Trickle-down impact planning

We introduced the concept of The Trickle-down Effect last year, an effect that sees the most minor changes trickling down through an OSS stack, with much bigger consequences than expected.

The trickle-down effect can be insidious, turning a nice open COTS solution into a beast that needs constant attention to cope with the most minor of operational changes. The more customisations made, the more gnarly the beast tends to be.”

Here’s an example I saw recently. An internal business unit wanted to introduce a new card type into the chassis set they managed. Speaking with the physical inventory team, it seemed the change was quite small and a budget was developed for the works… but the budget (dollars / time / risk) was about to blow out in a big way.

The new card wasn’t being picked up in their fault-management or performance management engines. It wasn’t picked up in key reports, nor was it being identified in the configuration management database or logical inventory. Every one of these systems needed interface changes. Not massive change obviously, but collectively the budget blew out by 10x and expedite changes pushed out the work previously planned by each of the interface development and testing teams.

These trickle-down impacts were known…. by some people…. but weren’t communicated to the business unit responsible for managing the new card type. There’s a possibility that they may not have even added the new card type if they realised the full OSS cost consequences.

Are these trickle-down impacts known and readily communicated within your OSS change processes?

One sentence to make most OSS experts cringe

Let me warn you. The following sentence is going to make many OSS experts cringe, maybe even feel slightly disgusted, but take the time to read the remainder of the post and ponder how it fits within your specific OSS context/s.

“Our OSS need to help people spend money!”

Notice the word is “help” and not “coerce?” This is not a post about turning our OSS into sales tools, well, not directly anyway.

May I ask you a question – Do you ever spend time thinking about how your OSS is helping your customer’s customer (which I’ll refer to as the end-customer) to spend their money? And I mean making it easier for them to buy the stuff they want to buy in return for some form of value / utility, not trick or coerce them into buying stuff they don’t want.

Let me step you through the layers of thinking here.

The first layer for most OSS experts is their direct customer, which is usually the service provider or enterprise that buys and operates the OSS. We might think they are buying an OSS, but we’re wrong. An organisation buys an OSS, not because it wants an Operational Support System, but because it wants Operational Support.

The second layer is a distinct mindset change for most OSS experts. Following on from the first layer, OSS has the potential to be far more than just operational support. Operational support conjures up the image of being a cost-centre, or something that is a necessary evil of doing business (ie in support of other revenue-raising activities). To remain relevant and justify OSS project budgets, we have to flip the cost-centre mentality and demonstrate a clear connection with revenue chains. The more obvious the connection, the better. Are you wondering how?

That’s where the third layer comes in. We have to think hard about the end-customer and empathise with their experiences. These experiences might be a consumer to a service provider’s (your direct customer) product offerings. It might even be a buying cycle that the service provider’s products facilitate. Either way, we need to simplify their ability to buy.

So let’s work back up through those layers again:
Layer 3 – If end-customers find it easier to buy stuff, then your customer wins more revenue (and brand value)
Layer 2 – If your customer sees that its OSS / BSS has unquestionably influenced revenue increase, then more is invested on OSS projects
Layer 1 – If your customer recognises that your OSS / BSS has undeniably influenced the increased OSS project budget, you too get entrusted with a greater budget to attempt to repeat the increased end-customer buy cycle… but only if you continue to come up with ideas that make it easier for people (end-customers) to spend their money.

At what layer does your thinking stop?

How smart contracts might reduce risk and enhance trust on OSS projects

Last Friday, we spoke about all wanting to develop trusted OSS supplier / customer relationships but rarely finding them and a contrarian factor for why trust is so hard to achieve in OSS – complexity.

Trust is the glue that allows OSS projects to happen. Not only that, it becomes a catch-22 with complexity. If OSS partners don’t trust each other, requirements, contracts, etc get more complex as a self-protection barrier. But with every increase in complexity, there becomes an increasing challenge to deliver and hence, risk of further reduction in trust.

On a smaller scale, you’ve seen it on all projects – if the project starts to falter, increased monitoring attention is placed on the project, which puts increased administrative load on the project team and reduces the time they have to deliver the intended outcomes. Sometimes the increased admin / report gains the attention of sponsors and access to additional resources, but usually it just detracts from the available delivery capability.

Vish Nandlall also associates trust and complexity in organisational models in his LinkedIn post below:

This is one of the reasons I’m excited about what smart contracts can do for the organisations and OSS projects of the future. Just as “Likes” and “Supplier Rankings” have facilitated online trust models, smart contracts success rankings have the ability to do the same for OSS suppliers, large and small. For example, rather than needing to engage “Big Vendor A” to build your entire, monolithic OSS stack, if an operator develops simpler, more modular work breakdowns (eg microservices), then they can engage “Freelancer B” and “Small Vendor C” to make valuable contributions on smaller risk increments. Being lower in complexity and risk means B and C have a greater chance of engendering trust, but their historical contract success ranking forces them to develop trust as a key metric.

We all want to develop trusted OSS partnerships, so why does so much scepticism exist?

Every OSS supplier wants to achieve “trusted” status with their customers. Each supplier wants to be the source trusted to provide the best vision of the future for each customer.

I’m an independent consultant, so I have been lucky enough to represent many organisations on both sides of that equation. And in that position, I’ve been able to get a first-hand view of the perception of trust between OSS vendors / integrators (suppliers) and operators (customers). Let’s just say that in general, we’re working in an industry with more scepticism than trust.

So if trust is so important and such a desired status, where is it breaking down?

Whilst I’d like to assume that most people in our industry go into OSS projects with the very best of intentions, there are definitely some suppliers that try to trick and entrap their customers whilst acting in an untrustworthy way. For the rest of this post, I’m going to assume the best – assume that we all have great intentions. We then look at why the trust relationships might be breaking down and some of the ways we can do better.

Jon Gordon provides a great list of 11 ways to build trust. Check out his link for a more detailed view, but the 11 factors are as follows:

  1. Say what you are going to do and then do what you say!
  2. Communicate, communicate, communicate
  3. Trust is built one day, one interaction at a time, and yet it can be lost in a moment because of one poor decision
  4. Value long term relationships more than short term success
  5. Sell without selling out. Focus more on your core principles and customer loyalty than short term commissions and profits.
  6. Trust generates commitment; commitment fosters teamwork; and teamwork delivers results.
  7. Be honest!
  8. Become a coach. Coach your customers. Coach your team at work
  9. Show people you care about them
  10. Always do the right thing. We trust those who live, walk and work with integrity.
  11. When you don’t do the right thing, admit it. Be transparent, authentic and willing to share your mistakes and faults

They all sound quite obvious don’t they? Do you also notice that many of the 11 (eg communication, transparency, admitting failure, doing what you say, etc) can be really easy to say but harder to do flawlessly under the pressure of complex OSS delivery projects (and ongoing operations)?

I know I certainly can’t claim a perfect track record on all of  these items. Numbers 1 and 2 can be particularly difficult when under extreme delivery pressure, especially when things just aren’t going to plan technically and you’re focussing attention on regaining control of the situation. In those situations, communication and transparency are what the customer needs to maintain confidence, but the customer relationship takes time that also needs to be allocated to overcoming the technical challenges. It becomes a balancing act.

So, how do we position ourselves to make it easier to keep to these 11 best intentions? Simple. By making a concerted effort to reduce complexity… actually not so simple as it sounds, but rewarding if you can achieve it. The less complex your delivery projects (or operational models), the more repeatable and reliable a supplier’s OSS delivery becomes. The more reliable, the less friction and a reduced chance of fracturing relationships. Subsequently, the more chance of building and retaining trust.

Hat-tip to Robert Curran of Aria Networks for spawning a discussion about trust.

Fast / Slow OSS processes

Yesterday’s post discussed using smart contracts and Network as a Service (NaaS) to give a network the properties that will allow it to self-heal.

It mentioned a couple of key challenges, one being that there will always be physical activities such as cable cuts fixes, faulty equipment replacement, physical equipment expansion / contraction / lifecycle-management.

In a TM Forum presentation last week, Sylvain Denis of Orange proposed the theory of fast and slow OSS processes. Fast – soft factories (software and logical resources) within the operations stack are inherently automatable (notwithstanding the complexities and cost-benefit dilemma of actually building automations). Slow – physical factories are slow processes as they usually rely on human tasks and/or have location constraints.

Orchestration relies on programmatic interfaces to both. Not all physical factories have programmatic interfaces in all OSS / BSS stacks yet. It will remain a key requirement for the forseeable future to be able to handle dual-speed processes / factories.

Potential OSS failures aren’t always technical

I recently attended an event where a brainstorming question was posed about how a particular next-gen OSS concept might fail. Interesting exercise!

There were a lot of super-clever technical people in the room. The brainstorming of ideas was a fascinating one. We dived deeply into the experiences of many of the technical people in the room and all the potential technical reasons for failure.

But I was left with an overwhelming feeling that:

    1. Most, if not all, of those technical hurdles could be overcome if given enough resources
    2. None of the more likely causes of failure were brought up, including:
      • People-related factors (or organisational change factors) such as resistance to change, a shortage of skills in a nascent area, stakeholder management, lack of “champion” support if momentum slows, inability to reach consensus on scope / design, etc
      • Financial viability factors such as inability to deliver on time/cost/scope, parallel operations and maintenance of legacy, lower additional benefit than predicted in the business case

That’s where I’ve noticed a greater proportion of OSS project failures anyway. Does this align with your experiences?

Compiling “The Zen of OSS” perhaps?

A recent presentation just reminded me of “The Zen of Python.” It’s a collection of 20 (19?) software principles, particularly as they relate to the Python programming language.

Since OSS is software-defined, (almost) all of the principles (not sure about the “Dutch” one) relate to OSS in a programming sense, but perhaps in a broader sense as well. I’d like to share two pairings:

Errors should never pass silently.
Unless explicitly silenced.

Unfortunately too many do pass silently, particularly across “best-of-breed” OSS stacks.


Now is better than never.
Although never is often better than right now.

An especially good hint if you’re working within an Agile model!

So that got me thinking (yes, scary, I know!). What would a Zen of OSS look like? I’d be delighted to accept your suggestions. Does one already exist (and no, I’m not referring to the vendor, Zenoss)?

In the meantime, I’ll have to prepare a list I think. However, you can be almost assured that the first principle on the Zen of OSS will be:

Just because you can, doesn’t mean you should.

Finding the most important problems to solve

The problem with OSS is that there are too many problems. We don’t have to look too hard to find a problem that needs solving.

An inter-related issue is that we’re (almost always) constrained by resources and aren’t able to solve every problem we find. I have a theory – As much as you are skilled at solving OSS problems, it’s actually your skill at deciding which problem to solve that’s more important.

With continuous release methodologies gaining favour, it’s easy to prioritise on the most urgent or easiest problems to solve. But what if we were to apply the Warren Buffett 20 punch-card approach to tackling OSS problems?

I could improve your ultimate financial welfare by giving you a ticket with only twenty slots in it so that you had twenty punches – representing all the investments that you got to make in a lifetime. And once you’d punched through the card, you couldn’t make any more investments at all. Under those rules, you’d really think carefully about what you did, and you’d be forced to load up on what you’d really thought about. So you’d do so much better.”
Warren Buffett

I’m going through this exact dilemma at the moment – am I so busy giving attention to the obvious problems that I’m not allowing enough time to discover the most important ones? I figure that anyone can see and get caught up in the noise of the obvious problems, but only a rare few can listen through it…

50 exercises to ignite your OSS innovation sessions

Every project starts with an idea… an idea that someone is excited enough to sponsor.

  1. But where are your ideas being generated from?
  2. How do they get cultivated and given time to grow?
  3. How do they get pitched? and How do they get heard?
  4. How are sponsors persuaded?
  5. How do they then get implemented?
  6. How do we amplify this cycle of innovation and implementation?

I’m fascinated by these questions in OSS for the reasons outlined in The OSS Call for Innovation.

If we look at the levels of innovation (to be honest, it’s probably more a continuum than bands / levels):

  1. Process Improvement
  2. Incremental Improvement (new integrations, feature enhancement, etc)
  3. Derivative Ideas (iPhone = internet + phone + music player)
  4. Quantum Innovation (Tablet computing, network virtualisation, cloud delivery models)
  5. Radical Innovations (transistors, cellular wireless networks, Claude Shannon’s Information Theory)

We have so many immensely clever people working in our industry and we’re collectively really good at the first two levels. Our typical mode of working – which could generally be considered fire-fighting (or dare I say it, Agile) – doesn’t provide the time and headspace to work on anything in the longer life-cycles of levels 3-5. These are the levels that can be more impactful, but it’s these levels where we need to carve out time specifically for innovation planning.

If you’re ever planning to conduct innovation fire-starter sessions, I really recommend reading Richard Brynteson’s, “50 Activities for Building Innovation.” As the title implies, it provides 50 (simple but powerful) exercises to help groups to generate ideas.

Please contact us if you’d like PAOSS to help facilitate your OSS idea firestarter or road-mapping sessions.

A summary of RPA uses in an OSS suite

This is the sixth and final post in a series about the four styles of RPA (Robotic Process Automation) in OSS.

Over the last few days, we’ve looked into the following styles of RPA used in OSS, their implementation approaches, pros / cons and the types of automation they’re best suited to:

  1. Automating repeatable tasks – using an algorithmic approach to completing regular, mundane tasks
  2. Streamlining processes / tasks – using an algorithmic approach to assist an operator during a process or as an alternate integration technique
  3. Predefined decision support – guiding operators through a complex decision process
  4. As part of a closed-loop system – that provides a learning, improving solution

RPA tools can significantly improve the usability of an OSS suite, especially for end-to-end processes that jump between different applications (in the many ways mentioned in the above links).

However, there can be a tendency to use the power of RPAs to “solve all problems” (see this article about automating bad processes). That can introduce a life-cycle of pain for operators and RPA admins alike. Like any OSS integration, we should look to keep the design as simple and streamlined as possible before embarking on implementation (subtraction projects).

The OSS / RPA parrot on the shoulder analogy

This is the fourth in a series about the four styles of RPA (Robotic Process Automation) in OSS.

The third style is Decision Support. I refer to this style as the parrot on the shoulder because the parrot (RPA) guides the operator through their daily activities. It isn’t true automation but it can provide one of the best cost-benefit ratios of the different RPA styles. It can be a great blend of human-computer decision making.

OSS processes tend to have complex decision trees and need different actions performed depending on the information being presented. An example might be a customer on-boarding, which includes credit and identity check sub-processes, followed by the customer service order entry.

The RPA can guide the operator to perform each of the steps along the process including the mandatory fields to populate for regulatory purposes. It can also recommend the correct pull-down options to select so that the operator traverses the correct branch of the decision tree of each sub-process.

This functionality can allow organisations to deliver less training than they would without decision support. It can be highly cost-effective in situations where:

  • There are many inexperienced operators, especially if there is high staff turnover such as in NOCs, contact centres, etc
  • It is essential to have high process / data quality
  • The solution isn’t intuitive and it is easy to miss steps, such as a process that requires an operator to swivel-chair between multiple applications
  • There are many branches on the decision tree, especially when some of the branches are rarely traversed, even by experienced operators

In these situations the cost of training can far outweigh the cost of building an OSS (RPA) parrot on each operator’s shoulder.

Using RPA as an alternate OSS integration

This is the third in a series about the four styles of RPA (Robotic Process Automation) in OSS.

The second of those styles is Streamlining processes / tasks by following an algorithmic approach to simplify processes for operators.

These can be particularly helpful during swivel-chair processes where multiple disparate systems are partially integrated but each needs the same data (ie reducing the amount of duplicated data entry between systems). As well as streamlining the process it also improves data consistency rates.

The most valuable aspect of this style of RPA is that it can minimise the amount of integration between systems, thus potentially reducing solution maintenance into the future. The RPA can even act as the integration technique where an API isn’t available or documentation isn’t available (think legacy systems here).

Using RPA to automate OSS activities

This is the second in a series about the four styles of RPA (Robotic Process Automation) in OSS.

The first of those styles is automating repeatable tasks by following an algorithmic approach to complete regular, mundane tasks.

Running an OSS has many high value, challenging tasks for operators to perform. Unfortunately, they also have many repetitive, simple (brain-dead?) tasks that need to be done too.

This might include collecting data from various sources and aggregating it into a single file or report for consumption by humans or machines. Other examples include admin clean-up tasks like accounts / tempfiles / processes / sessions and myriad simple process automations.

When we think of OSS automations, we often think of high value but complicated tasks like orchestrations, network self-healing, etc. They can be expensive and inflexible, not always delivering the perceived worth for the investment.

However, when thinking of RPA I think about the simplest stuff first. They are basic and consistent processes that are straightforward to define an algorithm for, making them the “low-hanging fruit” of OSS / RPA activities. They help to build momentum towards the bigger automation fish. Best of all, they free up your talented OSS operators to do more valuable activities.

Automating repeatable tasks is the most basic RPA style. We’ll step up the value chain with each additional style over the next few days.

The four styles of RPA used in OSS

You’re probably already aware of RPA (Robotic Process Automation) tools. You’ve possibly even used one (or more) to enhance your OSS experience. In some ways, they’re a really good addition to your OSS suite. In some ways, potentially not. That all comes down to the way you use them.

There are four main ways that I see them being used (but happy for you to point out others):

  1. Automating repeatable tasks – following an algorithmic approach to getting regular, mundane tasks done (eg weekly report generation)
  2. Streamlining processes / tasks – again following an algorithmic approach to assist an operator during a process (eg reducing the amount of data entry when there is duplication between systems)
  3. Predefined decision support – to guide operators through a process that involves making different decisions based on the information being presented (eg in a highly regulated or complex process, with many options, RPA rules can ensure quality remains high)
  4. As part of a closed-loop system – if your RPA tool can handle changes to its rules through feedback (ie not just static rules) then it can become an important part of a learning, improving solution

You’ll notice an increasing level of sophistication from 1-4. Not just sophistication but potential value to operators too.

We’ll take a closer look at the use of RPA in OSS over the next couple of days.

Onboarding outsiders as a new OSS business model

The majority of these new services [such as healthcare, content and media, autonomous vehicles, smart homes etc.] require partnerships and will be based on a platform business model where the customer is not aware of who is providing which part of the service and to be quite frankly honest, wont care. All as they will care about is the customer experience and the end-to-end delivery of their service that they have paid for. This is where the opportunity for the telco comes and we need to think beyond data!
Aaron Boasman-Patel
here on TM Forum Inform.

Are your OSS tools already integrating with third-party services?

Do your catalog / orchestration engines already call upon microservices from outside your organisation? Perhaps it’s something as simple as providing a content service bundled with a service provider’s standard bitpipe service. Perhaps it’s also bundled with an internal-facing analytics service or an outward-facing shopping cart service.

A telco isn’t going to want to (or be able to) provide all of these services but can use partnerships and catalog items to allow each unique customer to build the bundled offer they want.

This is where catalogs and microservices potentially represent a type of small-grid model. There are already many APIs from third-party providers and the catalog / orchestration tools already exist to support the model. For many telcos, it will take a slight mindset shift – to embrace partnerships (ie to discard the “not invented here” thinking); to allowing their many existing bit-pipe subscribers to sell and bill through the telco platform (embrace sell-through); to build platforms and processes to allow for simple certification and onboarding of third-parties.

If your current OSS isn’t already integrating with third-party services, is it on your roadmap? Then again, does it suit your proposed future business models?

Will it take open source to unlock OSS potential?

I have this sense that the other OSS, open source software, holds the key to the next wave of OSS (Operational Support Systems) innovation.

Why? Well, as yesterday’s post indicated (through Nic Brisbourne), “it’s hard to do big things in a small way.” I’d like to put a slight twist on that concept by saying, “it’s hard to do big things in a fragmented way.” [OSS is short for fragmented after all]

The skilled resources in OSS are so widely spread across many organisations (doing a lot of duplicated work) that we can’t reach a critical mass of innovation. Open source projects like ONAP represent a possible path to critical mass through sharing and augmentating code. They provide the foundation upon which bigger things can be built. If we don’t uplift the foundations across the whole industry quickly, we risk losing relevance (just ask our customers for their gripes list!).

BTW. Did you notice the news that Six Linux Foundation open source networking projects have just merged into one? The six initial projects are ONAP, OPNFV, OpenDaylight,, PDNA, and SNAS. The new project is called the LF Networking Fund (LFN).

But you may ask how organisations can protect their trade secrets whilst embracing open source innovation. Derek Sivers provides a fascinating story and line of thinking in “Why my code and ideas are public.” I really recommend having a read about Valerie.

Alternatively, if you’re equating open source with free / unprofitable, this link provides a list of highly successful organisations with significant open source contributions. There are plenty of creative ways to be rewarded for open source effort.

Comment below if you agree or disagree about whether we need OSS to unlock the potential of OSS innovation.

The two types of disruptive technologists

OSS is an industry that’s undergoing constant, and massive change. But it still hasn’t been disrupted in the modern sense of that term. It’s still waiting to have its Uber/AirBnB-moment, where the old way becomes almost obsoleted by the introduction of a new way. OSS is not just waiting, but primed for disruption.

It’s a massive industry in terms of revenues, but it’s still far from delivering everything that customers want/need. It’s potentially even holding back the large-scale service provider industry from being even more influential / efficient in the current digital communications world. Our recent OSS Call for Innovation spelled out the challenges and opportunities in detail.

Today we’ll talk about the two types of disruptive technologists – one that assists change and one that hinders.

The first disruptive technologist is a rare beast – they’re the innovators who create solutions that are distinctly different from anything else in the market, changing the market (for the better) in the process. As discussed in this recent post, most of the significant changes occurring to OSS have been extrinsic (from adjacent industries like IT or networking rather than OSS). We need more of these.

The second disruptive technologist is all too common – they’re the technologists whose actions disrupt an OSS implementation. They’re usually well-intended, but can get in the way of innovation in two main ways:
1) By not looking beyond incremental change to existing solutions
2) Halting momentum by creating and resolving a million “what if?” scenarios

Most of us probably fall into the second category more often than the first. We need to reverse that trend individually and collectively though don’t we?

Would you like to nominate someone who stands out as being the first type of disruptive technologist and why?

How “what if?” scenarios can halt a project

Let’s admit it; we’ve all worked on an OSS project that has gone into a period of extended stagnation because of a fear of the unknown. I call them “What if?” scenarios. They’re the scenarios where someone asks, “What if x happens?” and then the team gets side-tracked whilst finding an answer / resolution. The problem with “What if?” scenarios is that many of them will never happen, or will happen on such rare occasions that the impact will be negligible. They’re the opposite end of the Pareto Principle – they’re the 20% that take up the 80% of effort / budget / time. They need to be minimised and/or mitigated.

In some cases, the “what if?” questions comes from a lack of understanding about the situation, the product suite and / or the future solution. That’s completely understandable because we can never predict all of the eventualities of an OSS project at the outset. That’s the OctopOSS at work – you think you have all of the tentacles under control, but another one always comes and whacks you on the back of the head.

The best way to reduce the “what if?” questions from getting out of control is to give stakeholders a sandpit / MVP / rapid-prototype / PoC environment to interact with.

The benefit of the prototype environment is that it delivers something tangible, something that stakeholders far and wide can interact with and test assumptions, usefulness, usability, boundary cases, scalability, etc. Stakeholders get to understand the context of the product and get a better feeling for what the end solution is going to look like. That way, many of the speculative “what ifs?” are bypassed and you start getting into the more productive dialogue earlier. The alternative, the creation of a document or discussion, can devolve into an almost endless set of “what-if” scenarios and opinions, especially when there are large groups of (sometimes militant) stakeholders.

The more dangerous “what if?” questions come from the experts. They’re the ones who demonstrate their intellectual prowess by finding scenario after scenario that nobody else is considering. I have huge admiration for those who can uncover potential edge cases, race conditions, loopholes in code, etc. The challenge is that they can be extremely hard to document, test for and circumvent. They’re also often very difficult to quantify or prove a likelihood of occurrence, thus consuming significant resources.

Rather than divert resources to resolving all these “what if?” questions one-by-one, I try to seek a higher-order “safety-net” solution. This might be in the form of exception handling, try-catch blocks, fall-out analysis reports, etc. Or, it might mean assigning a watching brief on the problem and handling it only if it arises in future.

The evolving complexity of RCA

Root cause analysis (RCA) is one of the great challenges of OSS. As you know, it aims to identify the probable cause of an alarm-storm, where all alarms are actually related to a single fault.

In the past, my go-to approach was to start with a circuit hierarchy-based algorithm. If you had an awareness of the hierarchy of circuits, usually through an awareness in inventory, if you have a lower-order fault (eg Loss of Signal on a transmission link caused by a cable break), then you could suppress all higher-order alarms (ie from bearers or tributaries that were dependent upon the L1 link. That works well in the fixed networks of distant past (think SDH / PDH). This approach worked well because it was repeatable between different customer environments.

Packet-switching data networks changed that to an extent, because a data service could traverse any number of links, on-net or off-net (ie leased links). The circuit hierarchy approach was still applicable, but needed to be supplemented with other rules.

Now virtualised networking is changing it again. RCA loses a little relevance in the virtualised layer. Workloads and resource allocations are dynamic and transient, making them less suited to fixed algorithms. The objective now becomes self-healing – if a failure is identified, failed resources are spun down and new ones spun up to take the load. The circuit hierarchy approach loses relevance, but perhaps infrastructure hierarchy still remains useful. Cable breaks, server melt-downs, hanging controller applications are all examples of root causes that will cause problems in higher layers.]

Rather than fixed-rules, machine-based pattern-matching is the next big hope to cope with the dynamically changing networks.

The number of layers and complexity of the network seems to be ever increasing, and with it RCA becomes more sophisticated…. If only we could evolve to simpler networks rather than more complex ones. Wishful thinking?

Customers don’t invest in OSS. What do they invest in?

“An organisation buys an OSS, not because it wants an Operational Support System, but because it wants Operational Support.”

So if our customers are not investing in our OSS, what are they actually investing in? Easy! They’re investing in the ability to solve their own problems and opportunities in future.

If we don’t actually understand operations, what chance do we have to deliver operational support? We keep hearing the term, “customer experience this,” “CX that,” so it must be important right? Operational support staff might be a few steps removed from us (intentionally or unintentionally) but they are our “real” customers and the only way we can develop a solution that empathises with them is by spending time with them and listening (not always easy for us know-it-all OSS builder-types).

And just because we have a history in ops doesn’t mean we can assume to know this time. Operations are different at each organisation.

So, are we sure we understand the nature, extent and context of the unique problem/s that this customer needs to solve (not wants to solve)?