Expanding your bag of OSS tricks

Let me ask you a question – when you’ve expanded your bag of tricks that help you to manage your OSS, where have they typically originated?

By reading? By doing? By asking? Through mentoring? Via training courses?
Relating to technical? People? Process? Product?
Operations? Network? Hardware? Software?
Design? Procure? Implement / delivery? Test? Deploy?
By retrospective thinking? Creative thinking? Refinement thinking?
Other?

If you were to highlight the questions above that are most relevant to the development of your bag of tricks, how much coverage does your pattern show?

There are so many facets to our OSS (ie. tentacles on the OctopOSS) aren’t there? We have to have a large bag of tricks. Not only that, we need to be constantly adding new tricks too right?

I tend to find that our typical approaches to OSS knowledge transfer cover only a small subset (think about discussion topics at OSS conferences that tend to just focus on the technical / architectural)… yet don’t align with how we (or maybe just I) have developed capabilities in the past.

The question then becomes, how do we facilitate the broader learnings required to make our OSS great? To introduce learning opportunities for ourselves and our teams across vaguely related fields such as project management, change management, user interface design, process / workflows, creative thinking, etc, etc.

Zero touch network & Service Management (ZSM)

Zero touch network & Service Management (ZSM) is a next-gen network management approach using closed-loop principles hosted by ETSI. An ETSI blog has just demonstrated the first ZSM Proof of Concept (PoC). The slide deck describing the PoC, supplied by EnterpriseWeb, can be found here.

The diagram below shows a conceptual closed-loop assurance architecture used within the PoC
ETSI ZSM PoC.

It contains some similar concepts to a closed-loop traffic engineering project designed by PAOSS back in 2007, but with one big difference. That 2007 project was based on a single-vendor solution, as opposed to the open, multi-vendor PoC demonstrated here. Both were based on the principle of using assurance monitors to trigger fulfillment responses. For example, ours used SLA threshold breaches on voice switches to trigger automated remedial response through the OSS‘s provisioning engine.

For this newer example, ETSI’s blog details, “The PoC story relates to a congestion event caused by a DDoS (Denial of Service) attack that results in a decrease in the voice quality of a network service. The fault is detected by service monitoring within one or more domains and is shared with the end-to-end service orchestrator which correlates the alarms to interpret the events, based on metadata and metrics, and classifies the SLA violations. The end-to-end service orchestrator makes policy-based decisions which trigger commands back to the domain(s) for remediation.”

You’ll notice one of the key call-outs in the diagram above is real-time inventory. That was much harder for us to achieve back in 2007 than it is now with virtualised network and compute layers providing real-time telemetry. We used inventory that was only auto-discovered once daily and had to build in error handling, whilst relying on over-provisioned physical infrastructure.

It’s exciting to see these types of projects being taken forward by ETSI, EnterpriseWeb, et al.

Network slicing, another OSS activity

One business customer, for example, may require ultra-reliable services, whereas other business customers may need ultra-high-bandwidth communication or extremely low latency. The 5G network needs to be designed to be able to offer a different mix of capabilities to meet all these diverse requirements at the same time.
From a functional point of view, the most logical approach is to build a set of dedicated networks each adapted to serve one type of business customer. These dedicated networks would permit the implementation of tailor-made functionality and network operation specific to the needs of each business customer, rather than a one-size-fits-all approach as witnessed in the current and previous mobile generations which would not be economically viable.
A much more efficient approach is to operate multiple dedicated networks on a common platform: this is effectively what “network slicing” allows. Network slicing is the embodiment of the concept of running multiple logical networks as virtually independent business operations on a common physical infrastructure in an efficient and economical way.
.”
GSMA’s Introduction to Network Slicing.

Engineering a network is one of compromises. There are many different optimisation levers to pull to engineer a set of network characteristics. In the traditional network, it was a case of pulling all the levers to find a middle-ground set of characteristics that supported all their service offerings.

QoS striping of traffic allowed for a level of differentiation of traffic handling, but the underlying network was still a balancing act of settings. Network virtualisation offers new opportunities. It allows unique segmentation via virtual networks, where each can be optimised for the specific use-cases of that network slice.

For years, I’ve been posing the concept of telco offerings being like electricity networks – that we don’t need so many service variants. I should note that this analogy is not quite right. We do have a few different types of “electricity” such as highly available (health monitoring), high-bandwidth (content streaming), extremely low latency (rapid reaction scenarios such as real-time sensor networks), etc.

Now what do we need to implement and manage all these network slices?? Oh that’s right, OSS! It’s our OSS that will help to efficiently coordinate all the slicing and dicing that’s coming our way… to optimise all the levers across all the different network slices!

The OSS co-op business model

A co-operative is a member-owned business structure with at least five members, all of whom have equal voting rights regardless of their level of involvement or investment. All members are expected to help run the cooperative.”
Small Business WA.

The co-op business model has fascinated me since doing some tech projects in the dairy industry in the deep distant past. The dairy co-ops empower collaboration of dairy farmers where the might of the collective outweighs that of each individually. As the collective, they’ve been able to establish massive processing plants, distribution lines, bargaining power, etc. The dairy co-ops are a sell-side collaboration.

By contrast open source projects like ONAP represent an interesting hybrid – part buy-side collaboration (ie the service providers acquiring software to run their organisations) and part sell-side (ie the vendors contributing code to the project alongside the service providers).

I’ve long been intrigued by the potential for a pure sell-side co-operative in OSS.

As we all know, the OSS market is highly fragmented (just look the number of vendors / products on this page), which means inefficiency because of the duplicated effort across vendors. A level of market efficiency comes from mergers and acquisitions. In addition, some comes from vendors forming partnerships to offer more complete solutions to a given customer requirement list.

But the key to a true sell-side OSS co-operative would be in the definition above – “at least five members.” Perhaps it’s an open-source project that brings them together. Perhaps it’s an extended partnership.

As Tom Nolle stated in an article that prompted the writing of today’s post, “On the vendor side, commoditization tends to force consolidation. A vendor who doesn’t have a nice market share has little to hope for but slow decline. A couple such vendors (like Infinera and Coriant, recently) can combine with the hope that the combination will be more survivable than the individual companies were likely to be. Consolidation weeds out industry inefficiencies like parallel costly operations structures, and so makes the remaining players stronger.

Imagine for a moment if instead of having developers spread across 100 alarm management tools, that same developer pool can take a consolidated 5 alarm management products forward? Do you think we’d get better, more innovative, more complete products faster?

Having said that, co-ops have their weaknesses too.

What do you think? Could such a model work? Would it be a disaster?

Orchestration looks a bit like provisioning

The following is the result of a survey question posed by TM Forum:
Number 1 Driver for Orchestration

I’m not sure how the numbers tally, but conceptually the graph above paints an interesting perspective of why orchestration is important. The graph indicates the why.

But in this case, for me, the why is the by-product of the how. The main attraction of orchestration models is in how we can achieve modularity. All of the business outcomes mentioned in the graph above will only be achievable as a result of modularity.

Put another way, rather than having the integration spaghetti of an “old-school” OSS / BSS stack, orchestration (and orchestration plans) potentially provides the ability to provide clearer demarcation and abstraction all the way from product design down into transactions that hit the network… not to mention the meet-in-the-middle points between business units.

Demarcation points support catalog items (perhaps as APIs / microservices with published contracts), allowing building-block design of products rather than involvement of (and disputes between) business units all down the line of product design. This facilitates the speed (34%) and services on demand (28%) objectives stated in the graph.

But I used the term “old-school” with intent above. The modularity mentioned above was already achieved in some older OSS too. The ability to carve up, sequence, prioritise and re-construct a stream of service orders was already achievable by some provisioning + workflow engines of the past.

The business outcomes remain the same now as they were then, but perhaps orchestration takes it to the next level.

There is no differentiation left in out-bundling competitors

In 1998 Berkshire Hathaway acquired a reinsurance company called General Re. “The only significant staff change that followed the merger was the elimination of General Re’s investment unit. Some 150 people had been in charge of deciding where to invest the company’s funds; they were replaced with just one individual – Warren Buffett.
Robert G. Hagstrom
in, “The Warren Buffett Way.”

Buffett was able to replace 150 people, and significantly outperform them, because they were conducting (relatively) small value, high volume transactions and he did the exact opposite.

Compare this with Gemini Waghmare’s thoughts on BSS, “It used to be that operators differentiated by pricing. Complex bundles, friends and family plans, rollover minutes and megabytes were used as ways to win over consumers. This drove significant investment into charging platforms and product catalogs. The internet economy runs on one-click purchases and a recurring flat rate. Roaming and overages are going away and transactional VOD (video on-demand) makes way for subscription VOD.
It’s not uncommon for operators to have 10,000 price plans while Netflix has three. Facebook and Google make billions of dollars without charging a cent.
Operators would do well to deprecate the value of their charging systems and invest instead in cloud and flat-rate billing with added focus on collecting, normalizing and monetizing user data. By simplifying subscription models with lightweight billing platforms, the scale and cost of BSS will drop dramatically. After all, there is no differentiation left in out-bundling competitors
,” quoted here on Inform. There are some brilliant insights in this link, so I recommend you taking a closer look BTW.

10,000+ pricing plans definitely sounds like the equivalent to General Re before Buffett arrived. Having only 3 pricing plans would be more like the Buffett approach, change the dynamic of BSS tools and the size of the teams that use them! Having only 3 pricing plans would certainly change the dynamic for OSS too. The number of variants we’d be asked to handle would diminish, making it much easier to build and operate our OSS. Due to all the down-stream inefficiencies, you could actually argue that there is only negative-differentiation left in out-bundling competitors.

As an aside… Interesting comment that, “Facebook and Google make billions of dollars without charging a cent.” I’d beg to differ. Whilst consumers of the service aren’t billed, advertisers certainly are, which I assume still needs a billing engine… one that probably has quite a bit of algorithmic complexity.

Shooting the OSS messenger

NPS, or Net Promoter Score, has become commonly used in the telecoms industry in recent years. In effect, it is a metric that measures friction in the business. If NPS is high, the business runs more smoothly. Customers are happy with the service and want to buy more of it. They’re happy with the service so they don’t need to contact the business. If NPS is low, it’s harder to make sales and there’s the additional cost of time dealing with customer complaints, etc (until the customer goes away of course).

NPS can be easy to measure via survey, but a little more challenging as a near-real-time metric. What if we used customer contacts (via all channels such as phone, IVR, email, website, live-chat, etc) as a measure of friction? But more importantly, how does any of this relate to OSS / BSS? We’ll get to that shortly (I hope).

BSS (billing, customer relationship management, etc) and OSS (service health, network performance, etc) tend to be the final touchpoints of a workflow before reaching a customer. When the millions of workflows through a carrier are completing without customer contact, then friction is low. When there are problems, calls go up and friction / inefficiency is also going up. When there are problems, the people (or systems) dealing with the calls (eg contact centre operators) tend to start with OSS / BSS tools and then work their way back up the funnel to identify the cause of friction and attempt to resolve it.

The problem is that the OSS / BSS tools are often seen as the culprit because that’s where the issue first becomes apparent. It’s easier to log an issue against the OSS than to keep tracking back to the real source of the problem. Many times, it’s a case of shooting the messenger. Not only that, but if we’re not actually identifying the source of the problem then it becomes systemic (ie the poor customer experience perpetuates).

Maybe there’s a case for us to get better at tracking the friction caused further upstream of our OSS / BSS and to give more granular investigative tools to the call takers. Even if we do, our OSS / BSS are still the ones delivering the message.

The OSS Matrix – the blue or the red pill?

OSS Matrix
OSS tend to be very good at presenting a current moment in time – the current configuration of the network, the health of the network, the activities underway.

Some (but not all) tend to struggle to cope with other moments in time – past and future.

Most have tools that project into the future for the purpose of capacity planning, such as link saturation estimation (based on projecting forward from historical trend-lines). Predictive analytics is a current buzz-word as research attempts to predict future events and mitigate for them now.

Most also have the ability to look into the past – to look at historical logs to give an indication of what happened previously. However, historical logs can be painful and tend towards forensic analysis. We can generally see who (or what) performed an action at a precise timestamp, but it’s not so easy to correlate the surrounding context in which that action occurred. They rarely present a fully-stitched view in the OSS GUI that shows the state of everything else around it at that snapshot in time past. At least, not to the same extent that the OSS GUI can stitch and present current state together.

But the scenario that I find most interesting is for the purpose of network build / maintenance planning. Sometimes these changes occur as isolated events, but are more commonly run as projects, often with phases or milestone states. For network designers, it’s important to differentiate between assets (eg cables, trenches, joints, equipment, ports, etc) that are already in production versus assets that are proposed for installation in the future.

And naturally those states cross over at cut-in points. The proposed new branch of the network needs to connect to the existing network at some time in the future. Designers need to see available capacity now (eg spare ports), but be able to predict with confidence that capacity will still be available for them in the future. That’s where the “reserved” status comes into play, which tends to work for physical assets (eg physical ports) but can be more challenging for logical concepts like link utilisation.

In large organisations, it can be even more challenging because there’s not just one augmentation project underway, but many. In some cases, there can be dependencies where one project relies on capacity that is being stood up by other future projects.

Not all of these projects / plans will make it into production (eg funding is cut or a more optimal design option is chosen), so there is also the challenge of deprecating planned projects. Capability is required to find whether any other future projects are dependent on this deprecated future project.

It can get incredibly challenging to develop this time/space matrix in OSS. If you’re a developer of OSS, the question becomes whether you want to take the blue or red pill.

OSS stepping stone or wet cement

Very often, what is meant to be a stepping stone turns out to be a slab of wet cement that will harden around your foot if you do not take the next step soon enough.”
Richelle E. Goodrich
.

Not sure about your parts of the world, but I’ve noticed the terms “tactical” (ie stepping stone solution) and “strategic” (ie long-term solution) entering the architectural vernacular here in Australia.

OSS seem to be full of tactical solutions. We’re always on a journey to somewhere else. I love that mindset – getting moving now, but still keeping the future in mind. There’s just one slight problem… how many times have we seen a tactical solution that was build years before? Perhaps it’s not actually a problem at all in some cases – the short-term fix is obviously “good enough” to have survived.

As a colleague insightfully pointed out last week – “if you create a tactical solution without also preparing a strategic solution, you don’t have a tactical solution, you have a solution.

When architecting your OSS solutions, do you find yourself more easily focussing on the tactical, the strategic, or is having an eye on both the essential part of your solution?

OSS – just in time rather than just in case

We all know that once installed, OSS tend to stay in place for many years. Too much effort to air-lift in. Too much effort to air-lift back out, especially if tightly integrated over time.

The monolithic COTS (off-the-shelf) tools of the past would generally be commissioned and customised during the initial implementation project, with occasional integrations thereafter. That meant we needed to plan out what functionality might be required in future years and ask for it to be implemented, just in case. Along with all the baked-in functionality that is never needed, and the just in case but possibly never used, we ended up with a lot of bloat in our OSS.

With the current approach of implementing core OSS building blocks, then utilising rapid release and microservice techniques, we have an ongoing enhancement train. This provides us with an opportunity to build just in time, to build only functionality that we know to be essential.

This has pluses and minuses. On the plus side, we have more opportunity to restrict delivery to only what’s needed. On the minus side, a just in time mindset can build a stop-gap culture rather than strategic, long-term thinking. It’s always good to have long-term thinkers / planners on the team to steer the rapid release implementations (and reductions / refactoring) and avoid a new cause of bloat.

An OSS doomsday scenario

If I start talking about doomsday scenarios where the global OSS job industry is decimated, most people will immediately jump to the conclusion that I’m predicting an artificial intelligence (AI) takeover. AI could have a role to play, but is not a key facet of the scenario I’m most worried about.
OSS doomsday scenario

You’d think that OSS would be quite a niche industry, but there must be thousands of OSS practitioners in my home town of Melbourne alone. That’s partly due to large projects currently being run in Australia by major telcos such as nbn, Telstra, SingTel-Optus and Vodafone, not to mention all the smaller operators. Some of these projects are likely to scale back in coming months / years, meaning less seats in a game of OSS musical chairs. But this isn’t the doomsday scenario I’m hinting at in the title either. There will still be many roles at the telcos and the vendors / integrators that support them.

There are hundreds of OSS vendors in the market now, with no single dominant player. It’s a really fragmented market that would appear to be ripe for M&A (mergers and acquisitions). Ripe for consolidation, but massive consolidation is still not the doomsday scenario because there would still be many OSS roles in that situation.

The doomsday scenario I’m talking about is one where only one OSS gains domination globally. But how?

Most traditional telcos have a local geographic footprint with partners/subsidiaries in other parts of the world, but are constrained by the costs and regulations of a wired or cellular footprint to be able to reach all corners of the globe. All that uniqueness currently leads to the diversity of OSS offerings we see today. The doomsday scenario arises if one single network operator usurps all the traditional telcos and their legacy network / OSS / BSS stacks in one technological fell swoop.

How could a disruption of that magnitude happen? I’m not going to predict, but a satellite constellation such as the one proposed by Starlink has some of the hallmarks of such a scenario. By using low-earth orbit (LEO) satellites (ie lower latency than geostationary satellite solutions), point-to-point laser interconnects between them and peering / caching of data in the sky, it could fundamentally change the world of communications and OSS.

It has global reach, no need for carrier interconnect (hence no complex contract negotiations or OSS/BSS integration for that matter), no complicated lead-in negotiations or reinstatements, no long-haul terrestrial or submarine cable systems. None of the traditional factors that cost so much time and money to get customers connected and keep them connected (only the complication of getting and keeping the constellation of birds in the sky – but we’ll put that to the side for now). It would be hard for traditional telcos to compete.

I’m not suggesting that Starlink can or will be THE ubiquitous global communications network. What if Google, AWS or Microsoft added this sort of capability to their strengths in hosting / data? Such a model introduces a new, consistent network stack without the telcos’ tech debt burdens discussed here. The streamlined network model means the variant tree is millions of times simpler. And if the variant tree is that much simpler, so is the operations model and so is the OSS… with one distinct contradiction. It would need to scale for billions of customers rather than millions and trillions of events.

You might be wondering about all the enterprise OSS. Won’t they survive? Probably not. Comms networks are generally just an important means-to-an-end for enterprises. If the one global network provider were to service every organisation with local or global WANs, as well as all the hosting they would need, and hosted zero-touch network operations like Google is already pre-empting, would organisation have a need to build or own an on-premises OSS?

One ubiquitous global network, with a single pared back but hyperscaled OSS, most likely purpose-built with self-healing and/or AI as core constructs (not afterthoughts / retrofits like for existing OSS). How many OSS roles would survive that doomsday scenario?

Do you have an alternative OSS doomsday scenario that you’d like to share?

Hat tip again to Jay Fenton for pointing out what Starlink has been up to.

Using OSS machine learning to predict backwards not forwards

There’s a lot of excitement about what machine-led decisioning can introduce into the world of network operations, and rightly so. Excitement about predictions, automation, efficiency, optimisation, zero-touch assurance, etc.

There are so many use-cases that disruptors are proposing to solve using Artificial Intelligence (AI), Machine Learning (ML) and the like. I might have even been guilty of proposing a few ideas here on the PAOSS blog – ideas like closed-loop OSS learning / optimisation of common processes, the use of Robotic Process Automation (RPA) to reduce swivel-chairing and a few more.

But have you ever noticed that most of these use-cases are forward-looking? That is, using past data to look into the future (eg predictions, improvements, etc). What if we took a slightly different approach and used past data to reconcile what we’ve just done?

AI and ML models tend to rely on lots of consistent data. OSS produce or collect lots of consistent data, so we get a big tick there. The only problem is that a lot of our manually created OSS data is riddled with inconsistency, due to nuances in the way that each worker performs workflows, data entry, etc as well as our own personal biases and perceptions.

For example, zero-touch automation has significant cachet at the moment. To achieve that, we need network health indicators (eg alarms, logs, performance metrics), but also a record of interventions that have (hopefully) improved on those indicators. If we have inconsistent or erroneous trouble-ticketing information, our AI is going to struggle to figure out the right response to automate. Network operations teams tend to want to fix problems quickly, get the ticketing data populated as fast as possible and move on to the next fault, even if that means creating inconsistent ticketing data.

So, to get back to looking backwards, a machine-learning use-case to consider today is to look at what an operator has solved, compare it to past resolutions and either validate the accuracy of their resolution data or even auto-populate fields based on the operator’s actions.

Hat tip to Jay Fenton for the idea seed for this post.

1.045 Trillion reasons to re-consider your OSS strategy

The global Internet of Things (IoT) market will be worth $1.1 trillion in revenue by 2025 as market value shifts from connectivity to platforms, applications and services. By that point, there will be more than 25 billion IoT connections (cellular and non-cellular), driven largely by growth in the industrial IoT market. The Asia Pacific region is forecast to become the largest global IoT region in terms of both connections and revenue.
Although connectivity revenue will grow over the period, it will only account for 5 per cent of the total IoT revenue opportunity by 2025, underscoring the need for operators to expand their capabilities beyond connectivity in order to capture a greater share of market value
.”
GSMA Intelligence
, referred to here.

Let’s look at these projected numbers. The GSMA Intelligence report forecasts only 5 cents in every dollar of IoT spend (of a $1.1T market opportunity) will be allocated to connectivity. That leaves $1.045T on the table if network operators just focus on connectivity.

Traditional OSS tend to focus on managing connectivity – less so on managing marketplaces, customer-facing platforms and applications. Does that headline number – $1.045T – provide you with an incentive to re-consider what your OSS manages and future use cases?

IoT OSS market opportunity

IoT requires slightly different OSS thinking:

  • Rather than integrating to a (relatively) small number of device types, IoT will have an almost infinite number of sensor types from a huge range of suppliers.
  • Rather than managing devices individually, their sheer volume means that devices will need to be increasingly managed in cohorts via policy controls.
  • Rather than a fairly narrow set of network-comms based services, functionality explodes into diverse areas like metering, vehicle fleets, health-care, manufacturing, asset controls, etc, etc so IoT controllers will need to be developed by a much longer-tail of suppliers (meaning open development platforms and/or scalable certification processes to integrate into the IoT controller platforms).
  • There are undoubtedly many, many additional differences.

Caveat: I haven’t evaluated the claims / numbers in the GSMA Intelligence report. This blog is just to prompt a thought-experiment around hypothetical projections.

The paint the fence automation analogy

There are so many actions that could be automated by / with / in our OSS. It can be hard to know where to start can’t it? One approach is to look at where the largest amounts of manual effort is being expended by operators. Another way is to employ the “paint the fence” analogy.

When envisaging fulfilment workflows, it’s easiest to picture actions that start with a customer and wipe down through the OSS / BSS stack.

When envisaging assurance workflows, it’s easiest to picture actions that start in the network and wipe up through the OSS / BSS stack.
Paint the fence OSS analogy

Of course there are exceptions to these rules, but to go a step further, wipe down = revenue, wipe up = costs. We want to optimise both through automation of course.

Like ensuring paint coverage when painting a fence, OSS automation has the potential to best improve Customer Experience coverage when we use brushstrokes down and up.

On the downstroke, it’s through faster service activations, quotes, response times, etc. On the upstroke, it’s through network reliability (downtime reduction), preventative maintenance, expedited notifications, etc.

You’ll notice that these are indicators that are favourable to the customers. I’m sure it won’t take much sluething to see the association to trailing metrics that are favourable to the network operators though right?

How economies of unscale change the OSS landscape

For more than a century, economies of scale made the corporation an ideal engine of business. But now, a flurry of important new technologies, accelerated by artificial intelligence (AI), is turning economies of scale inside out. Business in the century ahead will be driven by economies of unscale, in which the traditional competitive advantages of size are turned on their head.
Economies of unscale are enabled by two complementary market forces: the emergence of platforms and technologies that can be rented as needed. These developments have eroded the powerful inverse relationship between fixed costs and output that defined economies of scale. Now, small, unscaled companies can pursue niche markets and successfully challenge large companies that are weighed down by decades of investment in scale — in mass production, distribution, and marketing
.”
Hemant Taneja with Kevin Maney
in their Sloan Review article, “The End of Scale.”

There are two pathways I can envisage OSS playing a part in the economies of unscale indicated in the Sloan Review quote above.

The first is the changing way of working towards smaller, more nimble organisations, which includes increasing freelancing. There are already many modularised activities managed within an OSS, such as field work, designs, third-party service bundling, where unscale is potentially an advantage. OSS natively manages all these modules with existing tools, whether that’s ticketing, orchestration, provisioning, design, billing, contract management, etc.

Add smart contract management and John Reilly’s value fabric will undoubtedly increase in prevalence. John states that a value fabric is a mesh of interwoven, cooperating organizations and individuals, called parties, who directly or indirectly deliver value to customers. It gives the large, traditional network operators the chance to be more creative in their use of third parties when they look beyond their “Not Invented Here” syndrome of the past. It also provides the opportunity to develop innovative supply and procurement chains (meshes) that can generate strategic competitive advantage.

The second comes with an increasing openness to using third-party platforms and open-source OSS tools within operator environments. The OSS market is already highly fragmented, from multi-billion dollar companies (by market capitalisation) through to niche, even hobby, projects. However, there tended to be barriers to entry for the small or hobbyist OSS provider – they either couldn’t scale their infrastructure or they didn’t hold the credibility mandated by risk averse network operators.

As-a-Service platforms have changed the scale dynamic because they now allow OSS developers to rent infrastructure on a pay-as-you-eat model. In other words, the more their customers consume, the more infrastructure an OSS supplier can afford to rent from platforms such as AWS. More importantly, this become a possibility because operators are now increasingly open to renting third-party services on shared (but compartmentalised / virtualised) infrastructure. BTW. When I say “infrastructure” here, I’m not just talking about compute / network / storage but also virtualisation, containerisation, databases, AI, etc, etc.

Similarly, the credibility barrier-to-entry is being pulled down like the Berlin Wall as operators are increasingly investing in open-source projects. There are large open-source OSS projects / platforms being driven by the carriers themselves (eg ONAP, OpenStack, OPNFV, etc) that are accommodative of smaller plug-in modules. Unlike the proprietary, monolithic OSS/BSS stacks of the past, these platforms are designed with collaboration and integration being front-of-mind.

However, there’s an element of “potential” in these economies of unscale. Andreas Hegers likens open-source to the wild west, as many settlers seek to claim their patch of real-estate in an uncharted map. Andreas states further, “In theory, vendor interoperability from open source should be convenient — even harmonious — with innovations being shared like recipes. Unfortunately for many, the system has not lived up to this reality.”

Where do you sit on the potential of economies of unscale and open-source OSS?

Getting lost in the flow of OSS

The myth is that people play games because they want to avoid challenging work. The reality is, people play games to engage in well-designed, challenging work. The only thing they are avoiding is poorly designed work. In essence, we are replacing poorly designed work with work that provides a more meaningful challenge and offers a richer sense of progress.
And we should note at this point that just because something is a game, it doesn’t mean it’s good. As we’ll soon see, it can be argued that everything is a game. The difference is in the design.
Really good games have been ruthlessly play-tested and calibrated to the point where achieving a state of flow is almost guaranteed for many. Play-testing is just another word for iterative development, which is essentially the conducting of progressive experiments
.”
Dr Jason Fox
in his book, “The Game Changer.”

Reflect with me for a moment – when it comes to your OSS activities, in which situations do you consistently get into a state of flow?

For me, it’s in quite a few different scenarios, but one in particular stands out – building up a network model in an inventory management tool. This activity starts with building models / patterns of devices, services, connections, etc, then using the models to build a replica of the network, either manually or via data migration, within the inventory tool(s). I can lose complete track of time when doing this task. In fact I have almost every single time I’ve performed this task.

Whilst not being much of a gamer, I suspect it’s no coincidence that by far my favourite video game genre is empire-building strategy games like the Civilization series. Back in the old days, I could easily get lost in them for hours too. Could we draw a comparison from getting that same sense of achievement, seeing a network (of devices in OSS, of cities in the empire strategy games) grow rapidly as a result of your actions?

What about fans of first-person shooter games? I wonder whether they get into a state of flow on assurance activities, where they get to hunt down and annihilate every fault in their terrain?

What about fans of horse grooming and riding games? Well…. let’s not go there. 🙂

Anyway, enough of all these reflections and musings. I would like to share three concepts with you that relate to Dr Fox’s quote above:

  1. Gamification – I feel that there is MASSIVE scope for gamification of our OSS, but I’ve yet to hear of any OSS developers using game design principles
  2. Play-testing – How many OSS are you aware of that have been, “ruthlessly play-tested and calibrated?” In almost every OSS situation I’ve seen, as soon as functionality meets requirements, we stop and move on to the next feature. We don’t pause and try a few more variants to see which is most likely to result in a great design, refining the solution, “to the point where achieving a state of flow is almost guaranteed for many
  3. Richer Progress – How many of our end-to-end workflows are designed with, “a richer sense of progress” in mind? Feedback tends to come through retrospective reporting (if at all), rarely through the OSS game-play itself. Chances are that our end-to-end processes actually flow through multiple un-related applications, so it comes back to clever integration design to deliver more compelling feedback. We simply don’t use enough specialist creative designers in OSS

It’s all a bit lumpy

Being an OSS product supplier to telecom operators is a tough business. There is a constant stream of outgoings on developer costs, cost of sale, general overheads, etc. Unfortunately revenue streams are rarely so smooth. In fact, they tend to be decidedly lumpy – unpredictable (in terms of timelines when forecasting inflows years in advance) but large spikes of income stemming from customer implementations.

Not only that, but the risks are high due to the complexity and unknowns of OSS implementation projects as well as the lack of repeatability that was discussed in yesterday’s post.

Enduringly valuable businesses achieve their status through predictable, diversified, recurring (and preferably growing) revenue streams, so they need to be objectives of our OSS business models.

Annual maintenance fees (usually in the order of 20-22% of up-front list prices) is the most common recurring revenue model used by OSS product suppliers. Transaction-based pricing is another common model.

Cloud subscription (consumption) based models are also becoming more common, although there are always challenges around convincing carriers of the security and sovereignty of such important tools and data being hosted off-site.

I’m fascinated with the platform-plays, like Salesforce, which is a mushrooming form of the subscription model because there’s an ecosystem (or marketplace) of sellers contributing to transaction volumes. OSS and BSS are the perfect platform play but I haven’t seen any built around this style of revenue model yet. [Please let me know if I’ve missed any].

It has also been interesting to observe Cisco’s market success on the back of a perceived revenue shift towards more software and services.

Whenever considering alternate revenue models, I refer back to this great image from Ross Dawson:
Revenue Models
Do any apply to your OSS? Can any apply to your OSS?

Tomorrow we’ll discuss OSS professional services revenues and the contrasting mindset compared with products.

Using OSS/BSS to steer the ship

For network operators, our OSS and BSS touch most parts of the business. The network, and the services they carry, are core business so a majority of business units will be contributing to that core business. As such, our OSS and BSS provide many of the metrics used by those business units.

This is a privileged position to be in. We get to see what indicators are most important to the business, as well as the levers used to control those indicators. From this privileged position, we also get to see the aggregated impact of all these KPIs.

In your years of working on OSS / BSS, how many times have you seen key business indicators that are conflicting between business units? They generally become more apparent on cross-team projects where the objectives of one internal team directly conflict with the objectives of another internal team/s.

In theory, a KPI tree can be used to improve consistency and ensure all business units are pulling towards a common objective… [but what if, like most organisations, there are many objectives? Does that mean you have a KPI forest and the trees end up fighting for light?]

But here’s a thought… Have you ever seen an OSS/BSS suite with the ability to easily build KPI trees? I haven’t. I’ve seen thousands of standalone reports containing myriad indicators, but never a consolidated roll-up of metrics. I have seen a few products that show operational metrics rolled-up into a single dashboard, but not business metrics. They appear to have been designed to show an information hierarchy, but not necessarily with KPI trees in mind specifically.

What do you think? Does it make sense for us to offer KPI trees as base product functionality from our reporting modules? Would this functionality help our OSS/BSS add more value back into the businesses we support?

Have I got an OSS deal for you!?!

Tending to be a low-volume, high-customisation, high-uniqueness product, OSS has a significantly different selling proposition than most “box drop” products.

Can you imagine if OSS salespeople used any of these “great deal” propositions (as described by Gary Halbert)?
“I’m going out of business.”
“I just had a fire and I’m having a fire sale.”
“I’m crazy.” (all used car dealers)
“I owe taxes and I’ve got to raise money fast to pay them.”
“I’ve lost my lease and I’ve got to sell this merchandise right away before it gets thrown into the sheet.”
“I’ve got to make space for some new merchandise that is arriving soon so I will sell you what I have on hand real cheap.”

Did the image of an OSS salesperson saying any of those, especially the first, bring a smile to your face?

Anyway, Gary’s article also goes on to say, “…I wrote: “and if you can find a way to use it, you can dramatically increase your sales volume.”
Now, compare that to this: “and if you can find a way to use it, you can make yourself a bushel of money!”
Isn’t that a lot more powerful? You bet! The words “dramatically increase your sales volume” do not even begin to conjure up the visual imagery of “a bushel of money
.””

From what I’ve experienced on the client side of the buying equation, OSS selling propositions seem to be driven by functionality. I call it the functionality arms-race, where vendors compete on functionality rather than efficacy. In a way, it’s the “sales volume” variant mentioned by Gary above.

The other approach that does align more closely with the “bushel of money” variant is the cost-out discussion. It’s the, “if you implement this OSS, you’ll be able to reduce head-count in your operations team,” argument. That’s definitely important for any operator that sees their OSS as a cost-centre. However, it’s a “save a bushel of money” argument rather than the more powerful “make a bushel of money” argument.

In reply to a recent post, James Crawshaw of Light Reading wrote, “OSS/BSS represents around 2-3% of revenue and takes up around 10% of capex.” I initially read this as OSS/BSS contributing 2-3% of revenue (ie the higher the percentage the better). However, James clarified that our IT/OSS/BSS tend to consume 2-3% of revenue (ie the lower the percentage the better).

Can you imagine how these tiny wording/perspective differences could change the credibility of the whole OSS/BSS industry? As soon as our OSS make a bushel of money, then the selling proposition becomes a whole lot stronger.

The Goldilocks OSS story

We all know the story of Goldilocks and the Three Bears where Goldilocks chooses the option that’s not too heavy, not too light, but just right.

The same model applies to OSS – finding / building a solution that’s not too heavy, not too light, but just right. To be honest, we probably tend to veer towards the too heavy, especially over time. We put more complexity into our architectures, integrations and customisations… because we can… which end up burdening us and our solutions.

A perfect example is AT&T offering its ECOMP project (now part of the even bigger Linux Foundation Network Fund) up for open source in the hope that others would contribute and help mature it. As a fairytale analogy, it’s an admission that it’s too heavy even for one of the global heavyweights to handle by itself.

The ONAP Charter has some great plans including, “…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.”

These are fantastic ambitions to strive for, especially at the Pappa Bear end of the market. I have huge admiration for those who are creating and chasing bold OSS plans. But what about for the large majority of customers that fall into the Goldilocks category? Is our field of vision so heavy (ie so grand and so far into the future) that we’re missing the opportunity to solve the business problems of our customers and make a difference for them with lighter solutions today?

TM Forum’s Digital Transformation World is due to start in just over two weeks. It will be fascinating to see how many of the presentations and booths consider the Goldilocks requirements. There probably won’t be many because it’s just not as sexy a story as one that mentions heavy solutions like policy-driven orchestration, zero-touch automation, AI / ML / analytics, self-scaling / self-healing networks, etc.

[I should also note that I fall into the category of loving to listen to the heavy solutions too!! ]