots, GenAI, intelligent automation, and more to meet this ever-increasing customer demand. In the digital economy, the technology managed and delivered by IT is the crucial connector between a business and its customers.

What does this mean for IT? IT can no longer play a back-office role within digital organizations. IT has a critical role as a business operates within the digital economy – and strong alignment between business and IT is required.

The successful use of chatbots, GenAI, automation, and other emerging technologies starts with having strong business-IT alignment. So how do organizations seize this opportunity, avoid the mistakes of the past (as with ITSM adoption), and realize true business-IT alignment?

First, ensure that any AI initiative has clearly defined objectives that are aligned with business strategy.

Second, successful adoption of AI requires strong involvement of business leaders[i]. Successful use of AI-enabled capabilities depends on the AI understanding the business of the business. It’s business leaders that have the knowledge that AI needs.

IT organizations must make the investment in building skills and competencies, in both AI technologies and in understanding the business of the business. Technology-only skills are no longer sufficient. IT must become that trusted advisor to help guide business leaders as the organization navigates the challenges of an AI-enhanced digital economy.

Lastly, good ITSM is an enabler for AI adoption. Good ITSM means aligning activities with business goals and objectives, defining services to ensure a shared understanding how technology delivers business value and outcomes, and providing business-relevant metrics and reporting. As a result, good ITSM enables fact-based decisions regarding AI adoption, such as where intelligent automation would improve a customer or employee experience.

Nothing will change – unless there is change!

Let’s be clear. Business-IT alignment challenges will not just go away, nor will they fix themselves. It’s up to IT to align with the rest of the organization, not the other way around. And it’s not just the CIO alone that can drive business-IT alignment – the entire IT organization must also drive it as well.

It’s time to break the pattern. Here are some suggestions for breaking through those alignment barriers– all of which can be initiated by IT.

Establish and nurture the guiding coalition. To demonstrate its commitment to overcoming the challenges of business-IT alignment, IT must form a team to drive change. This early step in Kotter’s 8-step model demonstrates IT’s commitment to driving improvement in business-IT alignment.
Map business value streams – plus. Value Stream Mapping is a great way to identify how value flows through an organization. But don’t stop there – identify and map how technology supports each step within each value stream. Review these value streams with all IT personnel to raise awareness of how IT enables business success. Then, take it one step further. Review value stream maps with non-IT stakeholders and decision-makers. Not only will this illustrate the role of IT in business success, but those stakeholders may also even be surprised to see how technology enables value flow through the business!
Look at what you’re reporting to whom. If IT is sending reports full of technology metrics to business colleagues, then IT is reporting the wrong things! Identify and define ways to measure and report on metrics that directly reflect the organization’s mission, vision, and goals. By measuring and reporting on metrics that are important to the business, IT demonstrates how its contributions lead to business success.
Get serious about continual improvement. IT organizations can positively influence non-IT colleagues by fixing those things that cause constant irritation when interacting with IT products, processes, and services. Establishing a regular and on-going continual improvement practice to remove these irritants – then publicizing those efforts – will begin to change the perception of IT.

Business-IT alignment has long been a critical success factor for the modern, digital-age organization. Success with AI adoption is raising the need for alignment to a new level. Taking these first steps will set you on the path of business-IT alignment – and AI success.

Does your IT organization continue to struggle with alignment to “The Business”? Let Tedder Consulting help you establish the strong foundation you need so that your organization will realize the business results required from its investments in and use of technology. Contact Tedder Consulting today for a no-obligation discussion about how we help!

[i] https://www.forbes.com/sites/forbestechcouncil/2023/10/06/why-business-leaders-should-understand-ai-alignment, Retrieved April 2024.

Leadership

Is the CIO the Continual Improvement Officer?

June 7, 2021 Doug Tedder Leave a comment

The CIO is often wearing many hats. They have to be tech whizzes and also strategic visionaries. And in my opinion, they now have to be the Continual Improvement Officer for their teams, their organizations, and in their careers.

Continual improvement is about improving the quality of products and services by learning from past successes and failures and making incremental changes over time. It helps IT align and realign its products, services, and activities to meet ever-changing business needs. Continual improvement can be the key to large-scale growth.

When done correctly, continual improvement can improve product and service quality, boost productivity and creativity, increase teamwork and create a competitive advantage.

It sounds simple, doesn’t it? We should learn from the mistakes – and the successes – we have. But, in a business environment, it’s never that simple. Why? Because many leaders don’t want to admit to mistakes. They don’t want to explore why things aren’t working as well as they should. They settle for “good enough”. They don’t want to examine what could be done better because they want to plunge ahead into that next project and hope that people forget about whatever mistakes were made or problems that were encountered.

For continual improvement to have success, it has to be embedded into the culture of an organization. It has to be accepted – and driven – from the top-down so that everyone is empowered to look at failed initiatives and missed KPIs as learning and improvement opportunities.

How can the CIO become the Continual Improvement Officer and build a culture that supports this?

Continual Improvement in IT

If a CIO wants to become the Continual Improvement Officer, she has to start with her own teams. One of the most important things a CIO can do then is allocate the time for continual improvement. IT is often (usually?) inundated with day-to-day work. They often are putting out fires or working to meet aggressive delivery deadlines and objectives. There is rarely-if ever- time for that “be back” work that inevitably comes up.

It’s up to the CIO to ensure continual improvement becomes a standard mode of operation and allocate adequate time to address continual improvement. How? It could be frequent projects or sprints with an objective to reduce technical debt. Perhaps it is establishing a cadence of regular meetings or time to discuss and implement continual improvement initiatives. Or it could be requiring that teams take the time to reflect on completed projects and initiatives and identify gaps, issues, and what could have been done differently.

Make these efforts inclusive by encouraging team members to bring their ideas to the table — and then identify opportunities to implement those ideas. Companies with a strong culture of continual improvement implement about 80% of their employees’ improvement ideas, according to KaiNexus. By implementing the improvement ideas from those that do the work establishes a mindset of continual improvement and encourages the team to identify and suggest further improvements. It’s a win-win for both the team and the organization.

Continual Improvement in the Rest of the Organization

IT is only one piece of the improvement puzzle though. To really build a culture of continual improvement, the CIO has to be the continual improvement champion within the rest of the organization and that requires communicating with and motivating other leaders.

CIOs can share their own continual improvement learnings and lessons. CIOs must be open about the setbacks and the growth from continual improvement activities, and when able, connect how continual improvement enhanced another department’s initiatives. Invite other executives to your continual improvement meetings to demonstrate how building a culture of continual improvement within IT is working. Offer to provide coaching and the expertise to help those leaders establish continual improvement efforts within their teams.

Continual Improvement as a CIO

I think the CIO needs to be the Continual Improvement Officer because it will not only improve their organization, but it is a critical skillset and approach that will benefit the CIO’s career.

Unfortunately, the CIO role has one of the highest turnover rates among the C-suite. According to TechTarget, the average CIO tenure hovers around 4 years. That means CIOs are frequently moving into new environments and navigating new work cultures. The best thing any CIO can do when they first step into a role is to bring an attitude of continual improvement. Not just for the new organization, but for their own individual actions.

It’s a powerful move to reflect on what could have been done differently in a past role as you move into a new role. This will help you embody the culture of continual improvement that you want your team to adapt as well. Be willing to address and share your own opportunities for improvement with your team as you begin implementing new initiatives.

What continual improvement successes have you had within your organization? What advice would you give to other leaders working toward a culture of continual improvement? Share your thoughts with me on LinkedIn!