Stealing fire for OSS

I’ve recently started reading a book called Stealing Fire: How Silicon Valley, the Navy SEALs, and Maverick Scientists Are Revolutionizing the Way We Live and Work. To completely over-generalise the subject matter, it’s about finding optimal performance states, aka finding flow. Not the normal topic of conversation for here on the PAOSS blog!!

However, the book’s content has helped to make the link between flow and OSS more palpable than you might think.

In the early days of working on OSS delivery projects, I found myself getting into a flow state on a daily basis – achieving more than I thought capable, learning more effectively than I thought capable and completely losing track of time. In those days of project delivery, I was lucky enough to get hours at a time without interruptions, to focus on what was an almost overwhelming list of tasks to be done. Over the first 5-ish years in OSS, I averaged an 85 hour week because I was just so absorbed by it. It was the source from where my passion for OSS originated. Or was it??

The book now has me pondering a chicken or egg conundrum – did I become so passionate about OSS that I could get into a state of flow or did I only become passionate about OSS because I was able to readily get into a state of flow with it? That’s where the book provides the link between getting in the zone and the brain chemicals that leave us with a feeling of ecstasis or happiness (not to mention the addictive nature of it). The authors describe this state of consciousness as Selflessness, Timelessness, Effortlessness, and Richness, or STER for short. OSS definitely triggered STER for me,, but chicken or egg??

Having spent much of the last few years embedded in big corporate environments, I’ve found a decreased ability to get into the same flow state. Meetings, emails, messenger pop-ups, distractions from surrounding areas in open-plan offices, etc. They all interrupt. It’s left me with a diminishing opportunity to get in the zone. With that has come a growing unease and sense of sub-optimal productivity during “office hours.” It was increasingly disheartening that I could generally only get into the zone outside office hours. For example, whilst writing blogs on the train-trip or in the hours after the rest of my family was asleep.

Since making the concerted effort to leave that “office state,” I’ve been both surprised and delighted at the increased productivity. Not just that, but the ability to make better lateral connections of ideas and to learn more effectively again.

I’d love to hear your thoughts on this in the comments section below. Some big questions for you:

  1. Have you experienced a similar productivity gap between “flow state” and “office state” on your OSS projects?
  2. Have you had the same experience as me, where modern ways of working seem to be lessening the long chunks of time required to get into flow state?
  3. If yes, how can our sponsor organisations and our OSS products continue to progress if we’re increasingly working only in office state?

Step-by-step guide to build a systematic root-cause analysis (RCA) pipeline

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:

  1. Scope – Identify your initial target / scope. For example, what are you seeking to prioritise:
    1. Event volume reduction to give the NOC breathing space to function better
    2. Identifying “most important” events (but defining what is most important)
    3. Minimising SLA breaches
    4. etc
  2. 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)
  3. 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
  4. Prioritise – Using a long-tail graph like below, prioritise pattern groups by the following (and in line with item #1 above):
      1. Number of instances of the pattern / group (ie frequency)
      2. Priority of instances (ie urgency of resolution)
      3. Number of linked incidents (ie volume)
      4. Other technique, such as a cumulative/blended metric

  5. 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)
  6. Note any Existing Resolutions – Identify and categorise any existing resolutions and/or RCA rules (if data supports this)
  7. 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.
  8. Codify Patterns – Progressively set out to identify possible root-cause by analysing cause-effect such as:
    1. Topology-based
    2. Object hierarchy
    3. Time-based ripple
    4. Geo-based ripple
    5. Other (as helped to be defined by NOC operators)
  9. Knowledge base – Create a knowledge base that itemises root-causes and supporting information
  10. 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
  11. Test pilot algorithm (with analytics??)
  12. Introduce algorithm into production use – But continue to monitor what’s being suppressed to
  13. Repeat – Then repeat from steps 7 to 12 to codify the next most important pattern
  14. Leading metrics – Identify leading metrics and/or preventative measures that could precede the RCA rule. Establish closed-loop automated resolution
  15. Improve – Manage and maintain process improvement

What if most OSS/BSS are overkill? Planning a simpler version

You may recall a recent article that provided a discussion around the demarcation between OSS and BSS, which included the following graph:

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:

In an OSS, what are O2A, T2R, U2C, P2O and DBA?

Let’s start with the last one first – DBA.

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)

If you’re interested in seeing how these workflows relate to the TM Forum APIs and specifically to NaaS (Network as a Service) designs, there’s a great document (TMF 909A v1.5) that can be found at the provided link. It shows the sub-elements (and associated APIs) that each of these workflows rely on.

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?

Top 10 most common OSS project risks

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:

  1. 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
  2. Change ManagementOSS 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
  3. 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
  4. 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)
  5. 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
  6. 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
  7. CommunicationOSS 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
  8. 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
  9. 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
  10. 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.

Inverting the pyramid of OSS and network innovation

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:

Zero-touch partnering could make platform ‘utopia’ real for telcos

Packaging Open APIs for NaaS

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:

Time to kill the RFP? Reinventing IT procurement for the 2020s: Volume 1

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.

Is your OSS squeaking like an un-oiled bearing?

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:

  1. First-time Installation
  2. Identifying best-fit tools
  3. Procurement of new tools
  4. Update / release processes
  5. Continuous data quality / consistency improvement
  6. Navigating to all features through the user interface
  7. Non-intuitive functionality / processes
  8. So many variants / complexity that end-users take years to attain expert-level capability
  9. Integration / interconnect
  10. Getting new starters up to speed
  11. Getting proficient operators to expertise
  12. Unlocking actionable insights from huge data piles
  13. Resolving the root-cause of complex faults
  14. Onboarding new customers
  15. Productionising new functionality
  16. Exception and fallout handling
  17. 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.

Would you hire a furniture maker as an OSS CEO?

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:

Idx Comparison Criteria Car OSS
1 Primary objective Transport passengers between destinations Operationalise and monetise a comms network
2 Claimed “Business” justification Personal freedom Reducing the cost of operations
3 Operation of common functionality without conscious thought (developed through years of operator practice) Steering

Changing gears

Indicating

Hmmm??? Depends on which sales person or operator you speak with
4 Error detection and current-state monitoring Warning lights and instrument cluster/s Alarm lists, performance graphs
5 Key differentiator for customers (1970’s) Engine size Database / CPU size
6 Key differentiator for customers (2000’s) Gadgets / functions / cup-holders Functionality
7 Key differentiator for customers (2020+) User Experience

Self-driving

Connected car (car as an “experience platform”)

User Experience??

Zero-touch assurance?

Connected OSS (ie OSS as an experience platform)???

I’d like to focus on three key areas next:

  1. Item 3
  2. Item 4 and
  3. 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.

Hat tip to Jerry Useem, whose article on Atlantic provided the idea seed for this OSS post.

How to bring your art and your science to your OSS

In the last two posts, we’ve discussed repeatability within the field of OSS implementation – paint-by-numbers vs artisans and then resilience vs precision in delivery practices.

Now I’d like you to have a think about how those posts overlay onto this quote by Karl Popper:
Non-reproducible single occurrences are of no significance to science.”

Every OSS implementation is different. That means that every one is a non-reproducible single occurrence. But if we bring this mindset into our OSS implementations, it means we’re bringing artisinal rather than scientific method to the project.

I’m all for bringing more art, more creativity, more resilience into our OSS projects.

I’m also advocating more science though too. More repeatability. More precision. Whilst every OSS project may be different at a macro level, there are a lot of similarities in the micro-elements. There tends to be similarities in sequences of activities if you pay close attention to the rhythms of your projects. Perhaps our products can use techniques to spot and leverage similarities too.

In other words, bring your art and your science to your OSS. Please leave a comment below. I’d love to hear the techniques you use to achieve this.

The OSS Minimum Feature Set is Not The Goal

This minimum feature set (sometimes called the “minimum viable product”) causes lots of confusion. Founders act like the “minimum” part is the goal. Or worse, that every potential customer should want it. In the real world not every customer is going to get overly excited about your minimum feature set. Only a special subset of customers will and what gets them breathing heavy is the long-term vision for your product.

The reality is that the minimum feature set is 1) a tactic to reduce wasted engineering hours (code left on the floor) and 2) to get the product in the hands of early visionary customers as soon as possible.

You’re selling the vision and delivering the minimum feature set to visionaries not everyone.”
Steve Blank here.

A recent blog series discussed the use of pilots as an OSS transformation and augmentation change agent.
I have the need for OSS speed
Re-framing an OSS replacement strategy
OSS transformation is hard. What can we learn from open source?

Note that you can replace the term pilot in these posts with MVP – Minimum Viable Product.

The attraction in getting an MVP / pilot version of your OSS into the hands of users is familiarity and momentum. The solution becomes more tangible and therefore needs less documentation (eg architecture, designs, requirement gathering, etc) to describe foreign concepts to customers. The downside of the MVP / pilot is that not every customer will “get overly excited about your minimum feature set.”

As Steve says, “Only a special subset of customers will and what gets them breathing heavy is the long-term vision for your product.” The challenge for all of us in OSS is articulating the long-term vision and making it compelling…. and not just leaving the product in its pilot state (we’ve all seen this happen haven’t we?)

We’ll provide an example of a long-term vision tomorrow.

PS. I should also highlight that the maximum feature set also isn’t the goal either.

OSS transformation is hard. What can we learn from open source?

Have you noticed an increasing presence of open-source tools in your OSS recently? Have you also noticed that open-source is helping to trigger transformation? Have you thought about why that might be?

Some might rightly argue that it is the cost factor. You could also claim that they tend to help resolve specific, but common, problems. They’re smaller and modular.

I’d argue that the reason relates to our most recent two blog posts. They’re fast to install (don’t need to get bogged down in procurement) and they’re easy to run in parallel for comparison purposes.

If you’re designing an OSS can you introduce the same concepts? Your OSS might be for internal purposes or to sell to market. Either way, if you make it fast to build and easy to use, you have a greater chance of triggering transformation.

If you have a behemoth OSS to “sell,” transformation persuasion is harder. The customer needs to rally more resources (funds, people, time) just to compare with what they already have. If you have a behemoth on your hands, you need to try even harder to be faster, easier and more modular.

I have the need for OSS speed

You already know that speed is important for OSS users. They / we don’t want to wait for minutes for the OSS to respond to a simple query. That’s obvious right? The bleeding obvious.

But that’s not what today’s post is about. So then, what is it about?

Actually, it follows on from yesterday’s post about re-framing of OSS transformation.  If a parallel pilot OSS can be stood up in weeks then it helps persuasion. If the OSS is also fast for operators to learn, then it helps persuasion.  Why is that important? How can speed help with persuasion?

Put simply:

  • It takes x months of uncertainty out of the evaluators’ lives
  • It takes x months of parallel processing out of the evaluators’ lives
  • It also takes x months of task-switching out of the evaluators’ lives
  • Given x months of their lives back, customers will be more easily persuaded

It also helps with the parallel bake-off if your pilot OSS shows a speed improvement.

Whether we’re the buyer or seller in an OSS pilot, it’s incumbent upon us to increase speed.

You may ask how. Many ways, but I’d start with a mass-simplification exercise.

What’s the one big factor holding back your OSS? And the exercise to reduce it

We’ve talked about some of the emotions we experience in the OSS industry earlier this week, the trauma of OSS and anxiety relating to OSS.

To avoid these types of miserable feelings, it’s human nature to seek to limit them. We over-analyse, we over-specify, we over-engineer, we over-document, we over-contract, we over-react, we over-estimate (nah, actually we almost never over-estimate do we?), we over-resource (well, actually, we don’t seem to do that very often either). Anyway, you get the “over” idea.

What is the one big factor that leads to all of these overs? What is the one big factor that makes our related costs and delivery times become overs too?

Have you guessed yet?

The answer is…… drum-roll please…… RISK.

Let’s face it. OSS projects are as full as a centipede’s sock drawer when it comes to risk. The customer carries risks, the supplier carries risk, the integrators carry risk, the sponsors carry risk, the end-users carry risk, the implementers carry risk. What a burden! And it is a burden that impacts in many ways, as indicated in the triple constraint of OSS projects.

Anyone who’s done more than a few OSS projects knows there are many risks and they tend to respond by going into over-mode (ie all the overs mentioned above). That’s a clever strategy. It’s called risk mitigation.

But today’s post isn’t about risk mitigation. It takes a contrarian approach. Let me explain.

Have you noticed how many companies build risk reduction techniques into their sales models? Phrases like “money-back guarantee” abound. This technique is designed to remove most of the risk for the customer and also remove the associated barrier to purchase. To be fair, it might not actually be a case of removing the risk, but directing all of the risk onto the seller. Marketers call it risk reversal.

I’m sure you’re thinking, “well that’s fine for high-volume, low-cost products like burgers or books, but not so easy for complex, customised solutions like OSS.” I hear you!

I’m not actually asking you to offer a money-back guarantee for your OSS, although Passionate About OSS does offer that all the way from our products through to our high-end consultancy services.

What I am asking you to do (whether customer, seller or integrator) is to run a planning exercise as if you MUST offer a money-back guarantee. What that forces is a change of mindset from risk mitigation to risk removal. It forces consideration of what are the myriad risks “in the system” (for customer, seller and integrator) and how can they be removed? Here are a few risk planning suggestions FWIW.

Set the following challenge for your analysts and engineers – Don’t come to me with a business case for the one-million-and-first feature to add, but prove your brilliance by showing me the business case for the risks you will remove. Risk reduction rather than feature-add or cost-out business cases.

Let me know what you discover and what your results are.

Would an OSS duopoly be a good thing?

The products/vendors page here on PAOSS has a couple of hundred entries currently. We’re currently working on an extended list that will almost double the number on it. More news on that shortly.

The level of fragmentation fascinates me, but if I’m completely honest, it probably disappoints me too. It’s great that it’s providing the platform for a long-tail of innovation. It’s exciting that there’s so many niche opportunities that exist. But it disappoints me because there’s so much duplication. How many alarm / performance / inventory / etc management tools are there? Can you imagine how many developer hours have been duplicated on similar feature development between products? And because there are so many different patterns, it means the total number of integration variants across the industry is putting a huge integration tax on us all.

Compare this to the strength of duopoly markets such as:

  • Microsoft / Apple (PC operating systems)
  • Google / Apple (smartphone operating systems)
  • Boeing / Airbus (commercial aircraft)
  • Visa / Mastercard (credit cards / payments)
  • Coca Cola / Pepsi (beverages, etc)

These duopolies have allowed for consolidation of expertise, effort, revenues/profits, etc. Most also provide a platform upon which smaller organisations / suppliers can innovate without having to re-invent everything (eg applications build upon operating systems, parts for aircraft, etc).

Buuuut……

Then I think about the impediments to achieving drastic consolidation through mergers and acquisitions (M&A) in the OSS industry.

There are opportunities to find complementary product alignment because no supplier services the entire OSS estate (where I’m using TM Forum’s TAM as a guide to the breadth of the OSS estate). However, it would be much harder to approach duopoly in OSS for a number of reasons:

  • Almost every OSS implementation is unique. Even if some of the products start out in common, they usually become quickly customised in terms of integrations, configurations, processes, etc
  • Interfaces to networks and other systems can vary so much. Modern EMS / devices / systems are becoming a little more consistent with IP, SNMP, Web APIs, etc. However, our networks still tend to have a lot of legacy protocols to interface with our networks
  • Consolidation of product lines becomes much harder, partly because of the integrations above, but partly because the functionality-sets and workflows differ so vastly between similar products (eg inventory management tools)
  • Similarly, architectures and build platforms (eg programming languages) are not easily compatible
  • Implementations are often regional for a variety of reasons – regulatory, local partnerships / relationships, language, corporate culture, etc
  • Customers can be very change-averse, even when they’re instigating the change

By contrast, we regularly hear of Coca Cola buying up new brands. It’s relatively easy for Coke to add a new product line/s without having much impact on existing lines.

We also hear about Google’s acquisitions, adding complementary products into its product line or simple for the purpose of acquiring new talent / expertise. There’s also acquisitions for the purpose of removing competitors or buying into customer bases.

Harder in all cases in the OSS industry.

Tomorrow we’ll share a story about an M&A attempting to buy into a customer base.

Then on Thursday, a story awaits on a possibly disruptive strategy towards consolidation in OSS.

To link or not to link your OSS. That is the question

The first OSS project I worked on had a full-suite, single vendor solution. All products within the suite were integrated into a single database and that allowed their product developers to introduce a lot of cross-linking. That has its strengths and weaknesses.

The second OSS suite I worked with came from one of the world’s largest network vendors and integrators. Their suite primarily consisted of third-party products that they integrated together for the customer. It was (arguably) a best-of-breed all implemented as a single solution, but since the products were disparate, there was very little cross-linking. This approach also has strengths and weaknesses.

I’d become so used to the massive data migration and cross-referencing exercise required by the first OSS that I was stunned by the lack of time allocated by the second vendor for their data migration activities. The first took months and a significant level of expertise. The second took days and only required fairly simple data sets. That’s a plus for the second OSS.

However, the second OSS was severely lacking in cross-domain data, which impacted the richness of insight that could be easily unlocked.

Let me give an example to give better context.

We know that a trouble ticketing system is responsible for managing the tracking, reporting and resolution of problems in a network operator’s network. This could be as simple as a repository for storing a problem identifier and a list of notes performed to resolve the problem. There’s almost no cross-linking required.

A more referential ticketing system might have links to:

  • Alarm management – to show the events linked to the problem
  • Inventory management – to show the impacted resources (or possibly impacted)
  • Service management – to show the services impacted
  • Customer management – to show the customers impacted and possibly the related customer interactions
  • Spares management – to show the life-cycle of physical resources impacted
  • Workforce management – to manage the people / teams performing restorative actions
  • etc

The referential ticketing system gives far richer information, obviously, but you have to trade that off against the amount of integration and data maintenance that needs to go into supporting it. The question to ask is what level of linking is justifiable from a cost-benefit perspective.

Treating your OSS/BSS suite like a share portfolio

Like most readers, I’m sure your OSS/BSS suite consists of many components. What if you were to look at each of those components as assets? In a share portfolio, you analyse your stocks to see which assets are truly worth keeping and which should be divested.

We don’t tend to take such a long-term analytical view of our OSS/BSS components. We may regularly talk about their performance anecdotally, but I’m talking about a strategic analysis approach.

If you were to look at each of your OSS/BSS components, where would you put them in the BCG Matrix?
BCG matrix
Image sourced from NetMBA here.

How many of your components are giving a return (whatever that may mean in your organisation) and/or have significant growth potential? How many are dogs that are a serious drain on your portfolio?

From an investor’s perspective, we seek to double-down our day-to-day investment in cash-cows and stars. Equally, we seek to divest our dogs.

But that’s not always the case with our OSS/BSS porfolio. We sometimes spend so much of our daily activity tweaking around the edges, trying to fix our dogs or just adding more things into our OSS/BSS suite – all of which distracts us from increasing the total value of our portfolio.

To paraphrase this Motley Fool investment strategy article into an OSS/BSS context:

  • Holding too many shares in a portfolio can crowd out returns for good ideas – being precisely focused on what’s making a difference rather than being distracted by having too many positions. Warren Buffett recommends taking 5-10 positions in companies that you are confident in holding forever (or for a very long period of time), rather than constantly switching. I shall note though that software could arguably be considered to be more perishable than the institutions we invest in – software doesn’t tend to last for decades (except some OSS perhaps  😀 )
  • Good ideas are scarce – ensuring you’re not getting distracted by the latest trends and buzzwords
  • Competitive knowledge advantage – knowing your market segment / portfolio extremely well and how to make the most of it, rather than having to up-skill on every new tool that you bring into the suite
  • Diversification isn’t lost – ensuring there is suitable vendor/product diversification to minimise risk, but also being open to long-term strategic changes in the product mix

Day-trading of OSS / BSS tools might be a fun hobby for those of us who solution them, but is it as beneficial as long-run investment?

I’d love to hear your thoughts and experiences.

2019 predictions for OSS

Well, this is the time of year when people make big predictions for the coming year. But let me start by saying the headline is something of a misnomer. I’m not clever enough to have any predictions for 2019 for a couple of reasons:

  1. There are far too many clever people working across the myriad fields of expertise that make up an OSS for me to possibly guess which might gain traction this year
  2. I’m yet to figure out whether there are any consistent patterns or cycles like Moore’s Law that uniquely define progress in OSS. On the contrary, you could claim that there are any number of metrics that might define progress for OSS (or to any individual OSS stack). But I’ll also be honest enough to say that I haven’t tried applying any of these futurology techniques to find any useful patterns either.
    Futurism Methodologies

Instead, I’ll call out the many industry-wide challenges / opportunities that are still waiting to be solved in 2019. Many of these same challenges / opportunities have been around since I first started working on OSS projects in circa 2000.

The Passionate About OSS Call for Innovation paper outlines a list of starting points where exponential improvements await.

I’m not sure if any will be solved in 2019 but I will make the prediction that the thousands of very clever people working in the OSS industry will make some exciting steps forward this year. Hopefully they’re some of the quantum leaps that await and not only the ever-present, but still highly challenging, incremental improvements.

OSS come in all shapes and sizes

As the OSS vendors / suppliers page here on PAOSS shows, there are a LOT of different OSS options, making it an extremely fragmented market. But there’s something of a reason for that fragmentation – customer requirements for OSS come in all shapes and sizes. Here are four of the major categories that I’ve been lucky enough to work on.

Tier 1 telcos – the OSS of these organisations tend to be best classified as having to cope with scale. Scale comes in multiple dimensions. The number of network devices under management tend to be large, as do the types of device. The number of subscribers and customer services tend to be large, not to mention having large amounts of change occurring on a daily basis. The number of process variants and system integrations also tend to be large. And being at scale means that they’re more likely to be able to justify the cost of customisations and automations – either to off-the-shelf products or via purpose-built tools. Budgets, both CAPEX and OPEX, also tend to be large. Except where niche slices of the total OSS suite are being delivered, the vendors that service this market are also large in terms of revenues, but also in their number of services staff available to service the customer’s unique needs. In the case of the telco, the business (and revenue model) is built around the network so it gets the clear attention of the organisation’s executives.

Enterprise customers – these OSS tend to be at the other end of the spectrum, even when the enterprise is large (eg banks). Networks tend to be more homogeneous, being IT/IP-centric. Services tend to be less customer-specific (ie for journaling costs at a business unit level rather than individual subscribers) but follow ITSM process models, so the service management daily delta is not at the same scale as the Tier 1 telco. For enterprise customers, the network is rarely core business, even if it is mission-critical to the business. As such, attention and budgets tend to be much smaller. In turn, this means that the smaller, self-service or open-source OSS products / suppliers tend to be present in this segment.

Then there are two categories of organisation that fit between the two previous ends of the spectrum:

Tier 2/3 telcos, MVNOs and data centres – Similar to the Tier-1 telco, just not at the same scale, which has implications on the nature of their OSS. They generally need all the same types of OSS tools as the T1s, just not catering for the same number of variants. Due to cost constraints, there may be one or a few significant OSS building blocks such as inventory, assurance or orchestration, but often there will also be enterprise-grade and/or open-source products in their OSS stack. CAPEX and OPEX budgets are smaller, so clever jack-of-all-trades OSS experts are often on the operational teams delivering sophisticated solutions on shoe-string budgets. Some of the best OSS experts I’ve come across can trace their roots back to these origins.

Utilities – the OSS of these organisations are a fascinating mix of the first two categories above because enterprise-grade OSS often aren’t really fit-for-purpose and carrier-grade OSS doesn’t quite suit either. Except in the case of multi-utilities (eg power + telco), these organisations tend to have very little service management change, mainly because they tend to have few to no external customers. This makes them similar to enterprise OSS. But like telcos, they often have networks that are more varied than your typical IT/IP-centric networks under management in enterprise-land. They often have less common network topologies and protocols, including older and even proprietary models that enterprise-grade OSS rarely support without expensive mediation. Just like the enterprise, the telco network (and hence the OSS) of a utility is not core business and can’t be justified through driving incremental revenues. However, it is generally mission-critical to the core business (eg tele-protection circuits are in place to ensure resilience of the electricity supply across the power network). As such, telco Network health / reliability and asset management tend to be the main focus of these OSS. And whereas telcos can delegate some responsibility for network security to their customers (using the dumb-pipe excuse), utilities bear full responsibility for the security of their telco networks and the critical infrastructure that these networks and OSS tools support.

These are only broadly general categories and there are more than 50 shades of grey in between. Are there any other broad categories that you feel I’m missing?

GE undergoes another re-structure. Does it unlock a competitive advantage?

GE has just announced plans to establish a new, independent company focused on building a comprehensive Industrial Internet of Things (IIoT) software portfolio.

The spun out company will “start with $1.2 billion in annual software revenue and an existing global industrial customer base. The company is intended to be a GE wholly-owned, independently run business with a new brand and identity, its own equity structure, and its own Board of Directors. The proposed new organization aims to bring together GE Digital’s industry-leading IIoT solutions including the Predix platform, Asset Performance Management, Historian, Automation (HMI/SCADA), Manufacturing Execution Systems, Operations Performance Management, and the GE Power Digital and Grid Software Solutions businesses.”

A couple of months ago, we posed the question about cross-over use-cases / functionality / products / data / process between IoT platforms and OSS.

Sure, there are fundamental differences between what a sensor network management platform (ooops, should I call that SNMP? That won’t cause any confusion will it??) and what an OSS does. However, there seems to be enough commonality and potential for shared insight to collude.

As far as I’ve ascertained (happy to be told otherwise), GE is the only organisation that has significant offerings in both spaces – Predix in sensor network management and a multitude of OSS / asset tools including Smallworld. Up until now, I understand that Predix and OSS have been kept in separate siloes by GE. Placing the two sets of assets together in the new, as yet unnamed, digital business increases the likelihood of collaboration surely.

If GE really is the only organisation at the Venn-Diagram convergence of IOT and OSS platforms, then it holds a competitive advantage in that niche. The only question that remains is to identify the use-cases and customers that the niche (and its functionality) is relevant to, if any.

PS. Just as an aside, the restructure also includes the announcement that GE is divesting a majority stake in ServiceMax, a product that is often bundled with its OSS offers, which it bought for $916M back in 2016. Silver Lake, a private equity firm will take over that stake in early 2019.

How to kill the OSS RFP (part 4)

This is the fourth, and final part (I think) in the series on killing the OSS RFI/RFP process, a process that suppliers and customers alike find to be inefficient. The concept is based on an initiative currently being investigated by TM Forum.

The previous three posts focused on the importance of trusted partnerships and the methods to develop them via OSS procurement events.

Today’s post takes a slightly different tack. It proposes a structural obsolescence that may lead to the death of the RFP. We might not have to kill it. It might die a natural death.

Actually, let me take that back. I’m sure RFPs won’t die out completely as a procurement technique. But I can see a time when RFPs are far less common and significantly different in nature to today’s procurement events.

How??
Technology!
That’s the answer all technologists cite to any form of problem of course. But there’s a growing trend that provides a portent to the future here.

It comes via the XaaS (As a Service) model of software delivery. We’re increasingly building and consuming cloud-native services. OSS of the future, the small-grid model, are likely to consume software as services from multiple suppliers.

And rather than having to go through a procurement event like an RFP to form each supplier contract, the small grid model will simply be a case of consuming one/many services via API contracts. The API contract (eg OpenAPI specification / swagger) will be available for the world to see. You either consume it or you don’t. No lengthy contract negotiation phase to be had.

Now as mentioned above, the RFP won’t die, but evolve. We’ll probably see more RFPs formed between customers and the services companies that will create customised OSS solutions (utilising one/many OSS supplier services). And these RFPs may not be with the massive multinational services companies of today, but increasingly through smaller niche service companies. These micro-RFPs represent the future of OSS work, the gig economy, and will surely be facilitated by smart-RFP / smart-contract models (like the OSS Justice League model).