The great OSS squeeeeeeze

TM Forum’s Open Digital Architecture (ODA) White Paper begins with the following statement:

Telecoms is at a crucial turning point. The last decade has dealt a series of punishing blows to an industry that had previously enjoyed enviable growth for more than 20 years. Services that once returned high margins are being reduced to commodities in the digital world, and our insatiable appetite for data demands continuous investment in infrastructure. On the other hand, communications service providers (CSPs) and their partners are in an excellent position to guide and capitalize on the next wave of digital revolution.

Clearly, a reduction in profitability leads to a reduction in cash available for projects – including OSS transformation projects. And reduced profitability almost inevitably leads executives to start thinking about head-count reduction too.

As Luke Clifton of Macquarie Telecom observed here, “Telstra is reportedly planning to shed 1,200 people from its enterprise business with many of these people directly involved in managing small-to-medium sized business customers. More than 10,000 customers in this segment will no longer have access to dedicated Account Managers, instead relegated to being managed by Telstra’s “Digital Hub”… Telstra, like the big banks once did, is seemingly betting that customers won’t leave them nor will they notice the downgrade in their service. It will be interesting to see how 10,000 additional organisations will be managed through a Digital Hub.
Simply put, you cannot cut quality people without cutting the quality of service. Those two ideals are intrinsically linked
…”

As a fairly broad trend across the telco sector, projects and jobs are being cut, whilst technology change is forcing transformation. And as suggested in Luke’s “Digital Hub” quote above, it all leads to increased expectations on our OSS/BSS.

Pressure is coming at our OSS from all angles, and with no signs of abating.

To quote Queen, “Pressure. Pushing down on me.Pressing down on you.”

So it seems to me there are only three broad options when planning our OSS roadmaps:

  1. We learn to cope with increased pressure (although this doesn’t seem like a viable long-term option)
  2. We reduce the size (eg functionality, transaction volumes, etc) of our OSS footprint [But have you noticed that all of our roadmaps seem expansionary in terms of functionality, volumes, technologies incorporated, etc??]
  3. We look beyond the realms of traditional OSS/BSS functionality (eg just servicing operations) and into areas of opportunity

TM Forum’s ODA White Paper goes on to state, “The growth opportunities attached to new 5G ecosystems are estimated to be worth over $580 billion in the next decade.
Servicing these opportunities requires transformation of the entire industry. Early digital transformation efforts focused on improving customer experience and embracing new technologies such as virtualization, with promises of wide-scale automation and greater agility. It has become clear that these ‘projects’ alone are not enough. CSPs’ business and operating models, choice of technology partners, mindset, decision-making and time to market must also change.
True digital business transformation is not an easy or quick path, but it is essential to surviving and thriving in the future digital market.”

BTW. I’m not suggesting 5G is the panacea or single opportunity here. My use of the quote above is drawing more heavily on the opportunities relating to digital transformation. Not of the telcos themselves, but digital transformation of their customers. If data is the oil of the 21st century, then our OSS/BSS and telco assets have the potential to be the miners and pipelines of that oil.

If / when our OSS go from being cost centres to revenue generators (directly attributable to revenue, not the indirect attribution by most OSS today), then we might feel some of the pressure easing off us.

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:

OSS change…. but not too much… oh no…..

Let me start today with a question:
Does your future OSS/BSS need to be drastically different to what it is today?

Please leave me a comment below, answering yes or no.

I’m going to take a guess that most OSS/BSS experts will answer yes to this question, that our future OSS/BSS will change significantly. It’s the reason I wrote the OSS Call for Innovation manifesto some time back. As great as our OSS/BSS are, there’s still so much need for improvement.

But big improvement needs big change. And big change is scary, as Tom Nolle points out:
IT vendors, like most vendors, recognize that too much revolution doesn’t sell. You have to creep up on change, get buyers disconnected from the comfortable past and then get them to face not the ultimate future but a future that’s not too frightening.”

Do you feel like we’re already in the midst of a revolution? Cloud computing, web-scaling and virtualisation (of IT and networks) have been partly responsible for it. Agile and continuous integration/delivery models too.

The following diagram shows a “from the moon” level view of how I approach (almost) any new project.

The key to Tom’s quote above is in step 2. Just how far, or how ambitious, into the future are you projecting your required change? Do you even know what that future will look like? After all, the environment we’re operating within is changing so fast. That’s why Tom is suggesting that for many of us, step 2 is just a “creep up on it change.” The gap is essentially small.

The “creep up on it change” means just adding a few new relatively meaningless features at the end of the long tail of functionality. That’s because we’ve already had the most meaningful functionality in our OSS/BSS for decades (eg customer management, product / catalog management, service management, service activation, network / service health management, inventory / resource management, partner management, workforce management, etc). We’ve had the functionality, but that doesn’t mean we’ve perfected the cost or process efficiency of using it.

So let’s say we look at step 2 with a slightly different mindset. Let’s say we don’t try to add any new functionality. We lock that down to what we already have. Instead we do re-factoring and try to pull the efficiency levers, which means changes to:

  1. Platforms (eg cloud computing, web-scaling and virtualisation as well as associated management applications)
  2. Methodologies (eg Agile, DevOps, CI/CD, noting of course that they’re more than just methodologies, but also come with tools, etc)
  3. Process (eg User Experience / User Interfaces [UX/UI], supply chain, business process re-invention, machine-led automations, etc)

It’s harder for most people to visualise what the Step 2 Future State looks like. And if it’s harder to envisage Step 2, how do we then move onto Steps 3 and 4 with confidence?

This is the challenge for OSS/BSS vendors, supplier, integrators and implementers. How do we, “get buyers disconnected from the comfortable past and then get them to face not the ultimate future but a future that’s not too frightening?” And I should point out, that it’s not just buyers we need to get disconnected from the comfortable past, but ourselves, myself definitely included.

In 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?

Two concepts to help ease long-standing OSS problems

There’s a famous Zig Ziglar quote that goes something like, “You can have everything in life you want, if you will just help enough other people get what they want.”

You could safely assume that this was written for the individual reader, but there is some truth in it within the OSS context too. For the OSS designer, builder, integrator, does the statement “You can have everything in your OSS you want, if you will just help enough other people get what they want,” apply?

We often just think about the O in OSS – Operations people, when looking for who to help. But OSS/BSS has the ability to impact far wider than just the Ops team/s.

The halcyon days of OSS were probably in the 1990’s to early 2000’s when the term OSS/BSS was at its most sexy and exciting. The big telcos were excitedly spending hundreds of millions of dollars. Those projects were huge… and hugely complex… and hugely fun!

With that level of investment, there was the expectation that the OSS/BSS would help many people. And they did. But the lustre has come off somewhat since then. We’ve helped sooooo many people, but perhaps didn’t help enough people enough. Just speak with anybody involved with an OSS/BSS stack and you’ll hear hints of a large gap that exists between their current state and a desired future state.

Do you mind if I ask two questions?

  1. When you reflect on your OSS activities, do you focus on the technology, the opportunities or the problems
  2. Do you look at the local, day-to-day activities or the broader industry

I tend to find myself focusing on the problems – how to solve them within the daily context on customer challenges, but the broader industry problems when I take the time to reflect, such as writing these blogs.

The part I find interesting is that we still face most of the same problems today that we did back in the 1990’s-2000’s. The same source of risks. We’ve done a fantastic job of helping many people get what they want on their day-to-day activities (the incremental). We still haven’t cracked the big challenges though. That’s why I wrote the OSS Call for Innovation, to articulate what lays ahead of us.

It’s why I’m really excited about two of the concepts we’ve discussed this week:

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.

Give me a fast OSS and I might ask you to slooooow doooown

The traditional telco (and OSS) ran at different speeds. Some tasks had to happen immediately (eg customers calling one another) while others took time (eg getting a connection to a customer’s home, which included designs, approvals, builds, etc), often weeks.

Our OSS have processes that must happen sequentially and expediently. They also have processes that must wait for dependencies, conditional events and time delays. Some roles need “fast,” others can cope with “slow.” Who wins out in this dilemma?

Even the data we rely on can transact at different speeds. For capacity planning, we’re generally interested in longer-term data. We don’t have to process at real-time. Therefore we can choose to batch process at longer cycle times and with summarised data sets. For network assurance, we’re generally interested in getting data as quick as is viable.

Today’s post is about that word, viable, and pragmatism we sometimes have to apply to our OSS.

For example, if our operations teams want to reduce network performance poll cycles from every 15 mins down to once a minute, we increase the amount of data to process by 15x. That means our data storage costs go up by 15x (assuming a flat-rate cost structure applies). The other hidden cost is that our compute and network costs also go up because we have to transfer and process 15x as much data.

The trade-off we have to make in responses to this rapid escalation of cost (when going from 15 to 1 min) is in the benefits we might derive. Can we avoid SLA (Service Level Agreement) breach costs? Can we avoid costly outages? Can we avoid damage to equipment? Can we reduce the risk of losing our carrier license?

The other question is whether our operators actually have the ability to respond to 15x as much data. Do we have enough people to respond at an increased cycle time? Do we have OSS tools that are capable of filtering what’s important and disregarding “background” activity? Do we have OSS tools that are capable of learning from every single metric (eg AI), at volumes the human brain could never cope with?

Does it make sense that we have a single platform for handling fast and slow processes? For example, do we use the same platform to process 1 minute-cycle performance data for long-term planning (batch-processed once daily) and quick-fire assurance (processed as fast as possible)?

If we stick to one platform, can our OSS apply data reduction techniques (eg selective discard of records) to get the benefits of speed, but with the cost reduction of slow?

A single glass of pain or single pane of glass??

Is your OSS a single pane of glass, or a single glass of pain?

You can tell I’m being a little flippant here. People often (perhaps idealistically) talk about OSS as being the single pane of glass (SPOG) to manage a network.

I say “idealistically” for a couple of reasons:

  1. There are usually many personas who interact with an OSS, each with vastly different user interface (UI) needs
  2. There is usually more than one OSS product in a client’s OSS suite, often from different vendors, with varying levels of integration

Where a single pane of glass can be a true ambition is as a consolidated health-status dashboard / portal, Invariably, this portal is used by executive / leader / manager personas who want to quickly see a single-screen health status that covers all networks and/or parts of the OSS suite. When things go wrong, this portal becomes the single glass of pain.

These single panes tend to be heavily customised for each organisation as every one has a unique set of metrics-that-matter. For those designing these panes, the key is to not just include vanity metrics, but to show information that the leader can action.

But the interesting perspective here is whether the single glass of pain is even relevant within your organisation’s culture. It’s just my opinion, but I prefer for coal-face workers to be empowered to make rapid recovery actions rather than requiring direction from up high in the org-chart. Coal-face workers generally have different tools with UIs that *should* help them monitor, manage and repair super-efficiently.

To get back to the “idealistic” comment above, each OSS UI needs to be fit-for-purpose for each unique persona (eg designers, product owners, network operations, etc). To me this implies that there is no single pane of glass…

I should caveat that by citing the example of an OSS search interface, something I’ve yet to see in OSS… although that’s just a front end to dozens of persona-specific panes of glass.

I sent you an OSS helicopter

There’s a fable of a man stuck in a flood. Convinced that God is going to save him, he says no to a passing canoe, boat, and helicopter that offer to help. He dies, and in heaven asks God why He didn’t save him. God says, “I sent you a canoe, a boat, and a helicopter!”
We all have vivid imaginations. We get a goal in our mind and picture the path so clearly. Then it’s hard to stop focusing on that vivid image, to see what else could work.
New technologies make old things easier, and new things possible. That’s why you need to re-evaluate your old dreams to see if new means have come along
.”
Derek Sivers
, here.

In the past, we could make OSS platform decisions with reasonable confidence that our choices would remain viable for many years. For example, in the 1990s if we decided to build our OSS around a particular brand of relational database then it probably remained a valid choice until after 2010.

But today, there are so many more platforms to choose from, not to mention the technologies that underpin them. And it’s not just the choices currently available but the speed with which new technologies are disrupting the existing tech. In the 1990s, it was a safe bet to use AutoCAD for outside plant visualisation without the risk of heavy re-tooling within a short timeframe.

If making the same decision today, the choices are far less clear-cut. And the risk that your choice will be obsolete within a year or two has skyrocketed.

With the proliferation of open-source projects, the decision has become harder again. That means the skill-base required to service each project has also spread thinner. In turn, decisions for big investments like OSS projects are based more on the critical mass of developers than the functionality available today. If many organisations and individuals have bought into a particular project, you’re more likely to get your new features developed than from a better open-source project that has less community buy-in.

We end up with two ends of a continuum to choose between. We can either chase every new bright shiny object and re-factor for each, or we can plan a course of action and stick to it even if it becomes increasingly obsoleted over time. The reality is that we probably fit somewhere between the two ends of the spectrum.

To be brutally honest I don’t have a solution to this conundrum. The closest technique I can suggest is to design your solution with modularity in mind, as opposed to the monolithic OSS of the past. That’s the small-grid OSS architecture model. It’s easier to replace one building than an entire city.

Life-cycles of key platforms are likely to now be a few years at best (rather than decades if starting in the 1990s). Hence, we need to limit complexity (as per the triple-constraint of OSS) and functionality to support the most high-value objectives.

I’m sure you face the same conundrums on a regular basis. Please leave a comment below to tell us how you overcome them.

Can OSS/BSS assist CX? We’re barely touching the surface

Have you ever experienced an epic customer experience (CX) fail when dealing a network service operator, like the one I described yesterday?

In that example, the OSS/BSS, and possibly the associated people / process, had a direct impact on poor customer experience. Admittedly, that 7 truck-roll experience was a number of years ago now.

We have fewer excuses these days. Smart phones and network connected devices allow us to get OSS/BSS data into the field in ways we previously couldn’t. There’s no need for printed job lists, design packs and the like. Our OSS/BSS can leverage these connected devices to give far better decision intelligence in real time.

If we look to the logistics industry, we can see how parcel tracking technologies help to automatically provide status / progress to parcel recipients. We can see how recipients can also modify their availability, which automatically adjusts logistics delivery sequencing / scheduling.

This has multiple benefits for the logistics company:

  • It increases first time delivery rates
  • Improves the ability to automatically notify customers (eg email, SMS, chatbots)
  • Decreases customer enquiries / complaints
  • Decreases the amount of time the truck drivers need to spend communicating back to base and with clients
  • But most importantly, it improves the customer experience

Logistics is an interesting challenge for our OSS/BSS due to the sheer volume of customer interaction events handled each day.

But it’s another area that excites me even more, where CX is improved through improved data quality:

  • It’s the ability for field workers to interact with OSS/BSS data in real-time
  • To see the design packs
  • To compare with field situations
  • To update the data where there is inconsistency.

Even more excitingly, to introduce augmented reality to assist with decision intelligence for field work crews:

  • To provide an overlay of what fibres need to be spliced together
  • To show exactly which port a patch-lead needs to connect to
  • To show where an underground cable route goes
  • To show where a cable runs through trayway in a data centre
  • etc, etc

We’re barely touching the surface of how our OSS/BSS can assist with CX.

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.

An OSS theatre of combat

Have you sat on both sides of the OSS procurement process? That is, been an OSS buyer (eg writing an RFP) and an OSS seller (eg responded to an RFP) on separate projects?

Have you noticed the amount of brain-power allocated to transferral of risk from both angles?

If you’re the buyer, you seek to transfer risk to the seller through clever RFP clauses.
If you’re the seller, you seek to transfer risk to the buyer through exclusions, risk margins, etc in your RFP response.

We openly collaborate on features during the RFP, contract formation, design and implementation phases. We’re open to finding the optimal technical solution throughout those phases.

But when it comes to risk, it’s bordering on passive-aggressive behaviour when you think about it. We’re also not so transparent or collaborative about risk in the pre-implementation phases. That increases the likelihood of combative risk / issue management during the implementation phase.

The trusting long-term relationship that both parties wish to foster starts off with a negative undercurrent.

The reality is that OSS projects carry significant risk. Both sides carry a large risk burden. It seems like we could be as collaborative on risks as we are on requirements and features.

Thoughts?

Addressing the trauma of OSS

You also have to understand their level of trauma. Your product, service or information is selling a solution to someone who is in trauma. There are different levels, from someone who needs a nail to finish the swing set in their backyard to someone who just found out they have a life-threatening disease. All of your customers had something happen in their life, where the problem got to an unmanageable point that caused them to actively search for your solution.
A buying decision is an emotional decision
.”
John Carlton
.

My clients tend to fall into three (fairly logical) categories:

  1. They’re looking to buy an OSS
  2. They’re looking to sell an OSS
  3. They’re in the process of implementing an OSS

Category 3 clients tend to bring a very technical perspective to the task. Lists of requirements, architectures, designs, processes, training, etc.

Category 2 clients tend to also bring a technical perspective to the task. Lists of features, processes, standards, workflows, etc.

Category 1 clients also tend to break down the buying decision in a technical manner. List of requirements, evaluation criteria, ranking/weighting models, etc.

But what’s interesting about this is that category 1 is actually a very human initiative. It precedes the other two categories (ie it is the lead action). And category 1 clients tend to only reach this state of needing help due to a level of trauma. The buying decision is an emotional decision.

Nobody wants to go through an OSS replacement or the procurement event that precedes it. It’s also a traumatic experience for the many people involved. As much as I love being involved in these projects, I wouldn’t wish them on anyone.

I wonder whether taking the human perspective, actively putting ourselves in the position of understanding the trauma the buyer is experiencing, might change the way we approach all three categories above?

That is, taking less of a technical approach (although that’s still important of course), but more on addressing the trauma. As the first step, do you step back to understand what is the root-cause of your customer’s unique trauma?

Do you have a nagging OSS problem you cannot solve?

On Friday, we published a post entitled, “Think for a moment…” which posed the question of whether we might be better-served looking back at our most important existing features and streamlining them rather than inventing new features to solve that have little impact.

Over the weekend, a promotional email landed in my inbox from Nightingale Conant. It is completely unrelated to OSS, yet the steps outlined below seem to be a fairly good guide for identifying what to reinvent within our existing OSS.

Go out and talk to as many people [customers or potential] as you can, and ask them the following questions:
1. Do you have a nagging problem you cannot solve?
2. What is that problem?
3. Why is solving that problem important to you?
4. How would solving that problem change the quality of your life?
5. How much would you be willing to pay to solve that problem?

Note: Before you ask these questions, make sure you let the people know that you’re not going to sell them anything. This way you’ll get quality answers.
After you’ve talked with numerous people, you’ll begin to see a pattern. Look for the common problems that you believe you could solve. You’ll also know how much people are willing to pay to have their problem solved and why.

I’d be curious to hear back from you. Do those first 4 questions identify a pattern that relates to features you’ve never heard of before or features that your OSS already performs (albeit perhaps not as optimally as it could)?

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.

My favourite OSS saying

My favourite OSS saying – “Just because you can, doesn’t mean you should.”

OSS are amazing things. They’re designed to gather, process and compile all sorts of information from all sorts of sources. I like to claim that OSS/BSS are the puppet masters of any significant network operator because they assist in every corner of the business. They assist with the processes carried out by almost every business unit.

They can be (and have been) adapted to fulfill all sorts of weird and wonderful requirements. That’s the great thing about software. It can be *easily* modified to do almost anything you want. But just because you can, doesn’t mean you should.

In many cases, we have looked at a problem from a technical perspective and determined that our OSS can (and did) solve it. But if the same problem were also looked at from business and/or operational perspectives, would it make sense for our OSS to solve it?

Some time back, I was involved in a micro project that added 1 new field to an existing report. Sounds simple. Unfortunately by the time all the rigorous deploy and transition processes were followed, to get the update into PROD, the support bill from our team alone ran into tens of thousands of dollars. Months later, I found out that the business unit that had requested the additional field had a bug in their code and wasn’t even picking up the extra field. Nobody had even noticed until a secondary bug prompted another developer to ask how the original code was functioning.

It wasn’t deemed important enough to fix. Many tens of thousands of dollars were wasted because we didn’t think to ask up the design tree why the functionality was (wasn’t) important to the business.

Other examples are when we use the OSS to solve a problem by expensive customisation / integration when manual processes can do the job more cash efficiently.

Another example was a client that had developed hundreds of customisations to resolve annoying / cumbersome, but incredibly rare tasks. The efficiency of removing those tasks didn’t come close to compensating for the expense of building the automations / tools. Just one sample of those tools was a $1000 efficiency improvement for a ~$200,000 project cost… on a task that had only been run twice in the preceding 5 years.

 

How to build a personal, cloud-native OSS sandpit

As a project for 2019, we’re considering the development of a how-to training course that provides a step-by-step guide to build your own OSS sandpit to play with. It will be built around cloud-native and open-source components. It will be cutting-edge and micro-scaled (but highly scalable in case you want to grow it).

Does this sound like something you’d be interested in hearing more about?

Like or comment if you’d like us to keep you across this project in 2019.

I’d love to hear your thoughts on what the sandpit should contain. What would be important to you? We already have a set of key features identified, but will refine it based on community feedback.

The Theory of Evolution, OSS evolution

Evolution says that biological change is a property of populations — that every individual is a trial run of an experimental combination of traits, and that at the end of the trial, you are done and discarded, and the only thing that matters is what aggregate collection of traits end up in the next generation. The individual is not the focus, the population is. And that’s hard for many people to accept, because their entire perception is centered on self and the individual.”
FreeThoughtBlog.

Have we almost reached the point where the same can be said for OSS workflows? In the past (and the present?) we had pre-defined process flows. There may be an occasional if/else decision gate, but we could capture most variants on a process diagram. These pre-defined processes were / are akin to a production line.

Process diagrams are becoming harder to lock down as our decision trees get more complicated. Technologies proliferate, legacy product lines don’t get obsoleted, the number of customer contact channels increases. Not only that, but we’re now marketing to a segment of one, treating every one of our customers as unique, whilst trying not to break our OSS / BSS.

Do we have the technology yet that allows each transaction / workflow instance to just be treated as an experimental combination of attributes / tasks? More importantly, do we have the ability to identify any successful mutations that allow the population (ie the combination of all transactions) to get progressively better, faster, stronger.

It seems that to get to CX nirvana, being able to treat every customer completely uniquely, we need to first master an understanding of the population at scale. Conversely, to achieve the benefits of scale, we need to understand and learn from every customer interaction uniquely.

That’s evolution. The benchmark sets the pattern for future workflows until a variant / mutation identifies a better benchmark to establish the new pattern for future workflows, which continues.

The production line workflow model of the past won’t get us there. We need an evolution workflow model that is designed to accommodate infinite optionality and continually learn from it.

Does such a workflow tool exist yet? Actually, it’s more than a workflow tool. It’s a continually improving loop workflow.

That’s not where to disrupt your OSS

The diagram below comes from an actual client’s functionality usage profile.
Long tail of OSS

The x-axis shows the functionality / use-cases. The y-axis shows the number of uses (it could equally represent usefulness or value).

Each big-impact demand (ie individual bars on the left-side of the graph) warrants separate investigation. The bars on the right side (ie the long tail in the red box) don’t. They might be worth investigating if we could treat some/all as a cohort though.

The left side of the graph represent the functionality / use-cases that have been around for decades. Every OSS has them. They’re so common and non-differentiated that they’re not remotely sexy. Customers / stakeholders aren’t going to be wowed by them. They’re just going to expect them. Our product developers have already delivered that functionality, have moved on and are now looking for new things to work on.

And where does the new stuff reside? Generally as new bars on the right side of the graph. That’s the law of diminishing returns territory right there! You’re unlikely to move the needle from out there.

Does this graph convince you to send your most skilled craftsmen back to do more tinkering / disrupting at the left side of the graph… as opposed to adding new features at the right side? Does it inspire you to dream up exciting cohort management techniques for the red box? Perhaps it even persuades you to cull some of the long-tail features that are chewing up lifecycle effort (eg code management, regression testing, complexity tax)?

If it does convince you, don’t forget to think about how you’re going to market it. How are you going to make the left side sexy / differentiated again? Are you going to have to prove just how much easier, cheaper, faster, more efficient, more profitable, etc it is? That brings us back to the OSS proof-of-worth discussion we had yesterday. It also brings us back to Sutton’s Law – go to where the money is.

The OSS proof-of-worth dilemma

Earlier this week we posted an article describing Sutton’s Law of OSS, which effectively tells us to go where the money is. The article suggested that in OSS we instead tend towards the exact opposite – the inverse-Sutton – we go to where the money isn’t. Instead of robbing banks like Willie Sutton, we break into a cemetery and aimlessly look for the cash register.

A good friend responded with the following, “Re: The money trail in OSS … I have yet to meet a senior exec. / decision maker in any telco who believes that any OSS component / solution / process … could provide benefit or return on any investment made. In telco, OSS = cost. I’ve tried very hard and worked with many other clever people also trying hard to find a way to pitch OSS which overcomes this preconception. BSS is often a little easier … in many cases it’s clear that “real money” flows through BSS and needs to be well cared for.”

He has a strong argument. The cost-out mentality is definitely ingrained in our industry.

We are saddled with the burden of proof. We need to prove, often to multiple layers of stakeholders, the true value of the (often intangible) benefits that our OSS deliver.

The same friend also posited, “The consequence is the necessity to establish beneficial working relationships with all key stakeholders – those who specify needs, those who design and implement solutions and those, especially, who hold or control the purse strings. [To an outsider] It’s never immediately obvious who these people are, nor what are their key drivers. Sometimes it’s ambition to climb the ladder, sometimes political need to “wedge” peers to build empires, sometimes it’s necessity to please external stakeholders – sometimes these stakeholders are vendors or government / international agencies. It’s complex and requires true consultancy – technical, business, political … at all levels – to determine needs and steer interactions.

Again, so true. It takes more than just technical arguments.

I’m big on feedback loops, but also surprised at how little they’re used in telco – at all levels.

  • We spend inordinate amounts of time building and justifying business cases, but relatively little measuring the actual benefits produced after we’ve finished our projects (or gaining the learnings to improve the next round of business cases)
  • We collect data in our databases, obliviously let it age, realise at some point in the future that we have a data quality issue and perform remedial actions (eg audits, fixes, etc) instead of designing closed-loop improvement cycles that ensure DQ isn’t constantly deteriorating
  • We’re great at spending huge effort in gathering / arguing / prioritising requirements, but don’t always run requirements traceability all the way into testing and operational rollout.
  • etc

Which leads us back to the burden of proof. Our OSS have all the data in the world, but how often do we use it to justify and persuade – to prove?

Our OSS products have so many modules and technical functionality (so much of it effectively duplicated from vendor to vendor). But I’ve yet to see any vendor product that allows their customer, the OSS operators, to automatically gather proof-of-worth stats (ie executive-ready reports). Nor have I seen any integrator build proof-of-worth consultancy into their offer, whereby they work closely with their customer to define and collect the metrics that matter. BTW. If this sounds hard, I’d be happy to discuss how I approach this task.

So let me leave you with three important questions today:

  1. Have you also experienced the overwhelming burden of the “OSS = cost” mentality
  2. If so, do you have any suggestions / experiences on how you’ve overcome it
  3. Does the proof-of-worth product functionality sound like it could be useful (noting that it doesn’t even have to be a product feature, but a custom report / portal using data that’s constantly coursing through our OSS databases)