Boring Boring ITSM & Covid 19

Last year I wrote a number of blog posts about ITSM underselling it’s importance to business. Blogs about how Service Management generally should be branding itself as a major digital enabler but was failing to take that message to the people that count. IT Service Management does not equal Service Desk, but who knew….? 

 The challenges posed to the business community, and the economy in general, by Covid 19 have shown in stark clarity that the organisations who have managed to transform to a digital operating model are better placed to survive. Digital has enabled home working to happen relatively seamlessly, digital has protected revenue streams, digital has ensured that supply chain issues are managed, digital has kept people in work and allowed them to continue to spend their money. Digital has kept the wheels of commerce turning. More importantly digital has kept primary care in hospitals working. 

 And what has underpinned the success of the digital enterprise? Effective service management! Service Management allows easily disrupted mesh of technologies, people and processes to work in relative harmony in an understated (but not undervalued) way.  

 It feels like we have been talking about digital transformation for years, indeed we have, but how many companies feel that they have sufficiently transformed in the midst of CovidNot many, but the roadmap has perhaps become a little clearer. 


Service Management, AI and Automation, Cloud – and Digital Transformation 

  1. Improve Service Management Agility 

Service Management, and ITIL generally, has allowed people to apply a best practice framework to process and underlying technology. The problem that this has created is a lack of agility. That in itself is no issue if the business it’s supporting is not agile, but it is unfortunately the antithesis of the digital enterprise.  

 Digital organisations thrive on the benefits of agility. They are quick to innovate, quick to bring products to market, quick to fail and quick to succeed. Service management needs to support this business agility whilst providing guide rails to reduce the risk of failures.  

 To do that we need to work with the business to provide IT services delivered via the channel of choice, in a requestable and repeatable fashion that leverages knowledge and asset data. Services need to be underpinned by automation to allow human interaction to be retained for high value activity; high value and low value activity need to be defined by data insights and not by anecdote. 

 We also need to ensure that boundaries (artificial or otherwise) do not prevent an effective ecosystem. No digital service is standalone and ensuring that the integration between the internal and external ecosystem is seamless and secure is essential.  


Here are my five key tips:  

  1. Use transition as an opportunity to transform. For example if you migrate your ITSM toolset into the cloud, transform and optimise on the journey Know what you have. Asset management and configuration management are the fundamental building blocks
  2. Use Knowledge effectively. Federate your knowledge sources, make sure that your knowledge is accessible where it is needed and not where it is easy to provide 
  3. Use omni-channel. The very nature of a digital ecosystem is the access to the same data and services through multiple channels 
  4. Leverage your ecosystem. Connected services are critical, digital gives us the chance to bridge silos


2.Leverage AI to drive Automation 

 AI designed for Service Management can corelate and provide insights into data from many disparate systems that structured reporting does not. It also does this in a much more rapid fashion with less overhead. 

 Our data is useless, we want to start again’ is a phrase that is often expressed; however it should really be re-written to say ‘our structured data is does not provide us useful information in a way that is easy and cost effective to access’. This is the problem statement AI is designed to solve.  

 Once you have valuable insights into unstructured data (which amounts to 90+% of all your data) the key is to be able to drive efficiencies from it. The simplest approach is to look at the metrics and associated costs, and look at what can be automated. Automation can come in a number of forms (through fulfilment of service catalogue items, through case or ticket exchange, and through RPA) but the essence remains the same. Replace low value human activity with high volume, error free, 24/7 automations to allow people to do what is the most effective and important part of their jobs – adding value. 


Here are five things to think about: 

  1. Start with the data. Use what data you have, AI and data science will inform quickly and effectively where the low hanging fruit are 
  2. Define your use cases with automation in mind. If you start by knowing that the end goal will deliver the benefits of automation, you’re more likely to leverage the benefits 
  3. Start small, be fast, scale rapidly. Choose your partners and tooling to support this strategy 
  4. Make automation technology available to the business. It should not remain in the realm of IT, rather IT should be a facilitator 
  5. People retain their value. Automation can replace people, but it shouldn’t. It should be used to allow people to add value where it really counts

3.Use the cloud, effectively

The hottest topic in town but for most organisations they are still at the start of the journey. The challenge as we know is that the cloud is easy to consume, but hard to get right from a cost and capacity management perspective, and the key is in the question ‘why move’.  

There are many reasons for migrating to the cloud; cost reductions (rarely effective, the cloud doesn’t seem to be cheaper), transition of costs to an opex model, agility (this one seems to keep cropping up), scalability, and more recently environmental reasons are becoming prevalent. So the how is dictated to by the why, and ultimately the challenge of using the cloud in the most effective was is also set by the ‘why’. 

3.a. The How? 

It’s simple isn’t it? Just chose between the following five: 

1. Rehost (lift, shift, rightsize) 

2.Replatform or Repurchase 




These are critical decisions that need to be made all with the knowledge that whatever ends up in the cloud will almost definitely need to work alongside legacy applications running in a datacentre somewhere, at least for a period of time. Maybe not so simple after all. 

3.b. Managing Cost & Capacity (being effective) 

Capacity management in the cloud is really a cost management challenge. Unconstrained by physical assets in a data centre, with virtually limitless scalability, the cloud is the biggest toy store on the planet. However to manage costs, you must understand your use of resources, and so capacity should remain at the forefront of your mind.  

There are three key high-level elements to managing cost and capacity effectively in the cloud.  

  1. Forecasting. Are you able to forecast resource requirements and associated costs based on historic business data accurately? 
  2. Planning. Using the forecasts you have built, are you able to build plans to improve current services and schedule new requirements? 
  3. Performance management. Are you able to measure against plan, and make changes based on data to both current utilisation as well and forecast utilisation? 

In summary 

Covid 19 has been a perfect storm. It has brought terrible pain and suffering, created heroes and shown us the true value of people whom often have been overlooked or under-celebrated. It has also shown us that the business world must change to be resilient, and it has shown us a glimpse into what the future could look like. I’m proud to be part of an organisation that can support that transformation.   


Boring Boring ITSM – time for a rebrand? (link to: 

Boring Boring ITSM? And what do you do? (link to: 

More details on AI-powered optimisation for Service Management here (link to: 



By Sunil Duggal