Top 5 IT Nightmares
I recently happened upon a post about the ‘Top 5 IT Nightmares’ supposedly facing CIOs, System Administrators, and end-users. Now, I can only legitimately lay claim to being truly experienced as an end-user, but it struck me that each of the listed ‘nightmares’ belonged to a different decade, and unlikely to resonate with anyone today. It did make wonder, however, is what a more current list would look like? A partly selfish thought because it is the professional responsibility of my team and I to understand not only the biggest problems facing our customers and partners today, but also the ways in which we can actually help.
So what follows below is a high-level and certainly non-exhaustive view of those IT related challenges being faced by businesses today.
- Siloed skills, siloed budgets, siloed value.
Abraham Maslow highlighted ‘deficiency needs’ at the base of a hierarchical list used to describe the pattern that human motivations move through. It is at this deficiency needs level that many of the challenges that businesses face can be traced to – not only in IT. Financial security, health, safety nets, belonging and acceptance, self-esteem etc – I have personally seen all of these things affect behaviour in the workplace on many occasions, and are often part of the reason for suboptimal decisions being made. This includes leaders and team members sharing out funds and then planning and executing against strategy set out by CIOs – bound by structure and implied demarcations.
Twenty years later Melvin Conway put forward a sociological observation specific to software systems that has been called-out many times by members of my team. The basis of this is that the interface structure of a software system will reflect the social structure of the organisation that produced it. The output of many IT departments can be mapped to both Maslow’s and Conway’s seemingly obvious observations. Siloed focus + skills and siloed budgets have led to siloed value for wave after wave of IT investment. It’s been very challenging to match capabilities up so that the sum of parts isn’t greater than the system as a whole at any specific point in time. The 80/20 spending habit gets replicated in a few zones of influence; it’s a compounded issue. This problem could be amplified more and more over the coming years without a change of approach and that is a challenging path to mentally map out.
- Fire fighting vs. Fire lighting.
Technology is becoming more intertwined in business activities, prompting IT to increasingly become a direct driver of differentiation, growth, savings, and profitability. Many leaders in their respective markets now realise that digital innovation is a key to continued success. Agile competitors are already using innovative digital technology to optimise, rationalise, and establish differentiation. Over the past 20+ years there has been an ever enduring balancing act that teams and individuals within IT-related functions have had to persevere with to keep the lights on and repay technical debt – service level agreements, performance monitoring, user satisfaction scores, etc. Specific industries, services, and technologies have built-up to support this. However, ‘fire fighting’ remains deep-seated in Business-as-Usual.
So, taking into account that there is a widely held perception that in order to execute against a digital first strategy you have to take the shackles off in certain places – i.e. almost intentionally light some new fires instead of trying to put them out. How messy is delivering IT-reliant services going to get in this type of environment? If there are indeed to be two speeds of delivery in the future – Mode 1 and Mode 2 (the terminology here itself is somewhat misleading as IT is delivered at a multiple speeds depending on a myriad of factors), how do we avoid duplicating the overhead of existing complexity and frustrations that we have already struggled to manage after 20+ years of attempted fine-tuning? It’s certainly a dilemma.
- Sprawling data, sprawling devices.
Digital data is growing at an exponential rate, doubling every two years, and changing our way of life. We are entering the Zettabyte era as far as global IP traffic is concerned. That’s roughly 1000 Exabytes or 1 trillion Gigabytes per year before we even get to looking at the traffic on private networks! Wireless and mobile devices will exceed traffic from wired devices by next year and two-thirds of all IP traffic will originate with non-PC devices by 2019. Admittedly, video is a large contributor to these increases but there are many other significant contributors. Digital innovation is both creating and then leveraging huge swaths of data as backed by the highlighted trends that touch on only moving it around. Within many organisations there is then a need to store, analyse, and make valuable recommendations/decisions based on new and old data, and any associated metadata. It’s all stored and queried in many different ways and in many different places. We don’t analyse the vast majority of data that is available to us already and it just keeps appearing. More insight clearly presents a massive opportunity in areas such as customer analytics, operational analytics & business intelligence, fraud & compliance, etc. but it’s also a massive challenge for CIOs. How can data be treated as a strategic asset in a cost effective manner?
- Rationalisation and consolidation – normal and constant.
This is not often highlighted publicly as a stand-alone priority or concern, most likely because it’s seen as a subset of general cost control and modernisation. However time-and-time again I see the burden of evergreening, lifecycle management, consolidation, rationalisation, etc. getting in the way of IT-related functions moving forward and delivering best value. Efforts to consolidate and rationalise never quite seem to fit properly into Business-as-Usual processes – it’s often quite an unexciting when compared to other workstreams with obvious business value and payback. Evergreening and consolidation efforts are often stalled and deprioritised, then there is build up and sight of just how much technology has moved along in those 3, 4, 5, or 6 years is lost, along with the tangible and easy-to-measure ROI. By then it’s developed into a problem getting in the way of offering true business value – and become a major project. The cost of people and time related to these efforts is also hard to measure or there is no appetite to do so, especially in disorganised, stop-start environments. Every evergreen decision appears to then be strategic in nature and balancing the cost of saving a few £/$/€s CapEx vs. losing ‘unseen’ £/$/€s micro-analysing CapEx spend is not an obvious consideration. Not getting this area right continues to have knock-on consequences in many other areas and that’s why it makes this list.
- Cyber risk, cloud risk, revenue risk.
Consider how rapidly cloud-leveraging service delivery models have evolved recently. Just a few years ago it was confined to some select non-essential SaaS platforms and maybe IaaS or PaaS for Test and Development or seasonal bursts. It was mostly a cost saving, speed, or efficiency effort. Now we’re seeing organisations move major databases to PaaS cloud offerings and portions of finance over to ERP clouds; certainly not just non-essential systems and it’s not bring driven by a simple cost saving agenda. In the background, Shadow IT (business users going around IT to set up new services on the web) is much more prevalent than most either realise or want to admit. It’s both a security risk and a massive risk to incoming revenue and service relevance. Fighting the swarm of niche/market-focused players and cloud offerings taking away revenue and budget is a daily business if that’s your approach. Another approach may be to try to execute against a true hybrid cloud/service brokerage strategy. That means wholesale changes across people, processes, tooling, etc. Not easy. Keeping it all open to change and having sensible exit plans from providers can get demoted to a ‘nice to have’, because it’s so difficult to achieve without creating arbitrary lowest-common denominators across providers, which in turn eradicates many of the perceived service USPs.
At the centre of this is data. It’s a strategic asset, it’s everywhere, yet we don’t know where all of it is at all times. Many organisations can’t in fact always answer the questions: ‘Are we moving sensitive data? – Personally Identifiable Information (PII)?’, ‘How is this data being used, ‘Who is using it’?, Who should be using it? Until that’s possible there is a risk associated with no-limits cloud adoption – if the decision is in your hands in the first place that is. And of course, alongside digitisation and data growth the cyber threat runs in parallel. In the past it was mainly individual depts that could leave data vulnerable to breach, but now, without stringent controls, it could be much more at risk. Controlling data (and workloads) is difficult, getting visibility into it and securing it is another matter entirely. Security today is often modelled around ‘tick-box’ compliance regulation checks that often do not lead to real-world security, partly because of the way people approach them. Corporate IT can’t address this area on its own – the whole business has to accept responsibility for data and its usage.
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