Going to the OSS zoo

There’s the famous quote that if you want to understand how animals live, you don’t go to the zoo, you go to the jungle. The Future Lab has really pioneered that within Lego, and it hasn’t been a theoretical exercise. It’s been a real design-thinking approach to innovation, which we’ve learned an awful lot from.”
Jorgen Vig Knudstorp
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This quote prompted me to ask the question – how many times during OSS implementations had I sought to understand user behaviour at the zoo versus the jungle?

By that, how many times had I simply spoken with the user’s representative on the project team rather than directly with end users? What about the less obvious personas as discussed in this earlier post about user personas? Had I visited the jungles where internal stakeholders like project sponsors, executives, data consumers, etc. or external stakeholders such as end-customers, regulatory bodies, etc go about their daily lives?

I can truthfully, but regretfully, say I’ve spent far more time at OSS zoos than in jungles. This is something I need to redress.

But, at least I can claim to have spent most time in customer-facing roles.

Too many of the product development teams I’ve worked closely with don’t even visit OSS zoos let alone jungles in any given year. They never get close to observing real customers in their native environments.

 

OSS Persona 10:10:10 Mapping

We sometimes attack OSS/BSS planning at a quite transactional level. For example, think about the process of gathering detailed requirements at the start of a project. They tend to be detailed and transactional don’t they? This type of requirement gathering is more like the WHAT and HOW rings in Simon Sinek’s Golden Circle.

Just curious, do you have a persona map that shows all of the different user groups that interact with your OSS/BSS?
More importantly, do you deeply understand WHY they interact with your OSS/BSS? Not just on a transaction-by-transaction level, but in the deeper context of how the organisation functions? Perhaps even on a psychological level?

If you do, you’re in a great position to apply the 10:10:10 mapping rule. That is, to describe how you’re adding value to each user group 10 minutes from now, 10 days from now and 10 months from now…

OSS Persona 10:10:10 Mapping

The mapping table could describe current tense (ie how your OSS/BSS is currently adding value), or as a planning mechanism for a future tense (ie how your OSS/BSS can add value in the future).
This mapping table can act as a guide for the evolution of your solution.

I should also point out that the diagram above only shows a sample of the internal personas that directly interact with your OSS/BSS. But I’d encourage you to look further. There are other personas that have direct and indirect engagement with your OSS/BSS. These include internal stakeholders like project sponsors, executives, data consumers, etc. They also include external stakeholders such as end-customers, regulatory bodies, etc.

If you need assistance to unlock your current state through persona mapping, real process mapping, etc and then planning out your target-state, Passionate About OSS would be delighted to help.

I’m really excited by a just-finished OSS analysis (part 3)

This is the third part of a series describing a really exciting analysis I’ve just finished.

Part 1 described how we can turn simple log files into a Sankey diagram that shows real-life process flows (not just a theoretical diagram drawn by BAs and SMEs), like below:

Part 2 described how the logs are broken down into a design tree and how we can assign weightings to each branch based on the data stored in the logs, as below:
OSS Decision Tree Analysis

I’ve already had lots of great feedback in relation to the Part 1 blog, especially from people who’ve had challenges capturing as-is process. The feedback has been greatly appreciated so I’m looking forward to helping them draw up their flow-charts on the way to helping optimise their process flows.

But that’s just the starting point. Today’s post is where things get really exciting (for me at least). Today we build on part 2 and not just record weightings, but use them to assist future decisions.

We can use the decision tree to “predict forward” and help operators / algorithms make optimal decisions whilst working towards process completion. We can use a feedback loop to steer an operator (or application) down the most optimal branches of the tree (and/or avoid the fall-out variants).

This allows us to create a closed-loop, self-optimising, Decision Support System (DSS), as follows:

Note: Diagram sourced from https://passionateaboutoss.com/closing-the-loop-to-make-better-decisions, where further explanation is provided

Using log data alone, we can perform decision optimisation based on “likelihood of success” or “time to complete” as per the weightings table. If supplemented with additional data, the weightings table could also allow decisions to be optimised by “cost to complete” or many other factors.

The model has the potential to be used in “real-time” mode, using the constant stream of process logs to continually refine and adapt. For example:

  • If the long-term average of a process path is 1 minute, but there’s currently a problem with and that path is failing, then another path (one that is otherwise slightly less optimised over the long-term), could be used until the first path is repaired
  • An operator happens to choose a new, more optimal path than has ever been identified previously (the delta function in the diagram). It then sets a new benchmark and informs the new approach via the DSS (Darwinian selection)

If you’re wondering how the DSS could be implemented, I can envisage a few ways:

  1. Using existing RPA (Robotic Process Automation) tools [which are particularly relevant if the workflow box in the diagram above crosses multiple different applications (not just a single monolithic OSS/BSS)]
  2. Providing a feedback path into the functionality of the OSS/BSS and it’s GUI
  3. Via notifications (eg email, Slack, etc) to operators
  4. Via a simple, more manual process like flow diagrams, work instructions, scorecards or similar
  5. You can probably envisage other methods

I’m really excited by a just-finished OSS analysis (part 2)

As the title suggests, this is the second part in a series describing a process flow visualisation, optimisation and decision support methodology that uses simple log data as input.

Yesterday’s post, part 1 in the series, showed the visualisation aspect in the form of a Sankey flow diagram.

This visualisation is exciting because it shows how your processes are actually flowing (or not), as opposed to the theoretical process diagrams that are laboriously created by BAs in conjunction with SMEs. It also shows which branches in the flow are actually being utilised and where inefficiencies are appearing (and are therefore optimisation targets).

Some people have wondered how simple activity logs can be used to show the Sankey diagrams. Hopefully the diagram below helps to describe this. You scan the log data looking for variants / patterns of flows and overlay those onto a map of decision states (DPs). In the diagram above, there are only 3 DPs, but 303 different variants (sounds implausible, but there are many variants that do multiple loops through the 3 states and are therefore considered to be a different variant).

OSS Decision Tree Analysis

The numbers / weightings you see on the Sankey diagram are the number* of instances (of a single flow type) that have transitioned between two DPs / states.

* Note that this is not the same as the count value that appears in the Weightings table. We’ll get to that in tomorrow’s post when we describe how to use the weightings data for decision support.

I’m really excited by a just-finished OSS analysis

In your travels, I don’t suppose you’ve ever come across anyone having challenges to capture and/or optimise their as-is OSS/BSS process flows? Once or twice?? 🙂

Well I’ve just completed an analysis that I’m really excited about. It’s something I’ve been thinking about for some time, but have just finished proving on the weekend. I thought it might have relevance to you too. It quickly helps to visualise as-is process and identify areas to optimise.

The method takes activity logs (eg from OSS, ITIL, WFM, SAP or similar) and turns them into a process diagram (a Sankey diagram) like below with real instance volumes. Much better than a theoretical process map designed by BAs and SMEs don’t you think?? And much faster and more accurate too!!

OSS Sankey process diagram

A theoretical process map might just show a sequence of 3 steps, but the diagram above has used actual logs to show what’s really occurring. It highlights governance issues (skipped steps) and inefficiencies (ie the various loops) in the process too. Perfect for process improvement.

But more excitingly, it proves a path towards real-time “predict-forward” decision support without having to get into the complexities of AI. More has been included in the analysis!

If this is of interest to you, let me know and I’ll be happy to walk you through the full analysis. Or if you want to know how your real as-is processes perform, I’d be happy to help turn your logs into visuals like the one above.

PS1. You might think you need a lot of fields to prepare the diagrams above. The good news is the only mandatory fields would be something like:

  1. Flow type – eg Order type, project type or similar (only required if the extract contains multiple flow types mixed together. The diagram above represents just one flow type)
  2. Flow instance identifier – eg Order number, project number or similar (the diagram above was based on data that had around 600,000 flow instances)
  3. Activity identifier – eg Activity name (as per the 3 states in the diagram above), recorded against each flow instance. Note that they will ideally be an enumerated list (ie from a finite pick-list)
  4. Timestamps – Start/end timestamp on each activity instance

If the log contains other details such as the name of the operator who completed each activity, that can help add richness, but not mandatory.

PS2. The main objective of the analysis was to test concepts raised in the following blog posts:

The OSS “out of control” conundrum

Over the years in OSS, I’ve spent a lot of my time helping companies create their OSS / BSS strategies and roadmaps. Sometimes clients come from the buy side (eg carriers, utilities, enterprise), other times clients come from the sell side (eg vendors, integrators). There’s one factor that seems to be most commonly raised by these clients, and it comes from both sides.

What is that one factor? Well, we’ll come back to what that factor is a little later, but let’s cover some background first.

OSS / BSS covers a fairly broad estate of functionality:
OSS and BSS overlaid onto the TAM

Even if only covering a simplified version of this map, very few suppliers can provide coverage of the entire estate. That infers two things:

  1. Integrations; and
  2. Relationships

If you’re from the buy-side, you need to manage both to build a full-function OSS/BSS suite. If you’re from the sell-side, you’re either forced into dealing with both (reactive) or sometimes you can choose to develop those to bring a more complete offering to market (proactive).

You will have noticed that both are double-ended. Integrations bring two applications / functions together. Relationships bring two organisations together.

This two-ended concept means there’s always a “far-side” that’s outside your control. It’s in our nature to worry about what’s outside our control. We tend to want to put controls around what we can’t control. Not only that, but it’s incumbent on us as organisation planners to put mitigation strategies in place.

Which brings us back to the one factor that is raised by clients on most occasions – substitution – how do we minimise our exposure to lock-in with an OSS product / service partner/s if our partnership deteriorates?

Well, here are some thoughts:

  1. Design your own architecture with product / partner substitution in mind (and regularly review your substitution plan because products are always evolving)
  2. Develop multiple integrations so that you always have active equivalency. This is easier for sell-side “reactives” because their different customers will have different products to integrate to (eg an OSS vendor that is able to integrate with four different ITSM tools because they have different customers with each of those variants)
  3. Enhance your own offerings so that you no longer require the partnership, but can do it yourself
  4. Invest in your partnerships to ensure they don’t deteriorate. This is the OSS marriage analogy where ongoing mutual benefits encourage the relationship to continue.

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.