Yesterday’s post talked about the difference between “flow state” and “office state” in relation to OSS delivery. It referenced a book I’m currently reading called Stealing Fire.
The post mainly focused on how the interruptions of “office state” actually inhibit our productivity, learning and ability to think laterally on our OSS. But that got me thinking that perhaps flow doesn’t just relate to OSS project delivery. It also relates to post-implementation use of the OSS we implement.
If we think about the various personas who use an OSS (such as NOC operators, designers, order entry operators, capacity planners, etc), do our user interfaces and workflows assist or inhibit them to get into the zone? More importantly, if those personas need to work collaboratively with others, do we facilitate them getting into “group flow?”
Stealing Fire suggests that it costs around $500k to train each Navy SEAL and around $4.25m to train each elite SEAL (DEVGRU). It also describes how this level of training allows DEVGRU units to quickly get into group flow and function together almost as if choreographed, even in high-pressure / high-noise environments.
Contrast this with collaborative activities within our OSS. We use tickets, emails, Slack notifications, work order activity lists, etc to collaborate. It seems to me that these are the precise instruments that prevent us from getting into flow individually. I assume it’s the same collectively. I can’t think back to any end-to-end OSS workflows that seem highly choreographed or seamlessly effective.
Think about it. If you experience significant rates of process fall-out / error, then it would seem to indicate an OSS that’s not conducive to group flow. Ditto for lengthy O2A (order to activate) or T2R (trouble to resolve) times. Ditto for bringing new products to market.
I’d love to hear your thoughts. Has any OSS environment you’ve worked in facilitated group flow? If so, was it the people and/or the tools? Alternatively, have the OSS you’ve used inhibited group flow?
PS. Stealing Fire details how organisations such as Google and DARPA are investing heavily in flow research. They can obviously see the pay-off from those investments (or potential pay-offs). We seem to barely even invest in UI/UX experts to assist with the designs of our OSS products and workflows.
Operators have developed many unique understandings of what impacts the health of their networks.
For example, mobile operators know that they have faster maintenance cycles in coastal areas than they do in warm, dry areas (yes, due to rust). Other operators have a high percentage of faults that are power-related. Others are impacted by failures caused by lightning strikes.
Near-real-time weather pattern and lightning strike data is now readily accessible, potentially for use by our OSS.
I was just speaking with one such operator last week who said, “We looked at it [using lightning strike data] but we ended up jumping at shadows most of the time. We actually started… looking for DSLAM alarms which will show us clumps of power failures and strikes, then we investigate those clumps and determine a cause. Sometimes we send out a single truck to collect artifacts, photos of lightning damage to cables, etc.”
That discussion got me wondering about what other lateral approaches are used by operators to assure their networks. For example:
What external data sources do you use (eg meteorology, lightning strike, power feed data from power suppliers or sensors, sensor networks, etc)
Do you use it in proactive or reactive mode (eg to diagnose a fault or to use engineering techniques to prevent faults)
Have you built algorithms (eg root-cause, predictive maintenance, etc) to utilise your external data sources
If so, do those algorithms help establish automated closed-loop detect and response cycles
By measuring and managing, has it created quantifiable improvements in your network health
I’d love to hear about your clever and unique insight-generation ideas. Or even the ideas you’ve proposed that haven’t been built yet.
TM Forum’s Open Digital Architecture (ODA) White Paper begins with the following statement:
Telecoms is at a crucial turning point. The last decade has dealt a series of punishing blows to an industry that had previously enjoyed enviable growth for more than 20 years. Services that once returned high margins are being reduced to commodities in the digital world, and our insatiable appetite for data demands continuous investment in infrastructure. On the other hand, communications service providers (CSPs) and their partners are in an excellent position to guide and capitalize on the next wave of digital revolution.
Clearly, a reduction in profitability leads to a reduction in cash available for projects – including OSS transformation projects. And reduced profitability almost inevitably leads executives to start thinking about head-count reduction too.
As Luke Clifton of Macquarie Telecom observed here, “Telstra is reportedly planning to shed 1,200 people from its enterprise business with many of these people directly involved in managing small-to-medium sized business customers. More than 10,000 customers in this segment will no longer have access to dedicated Account Managers, instead relegated to being managed by Telstra’s “Digital Hub”… Telstra, like the big banks once did, is seemingly betting that customers won’t leave them nor will they notice the downgrade in their service. It will be interesting to see how 10,000 additional organisations will be managed through a Digital Hub.
Simply put, you cannot cut quality people without cutting the quality of service. Those two ideals are intrinsically linked…”
As a fairly broad trend across the telco sector, projects and jobs are being cut, whilst technology change is forcing transformation. And as suggested in Luke’s “Digital Hub” quote above, it all leads to increased expectations on our OSS/BSS.
Pressure is coming at our OSS from all angles, and with no signs of abating.
To quote Queen, “Pressure. Pushing down on me.Pressing down on you.”
So it seems to me there are only three broad options when planning our OSS roadmaps:
We learn to cope with increased pressure (although this doesn’t seem like a viable long-term option)
We reduce the size (eg functionality, transaction volumes, etc) of our OSS footprint [But have you noticed that all of our roadmaps seem expansionary in terms of functionality, volumes, technologies incorporated, etc??]
We look beyond the realms of traditional OSS/BSS functionality (eg just servicing operations) and into areas of opportunity
TM Forum’s ODA White Paper goes on to state, “The growth opportunities attached to new 5G ecosystems are estimated to be worth over $580 billion in the next decade. Servicing these opportunities requires transformation of the entire industry. Early digital transformation efforts focused on improving customer experience and embracing new technologies such as virtualization, with promises of wide-scale automation and greater agility. It has become clear that these ‘projects’ alone are not enough. CSPs’ business and operating models, choice of technology partners, mindset, decision-making and time to market must also change. True digital business transformation is not an easy or quick path, but it is essential to surviving and thriving in the future digital market.”
BTW. I’m not suggesting 5G is the panacea or single opportunity here. My use of the quote above is drawing more heavily on the opportunities relating to digital transformation. Not of the telcos themselves, but digital transformation of their customers. If data is the oil of the 21st century, then our OSS/BSS and telco assets have the potential to be the miners and pipelines of that oil.
If / when our OSS go from being cost centres to revenue generators (directly attributable to revenue, not the indirect attribution by most OSS today), then we might feel some of the pressure easing off us.
Fault / Alarm management tools have lots of strings to their functionality bows to help operators focus in on the target/s that matter most. ITU-T’s recommendation X.733 provided an early framework and common model for classification of alarms. This allowed OSS vendors to build a standardised set of filters (eg severity, probable cause, etc). ITU-T’s recommendation M.3703 then provided a set of guiding use cases for managing alarms. These recommendations have been around since the 1990’s (or possibly even before).
Despite these “noise reduction” tools being readily available, they’re still not “compressing” event lists enough in all cases.
I imagine, like me, you’ve heard many customer stories where so many new events are appearing in an event list each day that the NOC (network operations centre) just can’t keep up. Dozens of new events are appearing on the screen, then scrolling off the bottom of it before an operator has even had a chance to stop and think about a resolution.
So if humans can’t keep up with the volume, we need to empower machines with their faster processing capabilities to do the job. But to do so, we first have to take a step away from the noise and help build a systematic root-cause analysis (RCA) pipeline.
I call it a pipeline because there are generally a lot of RCA rules that are required. There are a few general RCA rules that can be applied “out of the box” on a generic network, but most need to be specifically crafted to each network.
So here’s a step-by-step guide to build your RCA pipeline:
Scope – Identify your initial target / scope. For example, what are you seeking to prioritise:
Event volume reduction to give the NOC breathing space to function better
Identifying “most important” events (but defining what is most important)
Minimising SLA breaches
Gather Data – Gather incident and ticket data. Your OSS is probably already doing this, but you may need to pull data together from various sources (eg alarms/events, performance, tickets, external sources like weather data, etc)
Pattern Identification – Pattern identification and categorisation of incidents. This generally requires a pattern identification tool, ideally supplied by your alarm management and/or analytics supplier
Prioritise – Using a long-tail graph like below, prioritise pattern groups by the following (and in line with item #1 above):
Number of instances of the pattern / group (ie frequency)
Priority of instances (ie urgency of resolution)
Number of linked incidents (ie volume)
Other technique, such as a cumulative/blended metric
Gather Resolution Knowledge – Understand current NOC approaches to fault-identification and triage, as well as what’s important to them (noting that they may have biases such as managing to vanity metrics)
Note any Existing Resolutions – Identify and categorise any existing resolutions and/or RCA rules (if data supports this)
Short-list Remaining Patterns – Overlay resolution pattern on long-tail (to show which patterns are already solved for). then identify remaining priority patterns on the long-tail that don’t have a resolution yet.
Codify Patterns – Progressively set out to identify possible root-cause by analysing cause-effect such as:
Other (as helped to be defined by NOC operators)
Knowledge base – Create a knowledge base that itemises root-causes and supporting information
Build Algorithm / Automation – Create an algorithm for identifying root-cause and related alarms. Identify level of complexity, risks, unknowns, likelihood, control/monitoring plan for post-install, etc. Then build pilot algorithm (and possibly roll-back technique??). This might not just be an RCA rule, but could also include other automations. Automations could include creating a common problem and linking all events (not just root cause event but all related events), escalations, triggering automated workflows, etc
Test pilot algorithm (with analytics??)
Introduce algorithm into production use – But continue to monitor what’s being suppressed to
Repeat – Then repeat from steps 7 to 12 to codify the next most important pattern
Leading metrics – Identify leading metrics and/or preventative measures that could precede the RCA rule. Establish closed-loop automated resolution
Note that this mapping is just my demarc interpretation, but isn’t the definitive guide. It’s definitely open to differing opinions (ie religious wars).
Many of you will be familiar with the framework that the mapping is overlaid onto – TM Forum’s TAM (The Application Map). Version R17.5.1 in this case. It is as close as we get to a standard mapping of OSS/BSS functionality modules. I find it to be a really useful guide, so today’s article is going to call on the TAM again.
As you would’ve noticed in the diagram above, there are many, many modules that make up the complete OSS/BSS estate. And you should note that the diagram above only includes Level 2 mapping. The TAM recommendation gets a lot more granular than this. This level of granularity can be really important for large, complex telcos.
For the OSS/BSS that support smaller telcos, network providers or utilities, this might be overkill. Similarly, there are OSS/BSS vendors that want to cover all or large parts of the entire estate for these types of customers. But as you’d expect, they don’t want to provide the same depth of functionality coverage that the big telcos might need.
As such, I thought I’d provide the cut-down TAM mapping below for those who want a less complex OSS/BSS suite.
It’s a really subjective mapping because each telco, provider or vendor will have their own perspective on mandatory features or modules. Hopefully it provides a useful starting point for planning a low complexity OSS/BSS.
Then what high-level functionality goes into these building blocks? That’s possibly even more subjective, but here are some hints:
One of the benefits of virtualisation or NaaS (Network as a Service) is that it provides a layer of programmability to your network. That is, to be able to instantiate network services by software through a network API. Virtualisation also tends to assume/imply that there is a huge amount of available capacity (the resource pool) that it can shift workloads between. If one virtual service instance dies or deteriorates, then just automatically spin up another. If one route goes down, customer services are automatically re-directed via alternate routes and the service is maintained. No problem…
But there are some problems that can’t be solved in software. You can’t just use software to fix a cable that’s been cut by an excavator. You can’t just use software to fix failed electronics. Modern virtualised networks can do a great job of self-healing, routing around the problem areas. But there are still physical failures that need to be repaired / replaced / maintained by a field workforce. NSA doesn’t tend to cover that.
Looking at the diagram below, NSA does a great job of the closed-loop assurance within the red circle. But it then needs to kick out to the green closed-loop assurance processes that are already driven by our OSS/BSS.
As described in the link above, “Perhaps if the NSA was just assuring the yellow cloud/s, any time it identifies any physical degradation / failure in the resource pool, it kicks a notification up to the Customer Service Assurance (CSA) tools in the OSS/BSS layers? The OSS/BSS would then coordinate 1) any required customer notifications and 2) any truck rolls or fixes that can’t be achieved programmatically; just like it already does today. The additional benefit of this two-tiered assurance approach is that NSA can handle the NFV / VNF world, whilst not trying to replicate the enormous effort that’s already been invested into the CSA (ie the existing OSS/BSS assurance stack that looks after PNFs, other physical resources and the field workforce processes that look after it all).”
Therefore, a key part of the NSA process is how it kicks up from closed-loop 1 to closed-loop 2. Then, after closed-loop 2 has repaired the physical problem, NSA needs to be aware that the repaired resource is now back in the pool of available resources. Does your NSA automatically notice this, or must it receive a notification from closed loop 2?
It could be as simple as NSA sending alarms into the alarm list with a clearly articulate root-cause. The alarm has a ticket/s raised against it. The ticket triggers the field workforce to rectify it and the triggers customer assurance teams/tools to send notifications to impacted customers (if indeed they send notifications to customers who may not actually be effected yet due to the resilience measures that have kicked in). Standard OSS/BSS practice!
I spent some time with a client going through their OSS/BSS yesterday. They’re an Australian telco with a primarily home-grown, browser-based OSS/BSS. One of its features was something I’ve never seen in an OSS/BSS before. But really quite subtle and cool.
They have four tiers of users:
Super-admins (the carrier’s in-house admins),
Standard (their in-house users),
Partners (they use many channel partners to sell their services),
Customer (the end-users of the carrier’s services).
All users have access to the same OSS/BSS, but just with different levels of functionality / visibility, of course.
Anyway, the feature that I thought was really cool was that the super-admins have access to what they call the masquerade function. It allows them to masquerade as any other user on the system without having to log-out / login to other accounts. This allows them to see exactly what each user is seeing and experience exactly what they’re experiencing (notwithstanding any platform or network access differences such as different browsers, response times, etc).
This is clearly helpful for issue resolution, but I feel it’s even more helpful for design, feature release and testing across different personas.
In my experience at least, OSS/BSS builders tend to focus on a primary persona (eg the end-user) and can overlook multi-persona design and testing. The masquerade function can make this task easier.
Network slicing allows operators to segment their network and configure each different slice to the specific needs of that customer (or group of customers). So rather than the network infrastructure being configured for the best compromise that suits all use-cases, instead each slice can be configured optimally for each use-case. That’s an exciting concept.
The big potential roadblock however, falls almost entirely on our OSS/BSS. If our operational tools require significant manual intervention on just one network now, then what chance do operators have of efficiently looking after many networks (ie all the slices).
But something just dawned on me today. I was assuming that the onus for managing each slice would fall on the network operator. What if we take the approach that telcos use with security on network pipes instead? That is, the telco shifts the onus of security onto their customer (in most cases). They provide a dumb pipe and ask the customer to manage their own security mechanisms (eg firewalls) on the end.
In the case of network slicing, operators just provide “dumb slices.” The operator assumes responsibility for providing the network resource pool (VNFs – Virtual Network Functions) and the automation of slice management including fulfilment (ie adds, modifies, deletes, holds, etc) and assurance. But the customers take responsibility for actually managing their network (slice) with their own OSS/BSS (which they probably already have a suite of anyway).
This approach doesn’t seem to require the same level of sophistication. The main impacts I see (and I’m probably overlooking plenty of others) are:
There’s a new class of OSS/BSS required by the operators, that of automated slice management
The customers already have their own OSS/BSS, but they currently tend to focus on monitoring, ticketing, escalations, etc. Their new customer OSS/BSS would need to take more responsibility for provisioning, including traffic engineering
And I’d expect that to support customer-driven provisioning, the operators would probably need to provide ways for customers to programmatically interface with the network resources that make up their slice. That is, operators would need to offer network APIs or NaaS to their customers externally, not just for internal purposes
Determining the optimal slice model. For example, does the carrier offer:
A small number of slice types (eg video, IoT low latency, IoT low chat, etc), where each slice caters for a category of customers, but with many slice instances (one for each customer)
A small number of slice instances, where all customers in that category share the single slice
Customised slices for premium customers
A mix of the above
.In the meantime, changes could be made as they have in the past, via customer portals, etc.
Back in the old days, Network Service Assurance probably had a different meaning than it might today.
Clearly it’s assurance of a network service. That’s fairly obvious. But it’s in the definition of “network service” where the old and new terminologies have the potential to diverge.
In years past, telco networks were “nailed up” and network functions were physical appliances. I would’ve implied (probably incorrectly, but bear with me) that a “network service” was “owned” by the carrier and was something like a bearer circuit (as distinct from a customer service or customer circuit). Those bearer circuits, using protocols such as in DWDM, SDH, SONET, ATM, etc potentially carried lots of customer circuits so they were definitely worth assuring. And in those nailed-up networks, we knew exactly which network appliances / resources / bearers were being utilised. This simplified service impact analysis (SIA) and allowed targeted fault-fix.
In those networks the OSS/BSS was generally able to establish a clear line of association from customer service to physical resources as per the TMN pyramid below. Yes, some abstraction happened as information permeated up the stack, but awareness of connectivity and resource utilisation was generally retained end-to-end (E2E).
But in the more modern computer or virtualised network, it all goes a bit haywire, perhaps starting right back at the definition of a network service.
The modern “network service” is more aligned to ETSI’s NFV definition – “a composition of network functions and defined by its functional and behavioral specification. The Network Service contributes to the behaviour of the higher layer service, which is characterised by at least performance, dependability, and security specifications. The end-to-end network service behaviour is the result of a combination of the individual network function behaviours as well as the behaviours of the network infrastructure composition mechanism.”
They are applications running at OSI’s application layer that can be consumed by other applications. These network services include DNS, DHCP, VoIP, etc, but the concept of NaaS (Network as a Service) expands the possibilities further.
So now the customer services at the top of the pyramid (BSS / BML) are quite separated from the resources at the physical layer, other than to say the customer services consume from a pool of resources (the yellow cloud below). Assurance becomes more disconnected as a result.
OSS/BSS are able to tie customer services to pools of resources (the yellow cloud). And OSS/BSS tools also include PNI / WFM (Physical Network Inventory / Workforce Management) to manage the bottom, physical layer. But now there’s potentially an opaque gulf in the middle where virtualisation / NaaS exists.
The end-to-end association between customer services and the physical resources that carry them is lost. Unless we can find a way to establish E2E association, we just have to hope that our modern Network Service Assurance (NSA) tools make the yellow cloud robust to the point of infallibility. BTW. If the yellow cloud includes NaaS, then the NSA has to assure the NaaS gateway, catalog and all services instantiated through the gateway.
But as we know, there will always be failures in physical infrastructure (cable cuts, electronic malfunctions, etc). The individual resources can’t afford to be infallible, even if the resource pool seeks to provide collective resiliency.
Modern NSA has to find a way to manage the resource pool but also coordinate fault-fix in the physical resources that underpin it like the OSS used to do (still do??). They have to do more than just build policies and actions to ensure SLAs don’t they? They can seek to manage security, power, performance, utilisation and more. Unfortunately, not everything can be fixed programmatically, although that is a great place for NSA to start.
Perhaps if the NSA was just assuring the yellow cloud, any time it identifies any physical degradation / failure in the resource pool, it kicks a notification up to the Customer Service Assurance (CSA) tools in the OSS/BSS layers? The OSS/BSS would then coordinate 1) any required customer notifications and 2) any truck rolls or fixes that can’t be achieved programmatically; just like it already does today. The additional benefit of this two-tiered assurance approach is that NSA can handle the NFV / VNF world, whilst not trying to replicate the enormous effort that’s already been invested into the CSA (ie the existing OSS/BSS assurance stack that looks after PNFs, other physical resources and the field workforce processes that look after it all).
I’d love to hear your thoughts. Hopefully you can even correct me if/where I’m wrong.
I’d like to introduce the concept of CT/IR – Continual Test / Incremental Resilience. Analogous to CI/CD (Continuous Integration / Continuous Delivery) before it, CT/IR is a method to systematically and programmatically test the resilience of the network, then ensuring resilience is continually improving.
The continual, incremental improvement in resiliency potentially comes via multiple feedback loops:
Ideally, the existing resilience mechanisms work around or overcome any degradation or failure in the network
The continual triggering of faults into the network will provide additional seed data for AI/ML tools to learn from and improve upon, especially root-cause analysis (noting that in the case of CT/IR, the root-cause is certain – we KNOW the cause – because we triggered it – rather than reverse engineering what the cause may have been)
We can program the network to overcome the problem (eg turn up extra capacity, re-engineer traffic flows, change configurations, etc). Having the NaaS that we spoke about yesterday, provides greater programmability for the network by the way.
We can implement systematic programs / projects to fix endemic faults or weak spots in the network *
Perform regression tests to constantly stress-test the network as it evolves through network augmentation, new device types, etc
Now, you may argue that no carrier in their right mind will allow intentional faults to be triggered. So that’s where we unleash the chaos monkeys on our digital twin technology and/or PSUP (Production Support) environments at first. Then on our prod network if we develop enough trust in it.
I live in Australia, which suffers from severe bushfires every summer. Our fire-fighters spend a lot of time back-burning during the cooler months to reduce flammable material and therefore the severity of summer fires. Occasionally the back-burns get out of control, causing problems. But they’re still done for the greater good. The same principle could apply to unleashing chaos monkeys on a production network… once you’re confident in your ability to control the problems that might follow.
* When I say network, I’m also referring to the physical and logical network, but also support functions such as EMS (Element Management Systems), NCM (Network Configuration Management tools), backup/restore mechanisms, service order replay processes in the event of an outage, OSS/BSS, NaaS, etc.
As the title suggests above, NaaS has the potential to be as big a paradigm shift for networks (and OSS/BSS) as Agile has been for software development.
There are many facets to the Agile story, but for me one of the most important aspects is that it has taken end-to-end (E2E), monolithic thinking and has modularised it. Agile has broken software down into pieces that can be worked on by smaller, more autonomous teams than the methods used prior to it.
The same monolithic, E2E approach pervades the network space currently. If a network operator wants to add a new network type or a new product type/bundle, large project teams must be stood up. And these project teams must tackle E2E complexity, especially across an IT stack that is already a spaghetti of interactions.
But before I dive into the merits of NaaS, let me take you back a few steps, back into the past. Actually, for many operators, it’s not the past, but the current-day model.
As per the orange arrow, customers of all types (Retail, Enterprise and Wholesale) interact with their network operator through BSS (and possibly OSS) tools. [As an aside, see this recent post for a “religious war” discussion on where BSS ends and OSS begins]. The customer engagement occurs (sometimes directly, sometimes indirectly) via BSS tools such as:
Order Entry, Order Management
Product Catalog (Product / Offer Management)
SLA (Service Level Agreement) Management
If the customer wants a new instance of an existing service, then all’s good with the current paradigm. Where things become more challenging is when significant changes occur (as reflected by the yellow arrows in the diagram above).
For example, if any of the following are introduced, there are end-to-end impacts. They necessitate E2E changes to the IT spaghetti and require formation of a project team that includes multiple business units (eg products, marketing, IT, networks, change management to support all the workers impacted by system/process change, etc)
A new product or product bundle is to be taken to market
An end-customer needs a custom offering (especially in the case of managed service offerings for large corporate / government customers)
A new network type is added into the network
System and / or process transformations occur in the IT stack
If we just narrow in on point 3 above, fundamental changes are happening in network technology stacks already. Network virtualisation (SDN/NFV) and 5G are currently generating large investments of time and money. They’re fundamental changes because they also change the shape of our traditional OSS/BSS/IT stacks, as follows.
We now not only have Physical Network Functions (PNF) to manage, but Virtual Network Functions (VNF) as well. In fact it now becomes even more difficult because our IT stacks need to handle PNF and VNF concurrently. Each has their own nuances in terms of over-arching management.
The virtualisation of networks and application infrastructure means that our OSS see greater southbound abstraction. Greater southbound abstraction means we potentially lose E2E visibility of physical infrastructure. Yet we still need to manage E2E change to IT stacks for new products, network types, etc.
The diagram below shows how NaaS changes the paradigm. It de-couples the network service offerings from the network itself. Customer Facing Services (CFS) [as presented by BSS/OSS/NaaS] are de-coupled from Resource Facing Services (RFS) [as presented by the network / domains].
NaaS becomes a “meet-in-the-middle” tool. It effectively de-couples
The products / marketing teams (who generate customer offerings / bundles) from
The networks / operations teams (who design, build and maintain the network).and
The IT teams (who design, build and maintain the IT stack)
It allows product teams to be highly creative with their CFS offerings from the available RFS building blocks. Consider it like Lego. The network / ops teams create the building blocks and the products / marketing teams have huge scope for innovation. The products / marketing teams rarely need to ask for custom building blocks to be made.
You’ll notice that the entire stack shown in the diagram below is far more modular than the diagram above. Being modular makes the network stack more suited to being worked on by smaller autonomous teams. The yellow arrows indicate that modularity, both in terms of the IT stack and in terms of the teams that need to be stood up to make changes. Hence my claim that NaaS is to networks what Agile has been to software.
You will have also noted that NaaS allows the Network / Resource part of this stack to be broken into entirely separate network domains. Separation in terms of IT stacks, management and autonomy. It also allows new domains to be stood up independently, which accommodates the newer virtualised network domains (and their VNFs) as well as platforms such as ONAP.
The NaaS layer comprises:
A TMF standards-based API Gateway
A Master Services Catalog
A common / consistent framework of presentation of all domains
The ramifications of this excites me even more that what’s shown in the diagram above. By offering access to the network via APIs and as a catalog of services, it allows a large developer pool to provide innovative offerings to end customers (as shown in the green box below). It opens up the long tail of innovation that we discussed last week.
Some telcos will open up their NaaS to internal or partner developers. Others are drooling at the prospect of offering network APIs for consumption by the market.
You’ve probably already identified this, but the awesome thing for the developer community is that they can combine services/APIs not just from the telcos but any other third-party providers (eg Netflix, Amazon, Facebook, etc, etc, etc). I could’ve shown these as East-West services in the diagram but decided to keep it simpler.
Developers are not constrained to offering communications services. They can now create / offer higher-order services that also happen to have communications requirements.
If you weren’t already on board with the concept, hopefully this article has convinced you that NaaS will be to networks what Agile has been to software.
Agree or disagree? Leave me a comment below.
PS1. I’ve used the old TMN pyramid as the basis of the diagram to tie the discussion to legacy solutions, not to imply size or emphasis of any of the layers.
PS3. Similarly, the size of the NaaS layer is to bring attention to it rather than to imply it is a monolithic stack in it’s own right. In reality, it is actually a much thinner shim layer architecturally
PS4. The analogy between NaaS and Agile is to show similarities, not to imply that NaaS replaces Agile. They can definitely be used together
PS5. I’ve used the term IT quite generically (operationally and technically) just to keep the diagram and discussion as simple as possible. In reality, there are many sub-functions like data centre operations, application monitoring, application control, applications development, product owner, etc. These are split differently at each operator.
Back in the earliest days of OSS (and networks for that matter), it was the telcos that generated almost all of the innovation. That effectively limited innovation to being developed by the privileged few, those who worked for the government-owned, monopoly telcos.
But over time, the financial leaders at those telcos felt the costs of their amazing research and development labs outweighed the benefits and shut them down (or starved them at best). OSS (and network) vendors stepped into the void to assume responsibility for most of the innovation. But there was a dilemma for the vendors (and for telcos and consumers too) – they needed to innovate fast enough to win work against their competitors, but slow enough to accrue revenues from the investment in their earlier innovations. And innovation was still being constrained to the privileged few, those who worked for vendors and integrators.
Now, the telcos are increasingly pushing to innovate wider and faster than the current vendor collective can accommodate. It means we have to reach further out to the long-tail of innovators. To open the floor beyond the privileged few. Excitingly, this opportunity appears to be looming.
“How?” you may ask.
Network as a Service (NaaS) and API platform offerings.
If every telco offers consumption of their infrastructure via API, it provides the opportunity for any developer to bundle their own unique offering of products, services, applications, hosting, etc and take it to market. If you’re heading to TM Forum’s Digital Transformation World (DTW) in Nice next week, there are a number of Catalyst projects on display in this space, including:
The challenge for the telcos is in how to support the growth of this model. To foster the vendor market, it was easy enough for the telcos to identify the big suppliers and funnel projects (and funding) through them. But now they have to figure out a funnel that’s segmented at a much smaller scale – to facilitate take-up by the millions of developers globally who might consume their products (network APIs in this case) rather than the hundreds/thousands of large suppliers.
This brings us back to smart contracts and micro-procurement as well as the technologies such as blockchain that support these models. This ties in with another TM Forum initiative to revolutionise the procurement event:
But an additional benefit for the telcos, if and when the NaaS platform model takes hold, is that the developers also become a unpaid salesforce for the telcos. The developers will be responsible for marketing and selling their own bundles, which will drive consumption and revenues on the telcos’ assets.
Exciting new business models and supply chains are bound to evolve out of this long tail of innovation.
All OSS products are excellent these days. And all OSS vendors know what the most important functionality is. They already have those features built into their products. That is, they’ve already added the all-important features at the left side of the graph.
But it also means product teams are tending to only add the relatively unimportant new features to the right edge of the graph (ie inside the red box). Relatively unimportant and therefore delivering minimal differential advantage.
The challenge for users is that there is a huge amount of relatively worthless functionality that they have to navigate around. This tends to make the user interfaces non-intuitive.
But another approach, a product-led differentiator, dawned on me when discussing the many sources of OSS friction in yesterday’s post. What if we asked our product teams to take a focus on designing solutions that remove friction instead of the typical approach of adding features (and complexity)?
Almost every OSS I’m aware of has many areas of friction. It’s what gives the OSS industry a bad name. But what if one vendor reduced friction to levels far less than any other competitor? Would it be a differentiator? I’m quite certain customers would be lining up to buy a frictionless OSS even if it didn’t have every perceivable feature.
Network operators spend huge amounts on building and maintaining their OSS/BSS every year. There are many reasons they invest so heavily, but in most cases it can be distilled back to one thing – improving operational efficiency.
And our OSS/BSS definitely do improve operational efficiency, but there are still so many sources of friction. They’re squeaking like un-oiled bearings. Here are just a few of the common sources:
Identifying best-fit tools
Procurement of new tools
Update / release processes
Continuous data quality / consistency improvement
Navigating to all features through the user interface
Non-intuitive functionality / processes
So many variants / complexity that end-users take years to attain expert-level capability
Integration / interconnect
Getting new starters up to speed
Getting proficient operators to expertise
Unlocking actionable insights from huge data piles
Resolving the root-cause of complex faults
Onboarding new customers
Productionising new functionality
Exception and fallout handling
Access to supplier expertise to resolve challenges
The list goes on far deeper than that list too. The challenge for many OSS product teams, for any number of reasons, is that their focus is on adding new features rather than reducing friction in what already exists.
The challenge for product teams is diagnosing where the friction and risks are for their customers / stakeholders. How do you get that feedback?
Every vendor has a product support team, so that’s a useful place to start, both in terms of what’s generating the most support calls and in terms of first-hand feedback from customers
Do you hold user forums on a regular basis, where you get many of your customers together to discuss their challenges, your future roadmap, new improvements / features
Does your process “flow” data show where the sticking points are for operators
Do you conduct gemba walks with your customers
Do you have a program of ensuring all developers spend at least a few days a year interacting directly with customers on their site/s
Do you observe areas of difficulty when delivering training
Do you go out of your way to ask your customers / stakeholders questions that are framed around their pain-points, not just framed within the context of your existing OSS
Do you conduct customer surveys? More importantly, do you conduct surveys through an independent third-party?
On the last dot-point, I’ve been surprised at some of the profound insights end-users have shared with me when I’ve been conducting these reviews as the independent interviewer. I’ve tended to find answers are more open / honest when being delivered to an independent third-party than if the supplier asks directly. If you’d like assistance running a third-party review, leave us a note on the contact page. We’d be delighted to assist.
One of the longer lead-time items in relation to OSS data and processes is in network build and customer connections. From the time when capacity planning or a customer order creates the signal to build, it can be many weeks or months before the physical infrastructure work is complete and appearing in the OSS.
There are two financial downsides to this. Firstly, it tends to be CAPEX-heavy with equipment, construction, truck-rolls, government approvals, etc burning through money. Meanwhile, it’s also a period where there is no money coming in because the services aren’t turned on yet. The time-to-cash cycle of new build (or augmentation) is the bane of all telcos.
This is one of the exciting aspects of network virtualisation for telcos. In a time where connectivity is nearly ubiquitous in most countries, often with high-speed broadband access, physical build becomes less essential (except over-builds). Technologies such as uCPE (Universal Customer Premises Equipment), NFV (Network Function Virtualisation), SD WAN (Software-Defined Wide Area Networks), SDN (Software Defined Networks) and others mean that we can remotely upgrade and reconfigure the network without field work.
Network virtualisation gives the potential to speed up many of the slowest, and costliest processes that run through our OSS… but only if our OSS can support efficient orchestration of virtualised networks. And that means having an OSS with the flexibility to easily change out slow processes to replace them with fast ones without massive overhauls.
The traditional telco (and OSS) ran at different speeds. Some tasks had to happen immediately (eg customers calling one another) while others took time (eg getting a connection to a customer’s home, which included designs, approvals, builds, etc), often weeks.
Our OSS have processes that must happen sequentially and expediently. They also have processes that must wait for dependencies, conditional events and time delays. Some roles need “fast,” others can cope with “slow.” Who wins out in this dilemma?
Even the data we rely on can transact at different speeds. For capacity planning, we’re generally interested in longer-term data. We don’t have to process at real-time. Therefore we can choose to batch process at longer cycle times and with summarised data sets. For network assurance, we’re generally interested in getting data as quick as is viable.
Today’s post is about that word, viable, and pragmatism we sometimes have to apply to our OSS.
For example, if our operations teams want to reduce network performance poll cycles from every 15 mins down to once a minute, we increase the amount of data to process by 15x. That means our data storage costs go up by 15x (assuming a flat-rate cost structure applies). The other hidden cost is that our compute and network costs also go up because we have to transfer and process 15x as much data.
The trade-off we have to make in responses to this rapid escalation of cost (when going from 15 to 1 min) is in the benefits we might derive. Can we avoid SLA (Service Level Agreement) breach costs? Can we avoid costly outages? Can we avoid damage to equipment? Can we reduce the risk of losing our carrier license?
The other question is whether our operators actually have the ability to respond to 15x as much data. Do we have enough people to respond at an increased cycle time? Do we have OSS tools that are capable of filtering what’s important and disregarding “background” activity? Do we have OSS tools that are capable of learning from every single metric (eg AI), at volumes the human brain could never cope with?
Does it make sense that we have a single platform for handling fast and slow processes? For example, do we use the same platform to process 1 minute-cycle performance data for long-term planning (batch-processed once daily) and quick-fire assurance (processed as fast as possible)?
If we stick to one platform, can our OSS apply data reduction techniques (eg selective discard of records) to get the benefits of speed, but with the cost reduction of slow?
Well, would you hire a furniture maker as CEO of an OSS vendor?
At face value, it would seem to be an odd selection right? There doesn’t seem to be much commonality between furniture and OSS does there? It seems as likely as hiring a furniture maker to be CEO of a car maker?
Oh wait. That did happen.
Ford Motor Company made just such a decision last year when appointing Jim Hackett, a furniture industry veteran, as its CEO. Whether the appointment proves successful or not, it’s interesting that Ford made the decision. But why? To focus on user experience and design as it’s next big differentiator. Clever line of thinking Bill Ford!!
I’ve prepared a slightly light-hearted table for comparison purposes between cars and OSS. Both are worth comparing as they’re both complex feats of human engineering:
Transport passengers between destinations
Operationalise and monetise a comms network
Claimed “Business” justification
Reducing the cost of operations
Operation of common functionality without conscious thought (developed through years of operator practice)
Hmmm??? Depends on which sales person or operator you speak with
Error detection and current-state monitoring
Warning lights and instrument cluster/s
Alarm lists, performance graphs
Key differentiator for customers (1970’s)
Database / CPU size
Key differentiator for customers (2000’s)
Gadgets / functions / cup-holders
Key differentiator for customers (2020+)
Connected car (car as an “experience platform”)
Connected OSS (ie OSS as an experience platform)???
I’d like to focus on three key areas next:
Item 4 and
The transition between items 6 and 7
Item 3 – operating on auto-pilot
If we reference against item 1, the primary objective, experienced operators of cars can navigate from point A to point B with little conscious thought. Key activities such as steering, changing gears and Indicating can be done almost as a background task by our brains whilst doing other mental processing (talking, thinking, listening to podcasts, etc).
Experienced operators of OSS can do primary objectives quickly, but probably not on auto-pilot. There are too many “levers” to pull, too many decisions to make, too many options to choose from, for operators to background-process key OSS activities. The question is, could we re-architect to achieve key objectives more as background processing tasks?
Item 4 – error detection and monitoring
In a car, error detection is also a background task, where operators are rarely notified, only for critical alerts (eg engine light, fuel tank empty, etc). In an OSS, error detection is not a background task. We need full-time staff monitoring all the alarms and alerts popping up on our consoles! Sometimes they scroll off the page too fast for us to even contemplate.
In a car, monitoring is kept to the bare essentials (speedo, tacho, fuel guage, etc). In an OSS, we tend to be great at information overload – we have a billion graphs and are never sure which ones, or which thresholds, actually allow us to operate our “vehicle” effectively. So we show them all.
Transitioning from current to future-state differentiators
In cars, we’ve finally reached peak-cup-holders. Manufacturers know they can no longer differentiate from competitors just by having more cup-holders (at least, I think this claim is true). They’ve also realised that even entry-level cars have an astounding list of features that are only supplementary to the primary objective (see item 1). They now know it’s not the amount of functionality, but how seamlessly and intuitively the users interact with the vehicle on end-to-end tasks. The car is now seen as an extension of the user’s phone rather than vice versa, unlike the recent past.
In OSS, I’ve yet to see a single cup holder (apart from the old gag about CD trays). Vendors mark that down – cup holders could be a good differentiator. But seriously, I’m not sure if we realise the OSS arms race of features is no longer the differentiator. Intuitive end-to-end user experience can be a huge differentiator amongst the sea of complex designs, user interfaces and processes available currently. But nobody seems to be talking about this. Go to any OSS event and we only hear from engineers talking about features. Where are the UX experts talking about innovative new ways for users to interact with machines to achieve primary objectives (see item 1)?
But a functionality arms race isn’t a completely dead differentiator. In cars, there is a horizon of next-level features that can be true differentiators like self-driving or hover-cars. Likewise in OSS, incremental functionality increases aren’t differentiators. However, any vendor that can not just discuss, but can produce next-level capabilities like zero touch assurance (ZTA) and automated O2A (Order to Activate) will definitely hold a competitive advantage.
I’d hazard a guess that everyone reading this would admit to being a techie at some level. And being a techie, I’d also imagine that you have blatant tech-love for certain products – gadgets, apps, sites, whatever.
But, let me ask you, are there any OSS products on your love-interest list?
If yes, leave me a comment of “yes” and name of the product below.
If no, leave me a comment of “no” below.
I’m really interested and intrigued to see your answer.
There’s probably only one OSS that I’ve ever had a tech-crush on (but it’s no longer available on the market). It definitely wasn’t love at first sight. If I’m honest, it was probably the opposite. It was a love that took a long time to build. It had some cool modules, but generally it was a bit clunky. The real attraction was that the power and elegance of its data model allowed me to do almost anything with it. To build almost anything with it. To answer almost any business / network / operation question that I could dream up.
I wonder whether the same is true of your other tech-loves? Do they provide the platform for us to create/achieve things that we never dreamed we’d be able to?
If that’s true, I wonder then whether that’s one key to solving the header question?
I wonder whether the other key (the second authentication factor) is in the speed that a user can achieve the necessary level of expertise? Few users ever have the luxury that I had, spending every day for years, to establish the required expertise to make that OSS excel.
As Seth Godin says, “Make things better by making better things.”
PS. If you were kind enough to leave a Yes or No comment below, I’d also love to hear why in an additional comment.
A friend of mine has a great saying, “only do what only you can do.”
Do you think that this holds true for the companies undergoing digital transformation? Banks are now IT companies. Insurers are IT companies. Car manufacturers are now IT companies. Telcos are, well, some are IT companies.
We’ve spoken before about the skill transformations that need to happen within telcos if they’re to become IT companies. Some are actively helping their workforce to become more developer-centric. Some of the big telcos that I’ve been assisting in the last few years are embarking on bold Agile-led IT transformations. They’re cutting more of their own code and managing their own IT developments.
That’s exciting news for all of us in OSS. Even if it loses the name OSS in future, telcos will still need software that efficiently operationalises their networks. We have the overlapping skills in software, networks, business and operations.
But I wonder about the longevity of the in-house approach unless we come focus clearly on the first quote above. If all development is brought in-house, we end up with a lot of duplication across the industry. I’m not really sure that it makes sense doing all the heavy-lifting of all custom OSS tools when the heavy-lifting has already been done elsewhere.
In my very humble opinion, it’s not just a choice between in-house and outsourced that matters. The more important decisions are around choosing to only develop the tools in-house that only you can do (ie the strategic differentiators).
Is your OSS a single pane of glass, or a single glass of pain?
You can tell I’m being a little flippant here. People often (perhaps idealistically) talk about OSS as being the single pane of glass (SPOG) to manage a network.
I say “idealistically” for a couple of reasons:
There are usually many personas who interact with an OSS, each with vastly different user interface (UI) needs
There is usually more than one OSS product in a client’s OSS suite, often from different vendors, with varying levels of integration
Where a single pane of glass can be a true ambition is as a consolidated health-status dashboard / portal, Invariably, this portal is used by executive / leader / manager personas who want to quickly see a single-screen health status that covers all networks and/or parts of the OSS suite. When things go wrong, this portal becomes the single glass of pain.
These single panes tend to be heavily customised for each organisation as every one has a unique set of metrics-that-matter. For those designing these panes, the key is to not just include vanity metrics, but to show information that the leader can action.
But the interesting perspective here is whether the single glass of pain is even relevant within your organisation’s culture. It’s just my opinion, but I prefer for coal-face workers to be empowered to make rapid recovery actions rather than requiring direction from up high in the org-chart. Coal-face workers generally have different tools with UIs that *should* help them monitor, manage and repair super-efficiently.
To get back to the “idealistic” comment above, each OSS UI needs to be fit-for-purpose for each unique persona (eg designers, product owners, network operations, etc). To me this implies that there is no single pane of glass…
I should caveat that by citing the example of an OSS search interface, something I’ve yet to see in OSS… although that’s just a front end to dozens of persona-specific panes of glass.