Would an EoL be beneficial for OSS?

In the world of networking, it’s common for devices to go EOL (end-of-life). Capital spend and depreciation models are based around refresh cycles of around 5-7 years. Vendors reinforce this refresh cycle by designing obsolescence into maintenance, support and part supplies. Customers tend to simply submit to the risk of having no vendor support by buying the next generation replacements.

But how often do you hear of an OSS going EOL? Not often right? They tend to get written off only when the cost of upkeep outweighs new revenues.

I know, I can hear you saying that software is different from hardware and of course I agree with you. I’d partially counter by claiming that software architectures and development platforms also have a discernibly useful life just like physical network devices. If you doubt that, I’m sure you’ve seen OSS tools with origins in the 1990s that are still being developed upon. I tend to believe that product usefulness becomes asymptotic for its vendors. With the speed of change and proliferation of new platforms, useful lives are getting ever-shorter.

Would a pre-ordained product replacement life-cycle be beneficial for the OSS industry? It has some merits.

For a start, planned obsolescence enforces designs with interchangeability, in line with the small-grid OSS described yesterday. It promotes short-term enhancements to long-term visions. It becomes easier for customers to write off their investment and inject new capital into the vendor market. It penalises the amount of Frankenstein integrations that tend to become increasingly burdensome (to vendor and customer) into the future. It enforces those mythical beasts of telco software – subtraction projects. It promotes innovation to avoid the asymptotic benefit deterioration curve shown below:
Asymptotic OSS feature development

As the asymptote is being reached, a new jumping-off point commences with the new product.

But it’s a difficult status-quo to break. Vendors have invested millions of developer hours into their products. Taking a product EoL is effectively throwing that invested effort away. For carriers, it means the risk and cost of breaking integrations / processes and replacing them with new ones.

I’d love to hear your thoughts on whether an EOL model might be relevant / useful for your OSS.

The future of work and its impact on OSS

Many years ago, I worked on a seriously big OSS transformation for one of the region’s biggest telcos. Everything was big on the project, the investment, the resources, the documentation. Everything except the outcomes. There was so much inefficiency that I often spoke about making one day of progress for every ten on site. Meetings, bureaucracy, impossible approval cycles, customer re-organisations, over-analysis, etc all added up to stagnation.

This contrasted so much with some of the amazing small teams I’ve worked alongside. Teams that worked cohesively, cleverly and just got stuff done with almost no resources. It’s one of the reasons I feel that the future of work, even for the very large organisations, will be via small teams. Outsourced to small, efficient teams / organisations. The gig economy, and the proliferation of tools that support it, make it an obvious approach to take, especially for very large organisations to leverage. Proof of work technologies, such as those building upon the discovery of blockchain, will provide further impetus to use smaller teams of experts.

Experts like a friend and colleague of mine who once built an alarm management tool in a weekend, by himself. It also happened to be more sophisticated than his employer’s existing tool that had taken years of combined developer effort by a larger team.

Maybe I’ll be proven wrong, but I see the transition to this model of work as being inevitable. The question I have is how to make our OSS more accommodating of this work model. Behemoth OSS stacks won’t. Highly modular OSS made up of many smaller components probably will, as long as they don’t succumb to the OSS chessboard analogy. The pulleys and strings will make it impossible for small, interchangable teams to decipher and manage.

A small-grid OSS model is the one I’d be backing in.

OSS – like a duck on a pond

Let’s start with a basic question. “What does an OSS need to do?”

The basic answer is, “make operations easier.”

The real answer(s) is so much more nuanced than that of course. The term easier can also encapsulate other words such as faster, more accurate, more repeatable, cheaper, etc.

Designing, building, operating and maintaining a sizable network is extremely challenging, despite network operators around the world, and the vendors that supply to them, employing some of the best and brightest. So we design OSS and related tools / processes to make operations easier.

Yet I sometimes wonder whether we achieve that aim – to make operations easier. Seems to me that we tend to focus more on just replicating functions at a higher layer in the management stack. That is, moving the function to the OSS rather than EMS/NMS, without really making it much easier operationally.

Let’s start at the user interface (UI). How often are they intuitive enough for an experienced network operator to start doing tasks with negligible OSS expert guidance?
Let’s look at deployments. How often are the projects low on effort, risk, cost and complexity?
Let’s look at flexibility (ie in-flight modifications or transformations). How often do we actually deliver flexibility to our customers through our OSS. To ask the same as above, how often are our changes low on effort, risk, cost and complexity?

As a small step towards providing an answer, I wonder whether it’s a case of making the hard things look easy and the easy things look hard.

We want to make the really hard operational things much easier to do within an OSS because that’s the primary purpose of an OSS. That’s the example of a duck on a pond. The OSS is gliding along effortlessly across the top of the water, but under the water it is paddling furiously.

Conversely, we want to make the really easy* operational things look hard to do within an OSS so that we’re not constantly being asked to build functionality / complexity into our OSS that doesn’t warrant being there. It diffuses the intent of the OSS. Just because we can, doesn’t mean we should.

OSS Road-itecture. Part-roadmap, part-architecture

A post from earlier this week discussed a less risky, dependency-reduced, stepping-stone transformation approach. It contrasted with the big-bang delivery model that’s often proposed on OSS projects.

Taking the same train of thought, have you noticed how often architects (including myself) come up with an end-state view of what an OSS, or IT, or networks will be? Have you also noticed that they often seek to demonstrate the cleverness of their architecture in the end-state?

To be honest, I’m more impressed with architectures that cleverly guide a reader through the minefield of complexity via multiple lesser steps and steer towards an intended end-state. To be equally honest, this type of architecture is probably part-roadmap, part-architecture. The journey often demonstrates the impracticality of an ideal end-state.

This may lead to an OSS with compromises but at least it’s not compromised.

The big-bang end-state might look really impressive on paper, but not be viable for the delivery team.

For fear of OSS investment

Friday’s post discussed three analogies about the challenges of performing an OSS pivot.

The biggest challenge in initiating the transformation / replacement of any significant OSS is fear. There are many OSS out there whose “owners” want to change and need to change… but fear changing because a significant pivot would mean a “sell the farm” decision.

The fear is completely understandable. These are highly complex projects with so many potential pitfalls that invest massive amounts of resource (time, money, people). The risks can be huge for sponsors / stakeholders / investors. Failure of these projects can be career changing. The upside potential rarely balances the downside risk.

So, the only choice we have is to present pivots that aren’t “bet the farm” decisions.

The delivery approach of a bet the farm pivot tends to look like this:
The Bet-the-farm OSS Transformation Approach

The less risky, dependency-reduced, stepping-stone transformation tends to look a bit like this, but probably with a lot more verticals, as described here:
The Stepping-Stone OSS Transformation Approach

Do the laws of physics prevent you from making an OSS pivot?

AIrcraft carrier
Image linked from GCaptain.com.

As you already know, the word pivot has become common in the world of business, particularly the world of start-ups. It’s a euphemism for a significant change in strategic direction. In the context of today’s post, I love the word pivot because it implies a rapid change in direction, something that’s seemingly impossible for most of our OSS and the customers who use them.

I like to use analogies. It’s no coincidence that some of the analogies posted here on PAOSS relate to the challenge in making strategic change in our OSS. Here are just three of those analogies:

The OSS intertia principle relates classical physics with our OSS, where Force equals Mass x Acceleration (F = ma). In other words, the greater the mass (of your OSS), the more force must be applied to reach a given acceleration (ie to effect a change)

The OSS chess-board analogy talks about the rubber bands and pulleys (ie integrations) that enmesh the pieces on our OSS chessboard. This means that other pieces get dragged out of position whenever we try to move any individual piece and chaos ensues.

The aircraft carrier analogy compares OSS (and the CSPs they service) with navies of old. In days gone by, CSPs enjoyed command of the sea. Their boats were big, powerful and mobile enough to move around world. However, their size requires significant planning to change course. The newer application and content communications models are analogous to the advent of aviation. The over the top (OTT) business model has the speed, flexibility, lower cost base and diversity of aircraft. Air supremacy has changed the competitive dynamic. CSPs and our OSS can’t quickly change from being a navy to being an airforce, so the aircraft carrier approach looks to the future whilst working within the constraints of the past.

When making day to day changes within, and to, your OSS does the ability to pivot ever come to mind?

Do you intentionally ensure it stays small, modular and limit its integrations to simplify your game of OSS chess?
If constrained by existing mass that you simply can’t eliminate, do you seek to transform via OSS‘s aviation equivalents?
Or like many of the OSS around the world, are you just making them larger, enmeshed behemoths that will never be able to change the laws of physics and achieve a pivot?

Do any of our global target architectures represent such behemoths?

Build an OSS and they will come… or sometimes not

Build it and they will come.

This is not always true for OSS. Let me recount a few examples.

The project team is disconnected from the users – The team that’s building the OSS in parallel to existing operations doesn’t (or isn’t able to) engage with the end users of the OSS. Once it comes time for cut-over, the end users want to stick with what they know and don’t use the shiny new OSS. From painful experience I can attest that stakeholder management is under-utilised on large OSS projects.

Turf wars – Different groups within a customer are unable to gain consensus on the solution. For example, the operational design team gains the budget to build an OSS but the network assurance team doesn’t endorse this decision. The assurance team then decides not to endorse or support the OSS that is designed and built by the design team. I’ve seen an OSS worth tens of millions of dollars turned off less than 2 years after handover because of turf wars. Stakeholder management again, although this could be easier said than done in this situation.

It sounded like a good idea at the time – The very clever OSS solution team keeps coming up with great enhancements that don’t get used, for whatever reason (eg non fit-for-purpose, lack of awareness of its existence by users, lack of training, etc). I’ve seen a customer that introduced over 500 customisations to an off-the-shelf solution, yet hundreds of those customisations hadn’t been touched by users within a full year prior to doing a utilisation analysis. That’s right, not even used once in the preceding 12 months. Some made sense because they were once-off tools (eg custom migration activities), but many didn’t.

The new OSS is a scary beast – The new solution might be perfect for what the customer has requested in terms of functionality. But if the solution differs greatly from what the operators are used to, it can be too intimidating to be used. A two-week classroom-based training course at the end of an OSS build doesn’t provide sufficient learning to take up all the nuances of the new system like the operators have developed with the old solution. Each significant new OSS needs an apprenticeship, not just a short-course.

It’s obsolete before it’s finishedOSS work in an environment of rapid change – networks, IT infrastructure, organisation models, processes, product offerings, regulatory shifts, disruptive innovation, etc, etc. The longer an OSS takes to implement, the greater the likelihood of obsolescence. All the more reason for designing for incremental delivery of business value rather than big-bang delivery.

What other examples have you experienced where an OSS has been built, but the users haven’t come?

Falsely rewarding based on OSS existence rather than excellence

There’s a common belief that most jobs see people rewarded for presence rather than performance. That is, they’re encouraged to be on site from 9am to 5pm rather than being given free reign over their work schedules as long as key outcomes are met / exceeded.

In OSS vendor / product selection there’s a similar concept. Contracts are often awarded based on existence rather than excellence. When evaluating a product, if it’s able to do a majority of the functions in the long list of requirements then the box is ticked.

However, this doesn’t take into account that there are usually only a very small number of functions that any given customer’s OSS needs to perform at a very high level of efficiency. All the others are effectively just nice to have. That’s the 80/20 rule at work.

When guiding a customer through their vendor selections, I always take them through an exercise to identify the use-cases / functions that really matter. Then we ensure that the demos or proofs of concept focus closely on how excellent the OSS is at those most important factors.

OSS automations – just because we can, doesn’t mean we should

Automation is about using machines / algorithms to respond faster than humans can, or more efficiently than humans can, or more accurately than humans can… but only if the outcomes justify the costs. When it comes to automations, it’s a case of, “just because we can, doesn’t mean we should.”

The more complex the decision tree you’re trying to automate, the higher the costs and therefore the harder it becomes to cost-justify. So the first step in any automation is taking a lateral thinking approach to simplifying the decision tree.

This recent post highlighted a graph from Nokia’s Bell Labs and the financial dependency that network slicing has on operational automation:
Nokia Network Slicing

Let’s use the Toyota Five Whys technique to work our way through the implications of this:

Statement 0: As CSPs, we need to drastically reduce complexity in the processes / decision-trees across our whole organisation.

Why 1? So that we can apply significant levels of automation

Why 2? So that we can apply technologies / techniques such as network slicing or virtualisation that are cost-justifiable

Why 3? So that we can offer differentiated, premium services

Why 4? So that our offerings don’t become commodities

Why 5? So that we retain corporate profitability to return to shareholders and/or invest in further interesting projects

I love that we’re looking to all number of automation technologies / techniques to apply to our OSS. However, we’re bypassing the all-important statement 0. We’re starting at Why 1 and partially missing the cost-justifiable part of Why 2. If our automation projects don’t prove cost-justifiable, then we never get the chance to reach whys 3, 4 and 5.

OSS implementation, but without the dependencies

One of the challenges with getting a new OSS or OSS transformation project completed can be the large number of dependencies that can cause momentum gridlock. If you’re looking to deliver business value in one big-bang, which is a really common approach to delivering OSS projects, then you end up juggling many different activities and hoping they all align at the right times.

I’ve noticed that the vendors tend to design their delivery schedules around big-bang / waterfall approaches like below.
Big-bang OSS delivery

Many vendors will even assure you that this is their standard practice and are hesitant to consider changes to their “best practice” delivery scheduling. Having been involved in many of these types of deliveries in the past, on both vendor and customer side, I can assure you that they rarely work well.

Generally speaking, the gridlocks occur on the customer-side, but the result is detrimental to customer and vendor alike. Hold-ups mean inefficient allocation of resources as well as the resultant cost / time over-runs.

The alternative is to apply a bit more lateral thinking to how you break down the work into smaller chunks. The lateral thinking work breakdown aims are two-fold:

  1. How to break up the work so that it best avoids dependencies; whilst also
  2. Delivering some sort of value to the customer

There are many dependencies on a typical OSS project – hardware, procurement, IT infrastructure, network connectivity, security, approvals, integrations, licensing, resource availability, data quality and many more. However, each different customer, their org chart and project has its own unique mix of dependencies, so I don’t subscribe to the “best practice” argument to project delivery.

The diagram below shows an example of an alternate breakdown. The business value chunks that are delivered might be tiny in some cases, but at least momentum can be demonstrated. Rather than having a mass of entwined dependencies, you can isolate and minimise dependencies for that sliver of business value. When the dependency/ies has cleared, you can jump straight onto the next activity from an existing build-state rather than having to align all the activities to land in perfect precision.
Incremental OSS work breakdown

OSS project stalled? Cancel it

When a project appears to be in limbo, in a permanent holding pattern, where sunk costs meet opportunity costs, where no one can figure out what to do…

Cancel it.
Cancel it with a week’s notice.

One of two things will happen:
A. A surge of support and innovation will arrive, and it won’t be stuck any more.
B. You’ll follow through and cancel it, and you won’t be stuck any more.

It costs focus and momentum to carry around the stalled. Let it go.”
Seth Godin on his blog here.

OSS projects have a tendency to get so big and complex and with so many dependencies that they can stagnate. When projects stagnate, we have a tendency of treating them with contempt or cynicism don’t we? We treat them this way even when we’re involved, so you know that outsiders are treating them with even more contempt and cynicism.

So Seth’s concept is an interesting one. I haven’t tried his technique before.

Have you? Did it achieve your desired outcomes?
Did it rally the troops? Did it clear the way for assignment of resources onto better projects, Darwinian-style? Or did it just throw away the last vestiges of momentum and all sunk costs?

OSS holds the key to network slicing

Network slicing opens new business opportunities for operators by enabling them to provide specialized services that deliver specific performance parameters. Guaranteeing stringent KPIs enables operators to charge premium rates to customers that value such performance. The flip side is that such agreements will inevitably come with tough contractual obligations and penalties when the agreed KPIs are not met…even high numbers of slices could be managed without needing to increase the number of operational staff. The more automation applied, the lower the operating costs. At 100 percent automation, there is virtually no cost increase with the number of slices. Granted this is a long-term goal and impractical in the short to medium term, yet even 50 percent automation will bring very significant benefits.”
From a paper by Nokia – “Unleashing the economic potential of network slicing.”

With typical communications services tending towards commoditisation, operators will naturally seek out premium customers. Customers with premium requirements such as latency, throughput, reliability, mobility, geography, security, analytics, etc.

These custom requirements often come with unique network configuration requirements. This is why network slicing has become an attractive proposition. The white paper quoted above makes an attempt at estimating profitability of network slicing including some sensitivity analyses. It makes for an interesting read.

The diagram below is one of many contained in the White Paper:
Nokia Network Slicing

It indicates that a significant level of automation is going to be required to achieve an equivalent level of operational cost to a single network. To re-state the quote, “The more automation applied, the lower the operating costs. At 100 percent automation, there is virtually no cost increase with the number of slices. Granted this is a long-term goal and impractical in the short to medium term, yet even 50 percent automation will bring very significant benefits.”

Even 50% operational automation is a significant ambition. OSS hold the key to delivering on this ambition. Such ambitious automation goals means we have to look at massive simplification of operational variant trees. Simplifications that include, but go far beyond OSS, BSS and networks. This implies whole-stack simplification.

If ONAP is the answer, what are the questions?

ONAP provides a comprehensive platform for real-time, policy-driven orchestration and automation of physical and virtual network functions that will enable software, network, IT and cloud providers and developers to rapidly automate new services and support complete lifecycle management.
By unifying member resources, ONAP is accelerating the development of a vibrant ecosystem around a globally shared architecture and implementation for network automation–with an open standards focus–faster than any one product could on its own
.”
Part of the ONAP charter from onap.org.

The ONAP project is gaining attention in service provider circles. The Steering Committee of the ONAP project hints at the types of organisations investing in the project. The statement above summarises the mission of this important project. You can bet that the mission has been carefully crafted. As such, one can assume that it represents what these important stakeholders jointly agree to be the future needs of their OSS.

I find it interesting that there are quite a few technical terms (eg policy-driven orchestration) in the mission statement, terms that tend to pre-empt the solution. However, I don’t feel that pre-emptive technical solutions are the real mission, so I’m going to try to reverse-engineer the statement into business needs. Hopefully the business needs (the “why? why? why?” column below) articulates a set of questions / needs that all OSS can work to, as opposed to replicating the technical approach that underpins ONAP.

Phrase Interpretation Why? Why? Why?
real-time The ability to make instantaneous decisions Why1: To adapt to changing conditions
Why2: To take advantage of fleeting opportunities or resolve threats
Why 3: To optimise key business metrics such as financials
Why 4: As CSPs are under increasing pressure from shareholders to deliver on key metrics
policy-driven orchestration To use policies to increase the repeatability of key operational processes Why 1: Repeatability provides the opportunity to improve efficiency, quality and performance
Why 2: Allows an operator to service more customers at less expense
Why 3: Improves corporate profitability and customer perceptions
Why 4: As CSPs are under increasing pressure from shareholders to deliver on key metrics
policy-driven automation To use policies to increase the amount of automation that can be applied to key operational processes Why 1: Automated processes provide the opportunity to improve efficiency, quality and performance
Why 2: Allows an operator to service more customers at less expense
Why 3: Improves corporate profitability and customer perceptions
physical and virtual network functions Our networks will continue to consist of physical devices, but we will increasingly introduce virtualised functionality Why 1: Physical devices will continue to exist into the foreseeable future but virtualisation represents an exciting approach into the future
Why 2: Virtual entities are easier to activate and manage (assuming sufficient capacity exists)
Why 3: Physical equipment supply, build, deploy and test cycles are much longer and labour intensive
Why 4: Virtual assets are more flexible, faster and cheaper to commission
Why 5: Customer services can be turned up faster and cheaper
software, network, IT and cloud providers and developers With this increase in virtualisation, we find an increasingly large and diverse array of suppliers contributing to our value-chain. These suppliers contribute via software, network equipment, IT functions and cloud resources Why 1: CSPs can access innovation and efficiency occurring outside their own organisation
Why 2: CSPs can leverage the opportunities those innovations provide
Why 3: CSPs can deliver more attractive offers to customers
Why 4: Key metrics such as profitability and customer satisfaction are enhanced
rapidly automate new services We want the flexibility to introduce new products and services far faster than we do today Why 1: CSPs can deliver more attractive offers to customers faster than competitors
Why 2: Key metrics such as market share, profitability and customer satisfaction are enhanced as well as improved cashflow
support complete lifecycle management The components that make up our value-chain are changing and evolving so quickly that we need to cope with these changes without impacting customers across any of their interactions with their service Why 1: Customer satisfaction is a key metric and a customer’s experience spans the entire lifecyle of their service.
Why 2: CSPs don’t want customers to churn to competitors
Why 3: Key metrics such as market share, profitability and customer satisfaction are enhanced
unifying member resources To reduce the amount of duplicated and under-synchronised development currently being done by the member bodies of ONAP Why 1: Collaboration and sharing reduces the effort each member body must dedicate to their OSS
Why 2: A reduced resource pool is required
Why 3: Costs can be reduced whilst still achieving a required level of outcome from OSS
vibrant ecosystem To increase the level of supplier interchangability Why 1: To reduce dependence on any supplier/s
Why 2: To improve competition between suppliers
Why 3: Lower prices, greater choice and greater innovation tend to flourish in competitive environments
Why 4: CSPs, as customers of the suppliers, benefit
globally shared architecture To make networks, services and support systems easier to interconnect across the global communications network Why 1: Collaboration on common standards reduces the integration effort between each member at points of interconnect
Why 2: A reduced resource pool is required
Why 3: Costs can be reduced whilst still achieving interconnection benefits

As indicated in earlier posts, ONAP is an exciting initiative for the CSP industry for a number of reasons. My fear for ONAP is that it becomes such a behemoth of technical complexity that it becomes too unwieldy for use by any of the member bodies. I use the analogy of ATM versus Ethernet here, where ONAP is equivalent to ATM in power and complexity. The question is whether there’s an Ethernet answer to the whys that ONAP is trying to solve.

I’d love to hear your thoughts.

(BTW. I’m not saying that the technologies the ONAP team is investigating are the wrong ones. Far from it. I just find it interesting that the mission is starting with a technical direction in mind. I see parallels with the OSS radar analogy.)

Where are the reliability hotspots in your OSS?

As you already know, there are two categories of downtime – unplanned (eg failures) and planned (eg upgrades / maintenance).

Planned downtime sounds a lot nicer (for operators) but the reality is that you could call both types “incidents” – they both impact (or potentially impact) the customer. We sometimes underestimate that fact.

Today’s question is whether you’re able to identify where the hotspots are in your OSS suite when you combine both types of downtime. Can you tell which outages are service-impacting?

In a round-about way, I’m asking whether you already have a dashboard that monitors uptime of all the components (eg applications, probes, middleware, infra, etc) that make up your complete OSS / BSS estate? If you do, does it tell you what you anecdotally know already, or are there sometimes surprises?

Does the data give you the evidence you need to negotiate with the implementers of problematic components (eg patch cadence, the need for reliability fixes, streamlining the patch process, reduction in customisations, etc)? Does it give you reason to make architectural changes (eg webscaling)?

Stop looking for exciting new features for your OSS

The iPhone disrupted the handset business, but has not disrupted the cellular network operators at all, though many people were convinced that it would. For all that’s changed, the same companies still have the same business model and the same customers that they did in 2006. Online flight booking doesn’t disrupt airlines much, but it was hugely disruptive to travel agents. Online booking (for the sake of argument) was sustaining innovation for airlines and disruptive innovation for travel agents.
Meanwhile, the people who are first to bring the disruption to market may not be the people who end up benefiting from it, and indeed the people who win from the disruption may actually be doing something different – they may be in a different part of the value chain. Apple pioneered PCs but lost the PC market, and the big winners were not even other PC companies. Rather, most of the profits went to Microsoft and Intel, which both operated at different layers of the stack. PCs themselves became a low-margin commodity with fierce competition, but PC CPUs and operating systems (and productivity software) turned out to have very strong winner-takes-all effects
.”
Ben Evans
on his blog about Tesla.

As usual, Ben makes some thought-provoking points. The ones above have coaxed me into thinking about OSS from a slightly perspective.

I’d tended to look at OSS as a product to be consumed by network operators (and further downstream by the customers of those network operators). I figured that if our OSS delivered benefit to the downstream customers, the network operators would thrive and would therefore be prepared to invest more into OSS projects. In a way, it’s a bit like a sell-through model.

But the ideas above give some alternatives for OSS providers to reduce dependence on network operator budgets.

Traditional OSS fit within a value-chain that’s driven by customers that wish to communicate. In the past, the telephone network was perceived as the most valuable part of that value-chain. These days, digitisation and competition has meant that the perceived value of the network has dropped to being a low-margin commodity in most cases. We’re generally not prepared to pay a premium for a network service. The Microsofts and Intels of the communications value-chain is far more diverse. It’s the Googles, Facebooks, Instagrams, YouTubes, etc that are perceived to deliver most value to end customers today.

If I were looking for a disruptive OSS business model, I wouldn’t be looking to add exciting new features within the existing OSS model. In fact, I’d be looking to avoid our current revenue dependence on network operators (ie the commoditising aspects of the communications value-chain). Instead I’d be looking for ways to contribute to the most valuable aspects of the chain (eg apps, content, etc). Or even better, to engineer a more exceptional comms value-chain than we enjoy today, with an entirely new type of OSS.

Chasing the big OSS waves

The diagram below attempts to show how the entire market (whether that’s the supplier-side or the buyer-side) will absorb a given new feature.

The leaders pick up the concept at T0 and then it takes another few years before the laggards implement it.
OSS Buyer Developer Curve

Most of us in the OSS implementation world crave to be at the leading edge of change. The right-side of the curve is definitely the sexier side to be on. I know I do. It’s part of the reason this blog exists – to stay abreast of the exciting new ideas, projects and technologies that are coming through in OSS. Funnily enough, there’s probably even people within most of the laggards who are already excited about a new concept not long after T0, but are just unable to implement it until much later.

Supplier sales-pitches also tend to focus on the right side of the curve. That’s where the buzz is. That’s where the premiums are, the rewards for being first to market. It’s the customers on the right-side of the curve that are most attractive as sales targets for many suppliers.

But I also wonder whether the increasing proliferation of tech options within OSS means there’s also increasing inefficiency for suppliers (and possibly buyers) on the right side of the curve? Do we focus all our development efforts on ONAP or [insert any of millions of other alternative platforms, technologies, ideas, etc] today? What if the mass-market goes down an alternate path to the one you’ve chosen? How long before you identify a divergence from the mass-market trend? What’s the impact of changing direction (or not)? Are you bound to spill some blood by playing on the bleeding edge?

The left side of the graph is arguably more predictable. You can already see where the market is trending. Has the whole concept just been hype or has this new thing really made a difference for customers? Most of the implementation hurdles are likely to have already been resolved. Products have matured. More integrations, reports, etc have been developed. Waters have already been chartered.

I don’t have the numbers to back this up, but I also have a suspicion that there’s less supplier competition for the business of laggard or follower customers. I’ve seen some companies that have thrived on this model. They get a nice unimpeded ride on the back of the wave whilst everyone else is fighting to catch the front-edge of it.

Chasing the left side of the curve might seem counter-intuitive because it clearly represents a falling market. But there’s always the next wave to jump onto, each with similar predictability and reduced competition.

Not only that, but a majority of the the most important OSS use-cases have been around for many years. It’s increasingly difficult to find new functionality that delivers tangible benefits. Whilst other suppliers have jumped off to chase the next big thing, the followers can keep refining their solutions for what matters most.

Let me pose the question this way – Can you think of a single OSS product that is so refined that it can’t do the basics any better than it already does? Nope??

Persona mapping for OSS PoCs

When selecting new applications for an OSS or to augment an existing OSS, it always makes sense to me to run a Proof of Concept. But what do we want to demonstrate in that PoC? For me, we want to run demonstrations of the factors (eg features, use-cases, processes, etc) that justify the investment.

A simple exercise you can use is to identify the personas / roles that interact with the OSS. This could include personas such as NOC operator, strategic planner, network engineer, order entry, field ops, data / analytics, application administrator, etc. The actual personas will differ within each organisation of course.

For each of those personas, we can identify and interview an individual that represents that persona.

Interview questions include:

  1. What are the key responsibilities of your role
  2. What is the most important goal / KPI for your role
  3. How does this OSS (or proposed OSS) support you meeting this goal
  4. Describe the single most important process / function that you perform using the OSS
  5. Why is it so important
  6. How often do you perform this process / function
  7. Please provide a short list of other important processes / functions you perform with this OSS

We can then build this into a matrix and seek to prioritise into a set of use-cases. Based on time and cost constraints, we can then build the top-n of those use-cases into implementation scenarios for the PoC.

If your partners don’t have to talk to you then you win

If your partners don’t have to talk to you then you win.”
Guy Lupo
.

Put another way, the best form of customer service is no customer service (ie your customers and/or partners are so delighted with your automated offerings that they have no reason to contact you). They don’t want to contact you anyway (generally speaking). They just want to consume a perfectly functional and reliable solution.

In the deep, distant past, our comms networks required operators. But then we developed automated dialling / switching. In theory, the network looked after itself and people made billions of calls per year unassisted.

Something happened in the meantime though. Telco operators the world over started receiving lots of calls about their platform and products. You could say that they’re unwanted calls. The telcos even have an acronym called CVR – Call Volume Reduction – that describes their ambitions to reduce the number of customer calls that reach contact centre agents. Tools such as chatbots and IVR have sprung up to reduce the number of calls that an operator fields.

Network as a Service (NaaS), the context within Guy’s comment above, represents the next new tool that will aim to drive CVR (amongst a raft of other benefits). NaaS theoretically allows customers to interact with network operators via impersonal contracts (in the form of APIs). The challenge will be in the reliability – ensuring that nothing falls between the cracks in any of the layers / platforms that combine to form the NaaS.

In the world of NaaS creation, Guy is exactly right – “If your partners [and customers] don’t have to talk to you then you win.” As always, it’s complexity that leads to gaps. The more complex the NaaS stack, the less likely you are to achieve CVR.

The OSS self-driving vehicle

I was lucky enough to get some time of a friend recently, a friend who’s running a machine-learning network assurance proof-of-concept (PoC).

He’s been really impressed with the results coming out of the PoC. However, one of the really interesting factors he’s been finding is how frequently BAU (business as usual) changes in the OSS data (eg changes in naming conventions, topologies, etc) would impact results. Little changes made by upstream systems effectively invalidated baselines identified by the machine-learning engines to key in on. Those little changes meant the engine had to re-baseline / re-learn to build back up to previous insight levels. Or to avoid invalidating the baseline, it would require re-normalising all of data prior to the identification of BAU changes.

That got me wondering whether DevOps (or any other high-change environment) might actually hinder our attempts to get machine-led assurance optimisation. But more to the point, does constant change (at all levels of a telco business) hold us back from reaching our aim of closed-loop / zero-touch assurance?

Just like the proverbial self-driving car, will we always need someone at the wheel of our OSS just in case a situation arises that the machines hasn’t seen before and/or can’t handle? How far into the future will it be before we have enough trust to take our hands off the OSS wheel and let the machines drive closed-loop processes without observation by us?

The OSS Ferrari analogy

A friend and colleague has recently been talking about a Ferrari analogy on a security project we’ve been contributing to.

The end customers have decided they want a Ferrari solution, a shiny new, super-specified new toy (or in this case toys!). There’s just one problem though. The customer has a general understanding of what it is to drive, but doesn’t have driving experience or a driver’s license yet (ie they have a general understanding of what they want but haven’t described what they plan to do with the shiny toys operationally once the keys are handed over).

To take a step further back, since the project hasn’t articulated exactly where the customers want to go with the solution, we’re asking whether a Ferrari is even the right type of vehicle to take them there. As amazing as Ferraris are, might it actually make more sense to buy a 4WD vehicle?

As indicated in yesterday’s post, sometimes the requirements gathering process identifies the goal-based expectations (ie the business requirements – where the customer wants to go), but can often just identify a set of product features (ie the functional requirements such as a turbo-charged V8 engine, mid-mount engine, flappy-paddle gear change, etc, etc). The latter leads to buying a Ferrari. The former is more likely to lead to buying the vehicle best-suited to getting to the desired destination.

The OSS Ferrari sounds nice, but…