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.
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
Let me start today with a question: Does your future OSS/BSS need to be drastically different to what it is today?
Please leave me a comment below, answering yes or no.
I’m going to take a guess that most OSS/BSS experts will answer yes to this question, that our future OSS/BSS will change significantly. It’s the reason I wrote the OSS Call for Innovation manifesto some time back. As great as our OSS/BSS are, there’s still so much need for improvement.
But big improvement needs big change. And big change is scary, as Tom Nolle points out:
“IT vendors, like most vendors, recognize that too much revolution doesn’t sell. You have to creep up on change, get buyers disconnected from the comfortable past and then get them to face not the ultimate future but a future that’s not too frightening.”
Do you feel like we’re already in the midst of a revolution? Cloud computing, web-scaling and virtualisation (of IT and networks) have been partly responsible for it. Agile and continuous integration/delivery models too.
The following diagram shows a “from the moon” level view of how I approach (almost) any new project.
The key to Tom’s quote above is in step 2. Just how far, or how ambitious, into the future are you projecting your required change? Do you even know what that future will look like? After all, the environment we’re operating within is changing so fast. That’s why Tom is suggesting that for many of us, step 2 is just a “creep up on it change.” The gap is essentially small.
The “creep up on it change” means just adding a few new relatively meaningless features at the end of the long tail of functionality. That’s because we’ve already had the most meaningful functionality in our OSS/BSS for decades (eg customer management, product / catalog management, service management, service activation, network / service health management, inventory / resource management, partner management, workforce management, etc). We’ve had the functionality, but that doesn’t mean we’ve perfected the cost or process efficiency of using it.
So let’s say we look at step 2 with a slightly different mindset. Let’s say we don’t try to add any new functionality. We lock that down to what we already have. Instead we do re-factoring and try to pull the efficiency levers, which means changes to:
Platforms (eg cloud computing, web-scaling and virtualisation as well as associated management applications)
Methodologies (eg Agile, DevOps, CI/CD, noting of course that they’re more than just methodologies, but also come with tools, etc)
Process (eg User Experience / User Interfaces [UX/UI], supply chain, business process re-invention, machine-led automations, etc)
It’s harder for most people to visualise what the Step 2 Future State looks like. And if it’s harder to envisage Step 2, how do we then move onto Steps 3 and 4 with confidence?
This is the challenge for OSS/BSS vendors, supplier, integrators and implementers. How do we, “get buyers disconnected from the comfortable past and then get them to face not the ultimate future but a future that’s not too frightening?” And I should point out, that it’s not just buyers we need to get disconnected from the comfortable past, but ourselves, myself definitely included.
In the context of OSS/BSS, DBA has multiple meanings but I think the most relevant is Death By Acronym (don’t worry all you Database Administrators out there, I haven’t forgotten about you). Our industry is awash with TLAs (Three-Letter Acronyms) that lead to DBA.
Having said that, today’s article is about four that are commonly used in relation to end to end workflows through our OSS/BSS stacks. They often traverse different products, possibly even multiple different vendors’ products. They are as follows:
P2O – Prospect to Order – This workflow operates across the boundary between the customer and the customer-facing staff at the service provider. It allows staff to check what products can be offered to a customer. This includes service qualification (SQ), feasibility checks, then design, assign and reserve resources.
O2A – Order to Activate – This workflow includes all activities to manage customer services across entire life-cycles. That is, not just the initial activation of a service, but in-flight changes during activation and post-activation changes as well
U2C – Usage to Cash – This workflow allows customers or staff to evaluate the usage or consumption of a service (or services) that has already been activated for a customer
T2R – Trouble to Resolve – This “workflow” is more like a bundle of workflows that relate to assuring health of the services (and the network that carries them). They can be categorised as reactive (ie a customer triggers a resolution workflow by flagging an issue to the service provider) or a proactive (ie the service provider identifies and issue, degradation or potential for issue and triggers a resolution workflow internally)
PS. I recently read a vendor document that described additional flows:- I2I (Idea to Implementation – service onboarding, through a catalog presumably), P2P (Plan to Production – resource provisioning) and O2S (Order to Service). There’s also C2M (Concept to Market), L2C (Lead to Cash) and I’m sure I’m forgetting a number of others. Are there any additional TLAs that I should be listing here to describe end-to-end workflows?
There’s a famous Zig Ziglar quote that goes something like, “You can have everything in life you want, if you will just help enough other people get what they want.”
You could safely assume that this was written for the individual reader, but there is some truth in it within the OSS context too. For the OSS designer, builder, integrator, does the statement “You can have everything in your OSS you want, if you will just help enough other people get what they want,” apply?
We often just think about the O in OSS – Operations people, when looking for who to help. But OSS/BSS has the ability to impact far wider than just the Ops team/s.
The halcyon days of OSS were probably in the 1990’s to early 2000’s when the term OSS/BSS was at its most sexy and exciting. The big telcos were excitedly spending hundreds of millions of dollars. Those projects were huge… and hugely complex… and hugely fun!
With that level of investment, there was the expectation that the OSS/BSS would help many people. And they did. But the lustre has come off somewhat since then. We’ve helped sooooo many people, but perhaps didn’t help enough people enough. Just speak with anybody involved with an OSS/BSS stack and you’ll hear hints of a large gap that exists between their current state and a desired future state.
Do you mind if I ask two questions?
When you reflect on your OSS activities, do you focus on the technology, the opportunities or the problems
Do you look at the local, day-to-day activities or the broader industry
I tend to find myself focusing on the problems – how to solve them within the daily context on customer challenges, but the broader industry problems when I take the time to reflect, such as writing these blogs.
The part I find interesting is that we still face most of the same problems today that we did back in the 1990’s-2000’s. The same source of risks. We’ve done a fantastic job of helping many people get what they want on their day-to-day activities (the incremental). We still haven’t cracked the big challenges though. That’s why I wrote the OSS Call for Innovation, to articulate what lays ahead of us.
It’s why I’m really excited about two of the concepts we’ve discussed this week:
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.
OSS projects are full of risks we all know it. OSS projects have “earned” a bad name because of all those risks. On the other side of that same coin, OSS projects disappoint, in part I suspect because stakeholders expect such big things from their resource investments.
Ask anyone familiar with OSS projects and you’ll be sure to hear a long list of failings.
For those less familiar with what an OSS project has in store for you, I’d like to share a list of the most common risks I’ve seen on OSS projects.
Most people working in the OSS industry are technology-centric, so they’ll tend to cite risks that relate to the tech. That’s where I used to focus attention too. Now technology risk definitely exists, but as you’ll see below, I tend to start by looking at other risk factors first these days.
Most common OSS project risks / issues:
Complexity (to be honest, this is probably more the root-cause / issue that manifests as many of the following risks). However, complexity across many aspects of OSS projects is one of the biggest problem sources
Change Management – OSS tend to introduce significant change to an organisation – operationally, organisationally, processes, training, etc. This is probably the most regularly underestimated component of any large OSS build
Stakeholder Support / Politics – Challenges appear on every single OSS project. They invariably need strong support from stakeholders and sponsors to clear a path through the biggest challenges. If the project’s leaders aren’t fully committed and in unison, the delivery teams will be heavily constrained
Ill-defined Scope – Over-scoping, scope omission and scope creep all represent risks to an OSS project. But scope is never perfectly defined or static, so scope management mechanisms need to be developed up-front rather than in-flight. Tying back to point 1 above, complexity minimisation should be a key element of scope planning. To hark back to my motto for OSS, “just because we can, doesn’t mean we should)
Financial and commercial – As with scope, it’s virtually impossible to plan an OSS project to perfection. There are always unknowns.These unknowns can directly impact the original estimates. Projects with blow-outs and no contingency for time or money increase pressure on point 3 (stakeholders/sponsors) to maintain their support
Client resource skills / availability – An OSS has to be built to the needs of a client. If the client is unable to provide resources to steer the implementation, then it’s unlikely for the client to get a solution that is perfectly adapted to the client’s needs. One challenge for the client is that their most valuable guides, those with the client’s tribal knowledge, are also generally in high demand by “business as usual” teams. It becomes a challenge to allocate enough of their time to guide the OSS delivery team. Another challenge is augmenting the team with the required skill-set when a project introduces new skill requirements
Communication – OSS projects aren’t built in a vacuum. They have many project contributors and even more end-users. There are many business units that touch an OSS/BSS, each with their own jargon and interpretations. For example, how many alternate uses of the term “service” can you think of? I think an important early-stage activity is to agree on and document naming conventions
Culture – Of the client team and/or project team. Culture contributes to (or detracts from) motivation, morale, resource turnover, etc, which can have an impact on the team’s ability to deliver
Design / Integration – Finally, a technology risk. This item is particularly relevant with complex projects, it can be difficult for all of the planned components to operate and integrate as planned. A commonly unrecognised risk relates to the viability of implementing a design. It’s common for an end-state design to be specified but with no way of navigating through a series of steps / phases and reach the end-state
Technology – Similar to the previous point, there are many technology risks relating to items such as quality, scalability, resiliency, security, supportability, obsolescence, interoperability, etc
There’s one thing you will have probably noticed about this list. Most of the risks are common to other projects, not just OSS projects. However, the risks do tend to amplify on OSS projects because of their inherent complexity.
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.
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.
OSS can be cumbersome at times. Making change can be difficult. We tend to build layers of protections around them and the networks we manage. I get that. Change can be risky (although the protections are often implemented because the OSS and/or network platforms might not be as robust as they could be).
Contrast this with the OSS we want to create. We want to create a platform for rapid innovation, the platform that helps us and our clients generate opportunities and advantages.
For us to build a platform that allows our customers (and their customers) to revolutionise their markets, we might have to consider whether the protective layers around our OSS that are stymying change. Things like firewall burns, change review boards, documentation, approvals, politics, individuals with a reticence to change, etc.
For example, Netflix takes a contrarian, whitelist approach to access by its engineers rather than a blacklist. It assumes that its engineers are professional enough to only use the tools that they need to get their tasks done. They enable their engineers to use commonly off-limits functionality such as adding their own DNS records (ie to support the stand-up of new infrastructure). But they also take a use-it-or-lose-it approach, monitoring the tools that the engineer uses and rescinding access to tools they haven’t used within 90 days. But if they do need access again, it’s as simple as a message on Slack to reinstate it.
This is just one small example of streamlining the platform wrapper. There are probably a million others.
When working on OSS projects as the integrator / installer, I’ve seen many of these “platform wrapper” roadblocks. I’m sure you have too. If you see them as the installer, chances are the ops team you hand over to will also experience these roadblocks.
Question though. Do you flag these platform wrapper roadblocks for improvement, or do you treat them as non-platform and therefore just live with them?
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).
“There’s a fable of a man stuck in a flood. Convinced that God is going to save him, he says no to a passing canoe, boat, and helicopter that offer to help. He dies, and in heaven asks God why He didn’t save him. God says, “I sent you a canoe, a boat, and a helicopter!”
We all have vivid imaginations. We get a goal in our mind and picture the path so clearly. Then it’s hard to stop focusing on that vivid image, to see what else could work.
New technologies make old things easier, and new things possible. That’s why you need to re-evaluate your old dreams to see if new means have come along.”
Derek Sivers, here.
In the past, we could make OSS platform decisions with reasonable confidence that our choices would remain viable for many years. For example, in the 1990s if we decided to build our OSS around a particular brand of relational database then it probably remained a valid choice until after 2010.
But today, there are so many more platforms to choose from, not to mention the technologies that underpin them. And it’s not just the choices currently available but the speed with which new technologies are disrupting the existing tech. In the 1990s, it was a safe bet to use AutoCAD for outside plant visualisation without the risk of heavy re-tooling within a short timeframe.
If making the same decision today, the choices are far less clear-cut. And the risk that your choice will be obsolete within a year or two has skyrocketed.
With the proliferation of open-source projects, the decision has become harder again. That means the skill-base required to service each project has also spread thinner. In turn, decisions for big investments like OSS projects are based more on the critical mass of developers than the functionality available today. If many organisations and individuals have bought into a particular project, you’re more likely to get your new features developed than from a better open-source project that has less community buy-in.
We end up with two ends of a continuum to choose between. We can either chase every new bright shiny object and re-factor for each, or we can plan a course of action and stick to it even if it becomes increasingly obsoleted over time. The reality is that we probably fit somewhere between the two ends of the spectrum.
To be brutally honest I don’t have a solution to this conundrum. The closest technique I can suggest is to design your solution with modularity in mind, as opposed to the monolithic OSS of the past. That’s the small-grid OSS architecture model. It’s easier to replace one building than an entire city.
Both of these posts talk about the speed of getting things done outside the bureaucracy of big operators, big networks and big OSS. Today, as the post title suggests, we’re going to look at orgitecture – how re-designing the structure and culture of an organisation can help streamline digital transformations.
Do you agree with the premise that smaller entities (eg Agile autonomous groups, partners, consultants, etc) can get OSS tasks done more efficiently when operating at arms-length of the larger entity (eg the carrier)? I believe that this is a first principle of physics at play.
If you’ve worked under this arms-length arrangement in the past, you’ll also know that at some point those delivery outcomes need to get integrated back into the big entity. It’s what we referred to yesterday as absorption, where the level of integration effort falls on a continuum between minimally absorbed to fully absorbed.
OSS orgitecture is the re-architecture of the people, processes, culture and org structure to better allow for the absorption process. In the past, all the safety-checks (eg security, approvals, ops handover, etc) were designed on the assumption that internal teams were doing the work. They’re not always a great fit, especially when it comes to documentation review and approval.
For example, I have a belief that the effectiveness of documentation review and approval is inversely proportional to the number of reviewers (in most, but not all cases). Unfortunately, when an external entity is delivering, there tends to be inherently less trust than if an internal entity was delivering. As such, the safety-checks increase.
Another example is when the large organisation uses Agile delivery models, but use supply partners to deliver scope of works. The partners are able to assign effort in a sequential / waterfall manner, but can be delayed by only getting timeslices of attention from client’s staff (ie resources are available according to Agile sprint planning).
Security and cutover planning mechanisms such as Change Review Boards (CRB) have also been designed around old internal delivery models. They also need to be reconsidered to facilitate a pipeline of externally-implemented change.
Perhaps the biggest orgitecture factor is in getting multiple internal business units to work together effectively. In the old world we needed all the business units to reach consensus for a new product to come to market. Sales/Marketing/Products had to work with OSS/IT and Networks. Each of these units tend to have vastly different cultures and different cadences for getting their tasks done. Delivering a new product was as much an organisational challenge as it was a technical challenge and often took months. Those times-to-market are not feasible in a world of software where competitive advantages are fleeting. External entities can potentially help or hinder these timeframes. Careful design of small autonomous teams have the potential to improve abstraction at the interlocks, but culture remains the potential roadblock.
I’m excited by the opportunity for OSS delivery improvement coming from leveraging the gig economy. But if big OSS transformations are to make use of these efficiency gains, then we may also need to consider culture and process refinement as part of the change management.
One popular approach is to build a proof-of-concept or sandpit quickly on cloud hosting or in lab environments. It’s fast for a number of reasons including reduced number of approvals, faster activation of infrastructure, reduced safety checks (eg security, privacy, etc), minimised integration with legacy systems and many other reasons. The cloud hosting business model is thriving for all of these reasons.
However, it’s one thing to speed up development of an OSS PoC and another entirely to speed up deployment to a PROD environment. As soon as you wish to absorb the PoC-proven solution back into PROD, all the items listed above (eg security sign-offs) come back into play. Something that took days/weeks to stand up in PoC now takes months to productionise.
Have you noticed that the safety checks currently being used were often defined for the old world? They often aren’t designed with transition from cloud to PROD in mind. Similarly, the culture of design cross-checks and approvals can also be re-framed (especially when the end-to-end solution crosses multiple different business units). Lastly, and way outside my locus of competence, is in re-visiting security / privacy / deployment / etc models to facilitate easier transition.
One consideration to make is just how much absorption is required. For example, there are examples of services being delivered to the large entity’s subscribers by a smaller, external entity. The large entity then just “clips-the-ticket,” gaining a revenue stream with limited involvement. But the more common (and much more challenging) absorption model is for the partner to fold the solution back into the large entity’s full OSS/BSS stack.
So let’s consider your opportunity in terms of the absorption continuum that ranges between:
Perhaps it’s feasible for your opportunity to fit somewhere in between (partially absorbed)? Perhaps part of that answer resides in the cloud model you decide to use (public, private, hybrid, cloud-managed private cloud) as well as the partnership model?
Modularity and reduced complexity (eg integrations) are also a factor to consider (as always).
I haven’t seen an ideal response to the absorption challenge yet, but I believe the solution lies in re-framing corporate culture and technology stacks. We’ll look at that in more detail tomorrow.
How about you? Have you or your organisation managed to speed up your transition from PoC to PROD? What techniques have you found to be successful?
Do you work in a large organisation? Have you also worked in smaller organisations?
Where have you felt more efficient?
I’ve been lucky enough to work on some massive OSS transformations for large T1 telcos. But I’ve always noticed the inefficiency of working on these projects when embedded inside the bureaucracy of the beast. With all of the documentation, sign-offs, meetings, politics, gaining consensus, budget allocations, etc it can sometimes feel so inefficient. On some past projects, I’ve felt I can accomplish more in a day outside than a week or more inside the beast.
It’s one of the reasons I love working within a small entity (Passionate About OSS), but into big entities (the big telcos and utilities). It’s also why I strongly believe that the big entities need to better leverage smaller working groups to facilitate big OSS change. Not just OSS transformation, but any project where the size of the culture and technology stack are prohibitive.
Here are a few ways you can use to bring a start-up’s efficiency to a big OSS transformation:
Agile methodologies – If done well, Agile can be great at breaking transformations down into smaller, more manageable pieces. The art is in designing small autonomous teams / responsibilities and breakdown of work to minimise dependencies
Partnerships – Using smaller, external partners to deliver outcomes (eg product builds or service offerings) that can be absorbed into the big organisation. There are varying levels of absorption here – from an external, “clip-the-ticket” offering to offerings that are fully absorbed into the large entity’s OSS/BSS stack
Consultancies – Similar to partnerships, but using smaller teams to implement professional services
Spin-out / spin-in teams – Separating small teams of experts out from the bureaucracy of the large organisation so that they can achieve rapid progress
Smart contracts / RFPs – I love the potential for smart contracts to automate the offer of small chunks of work to trusted partners to bid upon and then deliver upon
Externalised Proofs of Concept (PoC) – One of the big challenges in implementing for large organisations is all of the safety checks that slow progress. Many, such as security and privacy mechanisms, are completely justified for a production network. But when a concept needs to be proved, such as user journeys, product integrations, sand-pit environments, etc, then cloud-based PoCs can be brilliant
Alternate brands – Have you also noticed that some of the tier-1 telcos have been spinning out low-cost and/or niche brands with much leaner OSS/BSS stacks, offerings and related culture lately? It’s a clever business model on many levels. Combined with the strangler fig transformation approach, this might just represent a pathway for the big brand to shed many of their OSS/BSS legacy constraints
Can you think of other models that I’ve missed?
The key to these strategies is not so much the carve-out, the process of getting small teams to do tasks efficiently, but the absorb-in process. For example, how to absorb a cloud-based PoC back into the PROD network, where all safety checks (eg security, privacy, operations acceptance, etc) still need to be performed. More on that in tomorrow’s post.
“Resilience is what happens when we’re able to move forward even when things don’t fit together the way we expect.[OSS project anyone???]
And tolerances are an engineer’s measurement of how well the parts meet spec.
One way to ensure that things work out the way you hope is to spend the time and money to ensure that every part, every form, every worker meets spec. Tighten your spec, increase precision and you’ll discover that systems become more reliable.
The other alternative is to embrace the fact that nothing is ever exactly on spec, and to build resilient systems.
You’ll probably find that while precision feels like the way forward, resilience, the ability to thrive when things go wrong, is a much safer bet.”
From the side of past experience, resilience is a massive factor in overcoming the many obstacles faced on implementation projects. I’ve yet to work on an OSS project where all challenges were known at inception.
In that example, the OSS/BSS, and possibly the associated people / process, had a direct impact on poor customer experience. Admittedly, that 7 truck-roll experience was a number of years ago now.
We have fewer excuses these days. Smart phones and network connected devices allow us to get OSS/BSS data into the field in ways we previously couldn’t. There’s no need for printed job lists, design packs and the like. Our OSS/BSS can leverage these connected devices to give far better decision intelligence in real time.
If we look to the logistics industry, we can see how parcel tracking technologies help to automatically provide status / progress to parcel recipients. We can see how recipients can also modify their availability, which automatically adjusts logistics delivery sequencing / scheduling.
This has multiple benefits for the logistics company:
It increases first time delivery rates
Improves the ability to automatically notify customers (eg email, SMS, chatbots)
Decreases customer enquiries / complaints
Decreases the amount of time the truck drivers need to spend communicating back to base and with clients
But most importantly, it improves the customer experience
Logistics is an interesting challenge for our OSS/BSS due to the sheer volume of customer interaction events handled each day.
But it’s another area that excites me even more, where CX is improved through improved data quality:
It’s the ability for field workers to interact with OSS/BSS data in real-time
To see the design packs
To compare with field situations
To update the data where there is inconsistency.
Even more excitingly, to introduce augmented reality to assist with decision intelligence for field work crews:
To provide an overlay of what fibres need to be spliced together
To show exactly which port a patch-lead needs to connect to