Category Archives: Simplification

Minimise the tentacles on the OctopOSS. Keep it simple

OSS answers that are simple but wrong vs complex but right

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“We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard, because that goal will serve to organize and measure the best of our energies and skills…”
John F Kennedy.

Let’s face it. The business of running a telco is complex. The business of implementing an OSS is complex. The excitement about working in our industry probably stems from the challenges we face, but the impact we can make if/when we overcome them.

The cartoon below tells a story about telco and OSS consulting (I’m ignoring the “Science vs everything else” box for the purpose of this post, focusing only on the simple vs complex sign-post).

Simple vs Complex

I was recently handed a brochure from a consulting firm that outlined a step-by-step transformation approach for comms service providers of different categories. It described quarter-by-quarter steps to transform across OSS, BSS, networks, etc. Simple!

The problem with their prescriptive model was that they’d developed a stereotype for each of the defined carrier categories. By stepping through the model and comparing against some of my real clients, it was clear that their transformation approaches weren’t close to aligning to any of those clients’ real situations.

Every single assignment and customer has its own unique characteristics, their own nuances across many layers. Nuances that in some cases are never even visible to an outsider / consultant. Trying to prepare generic, but prescriptive transformation models like this would seem to be a futile exercise.

I’m all for trying to bring repeatable methodologies into consulting assignments, but they can only act as general guidelines that need to be moulded to local situations. I’m all for bringing simplification approaches to consultancies too, as reflected by the number of posts that are categorised as “Simplification” here on PAOSS. We sometimes make things too complex, so we can simplify, but this definitely doesn’t imply that OSS or telco transformations are simple. There is no one-size-fits-all approach.

Back to the image above, there’s probably another missing arrow – Complex but wrong! And perhaps another answer with no specific path – Simple, but helpful in guiding us towards the summit / goal.

I can understand why telcos get annoyed with us consultants telling them how they should run their business, especially consultants who show no empathy for the challenges faced.

But more on that tomorrow!

That’s not where to disrupt your OSS

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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.

OSS’ Rosetta Stone

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When working on OSS projects, I find that linking or reference keys are so valuable at so many levels. Not just data management within the OSS database, but project management, design activities, task assignment / delivery, etc.

People might call things all sorts of different names, which leads to confusion.

Let me cite an example. When a large organisation has lots of projects underway and many people are maintaining project lists, but each with a slightly (or massively!!) different variant of the project name, there can be confusion, and possibly duplication. But introduce a project number and it becomes a lot easier to compare project lists (if everyone cites the project number in their documentation).

Trying to pattern match text / language can be really difficult. But if data sets have linking keys, we can easily use Excel’s vlookup function (or the human brain, or any other equivalent tool of choice) to make comparison a whole lot easier.

Linking keys could be activity codes in a WBS, a device name in a log file, a file number, a process number, part numbers in a designer’s pick-lists, device configuration code, etc.

Correlation and reconcile tasks are really important in OSS. An OSS does a lot of data set joins at application / database level. We can take a lead from code-level use of linking keys.

Just like the Rosetta stone proved to be the key to unlocking Egyptian hieroglyphs, introducing linking keys can be useful for translating different “languages” at many levels in OSS projects.

Cannibalisation intrigues me

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We’ve all heard the Kodak story. They invented digital cameras but stuck them in a drawer because it was going to cannibalise their dominant position in the photographic film revenue stream… eventually leading to bankruptcy.

Swisscom invented an equivalent of WhatsApp years before WhatsApp came onto the market. It allowed users (only Swisscom users, not external / global customers BTW) to communicate via a single app – calls, chat, pictures, videos, etc. Swisscom parked it because it was going to cannibalise their voice and SMS revenue streams. That product, iO, is now discontinued. Meanwhile, WhatsApp achieved an exit of nearly $22B by selling to Facebook.

Some network operators are baulking at offering SD-WAN as it may cannibalise their MPLS service offerings. It will be interesting to see how this story plays out.

What also intrigues me is where cannibalisation is going to come for the OSS industry. What is the format of network operationalisation that’s simpler, more desirable to customers, probably cheaper, but completely destroys current revenue models? Do any of the vendors already have such capability but have parked it in a drawer because of revenue destruction?

History seems to have proven that it’s better to cannibalise your own revenues than allow your competitors to do so.

Is your data getting too heavy for your OSS to lift?

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“Data mass is beginning to exhibit gravitational properties – it’s getting heavy – and eventually it will be too big to move.”
Guy Lupo in this article on TM Forum’s Inform that also includes contributions from George Glass and Dawn Bushaus.

Really interesting concept, and article, linked above.

The touchpoint explosion is helping to make our data sets ever bigger… and heavier.

In my earlier days in OSS, I was tasked with leading the migration of large sets of data into relational databases for use by OSS tools. I was lucky enough to spend years working on a full-scope OSS (ie it’s central database housed data for inventory management, alarm management, performance management, service order management, provisioning, etc, etc).

Having all those data sets in one database made it incredibly powerful as an insight generation tool. With a few SQL joins, you could correlate almost any data sets imaginable. But it was also a double-edged sword. Firstly, ensuring that all of the sets would have linking keys (and with high data quality / reliability) was a data migrator’s nightmare. Secondly, all those joins being done by the OSS made it computationally heavy. It wasn’t uncommon for a device list query to take the OSS 10 minutes to provide a response in the PROD environment.

There’s one concept that makes GIS tools more inherently capable of lifting heavier data sets than OSS – they generally load data in layers (that can be turned on and off in the visual pane) and unlike OSS, don’t attempt to stitch the different sets together. The correlation between data sets is achieved through geographical proximity scans, either algorithmically, or just by the human eye of the operator.

If we now consider real-time data (eg alarms/events, performance counters, etc), we can take a leaf out of Einstein’s book and correlate by space and time (ie by geographical and/or time-series proximity between otherwise unrelated data sets). Just wondering – How many OSS tools have you seen that use these proximity techniques? Very few in my experience.

BTW. I’m the first to acknowledge that a stitched data set (ie via linking keys such as device ID between data sets) is definitely going to be richer than uncorrelated data sets. Nonetheless, this might be a useful technique if your data is getting too heavy for your OSS to lift (eg simple queries are causing minutes of downtime / delay for operators).

Presence vs omni-presence and the green button of OSS design

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In OSS there are some tasks that require availability (the green button on communicator). The Network Operations Centre (NOC) is one. But does it require on-site presence in the NOC?

An earlier post showed how wrong I was about collaboration rooms. It seems that ticket flicking (and perhaps communication tools like slack) is the preferred model. If this is the preferred model, then perhaps there is no need for a NOC… perhaps only a DR NOC (Disaster Recover NOC).

“Truth is, there are hardly any good reasons to know if someone’s available or away at any given moment. If you truly need something from someone, ask them. If they respond, then you have what you needed. If they don’t, it’s not because they’re ignoring you – it’s because they’re busy. Respect that! Assume people are focused on their own work.
Are there exceptions? Of course. It might be good to know who’s around in a true emergency, but 1% occasions like that shouldn’t drive policy 99% of the time. ”
Jason Fried on Signal v Noise

Customer service needs availability. But with a multitude of channels (for customers) and collaboration tools (for staff*), it decreasingly needs presence (except in retail outlets perhaps). You could easily argue that contact centres, online chat operators, etc don’t require presence, just availability.

The one area where I’m considering the paradox of presence is in OSS design / architecture. There are often many facets of a design that require multiple SMEs – OSS application, security, database, workflow, user-experience design, operations, IT, cloud etc.

When we get many clever SMEs in the one room, they often have so many ideas and so much expertise that the design process resembles an endless loop. Presence seems to inspire omnipresence (the need to show expertise across all facets of the design). Sometimes we achieve a lot in these design workshops. Sometimes we go around in circles almost entirely because of the cleverness of our experts. They come up with so many good ideas we end up in paralysis by analysis.

The idea I’m toying with is how to use the divide and conquer theory – being able to carve up areas of responsibility and demarcation points to ensure each expert focuses on their area of responsibility. Having one expert come up with their best model within their black box of responsibility and connecting their black box with adjacent demarcation points. The benefits are also the detriments. The true double-edged sword. The benefits are having one true expert work through the options within the black box. The detriments are having only one expert work through the options within the black box.

There are some past projects that I wished I’d tried to inspire the divide and conquer approach in hindsight. In others, the collaboration model has worked extremely well.

But to get back to presence, I wonder whether thrashing up front to define black boxes and demarcation points then allows the experts to do their thing remotely and become less inclined to analyse and opine on everyone else’s areas of expertise.

* I use the term staff to represent anyone representing the organisation (staff, contractor, consultant, freelancer, etc)

Intent to simplify our OSS

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The left-hand panel of the triptych below shows the current state of interactions with most OSS. There are hundreds of variants inbound via external sources (ie multi-channel) and even internal sources (eg different service types). Similarly, there are dozens of networks (and downstream systems), each with different interface models. Each needs different formatting and integration costs escalate.
Intent model OSS

The intent model of network provisioning standardises the network interface, drastically simplifying the task of the OSS and the variants required for it to handle. This becomes particularly relevant in a world of NFVs, where it doesn’t matter which vendor’s device type (router say) can be handled via a single command intent rather than having separate interfaces to each different vendor’s device / EMS northbound interface. The unique aspects of each vendor’s implementation are abstracted from the OSS.

The next step would be in standardising the interface / data model upstream of the OSS. That’s a more challenging task!!

Telco services that are bigger, faster, better and the OSS that supports that

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We all know of the tectonic shifts in the world of telco services, profitability and business models.

One common trend is for telcos to offer pipes that are bigger and faster. Seems like a commoditising business model to me, but our OSS still need to support that. How? Through enabling efficiency at scale. Building tools, GUIs, workflows, integrations, sales pipelines, etc that enable telcos march seamlessly towards offering ever bigger/faster pipes. An OSS/BSS stack that supports this could represent one of the few remaining sustainable competitive advantages, so any such OSS/BSS could be highly valuable to its owner.

But if the bigger/faster pipe model is commoditising and there’s little differentiation between competing telcos’ OSS/BSS on service activation, then what is the alternative? Services that are better? But what is “better”? More to the point, what is sustainably better (ie can’t be easily copied by competitors)? Services that are “better” are likely to come in many different forms, but they’re unlikely to be related to the pipe (except maybe reliability / SLA / QoS). They’re more likely to be in the “bundling,” which may include premium content, apps, customer support, third-party products, etc. An OSS/BSS that is highly flexible in supporting any mix of bundling becomes important. Product / service catalogs are one of many possible examples.

An even bigger differentiator is not bigger / faster / better, but different (if perceived by the market as being invaluably different). The challenge with being different is that “different” tends to be fleeting. It tends to only last for a short period of time before competitors catch up. Since many of the differences available to telco services are defined in software, the window of opportunity is getting increasingly short… except when it comes to the OSS/BSS being able to operationalise that differentiator. It’s not uncommon for a new feature to take 9+ months to get to market, with changes to the OSS/BSS taking up a significant chunk of the project’s critical path. Having an OSS/BSS stack that can repeatedly get a product / feature to market much faster than competing telcos provides greater opportunity to capture the market during the window of difference.

Facebook’s algorithmic feed for OSS

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“This is the logic that led Facebook inexorably to the ‘algorithmic feed’, which is really just tech jargon for saying that instead of this random (i.e. ‘time-based’) sample of what’s been posted, the platform tries to work out which people you would most like to see things from, and what kinds of things you would most like to see. It ought to be able to work out who your close friends are, and what kinds of things you normally click on, surely? The logic seems (or at any rate seemed) unavoidable. So, instead of a purely random sample, you get a sample based on what you might actually want to see. Unavoidable as it seems, though, this approach has two problems. First, getting that sample ‘right’ is very hard, and beset by all sorts of conceptual challenges. But second, even if it’s a successful sample, it’s still a sample… Facebook has to make subjective judgements about what it seems that people want, and about what metrics seem to capture that, and none of this is static or even in in principle perfectible. Facebook surfs user behaviour..”
Ben Evans here.

Most of the OSS I’ve seen tend to be akin to Facebook’s old ‘chronological feed’ (where users need to sift through thousands of posts to find what’s most interesting to them).

The typical OSS GUI has thousands of functions (usually displayed on a screen all at once – via charts, menus, buttons, pull-downs, etc). But of all of those available functions, any given user probably only interacts with a handful.
Current-style OSS interface

Most OSS give their users the opportunity to customise their menus, colour schemes, even filters. For some roles such as network ops, designers, order entry operators, there are activity lists, often with sophisticated prioritisation and skills-based routing, which starts to become a little more like the ‘algorithmic feed.’

However, unlike the random nature of information hitting the Facebook feed, there is a more explicit set of things that an OSS user is tasked to achieve. It is a little more directed, like a Google search.

That’s why I feel the future OSS GUI will be more like a simple search bar (like Google) that will provide a direction of intent as well as some recent / regular activity icons. Far less clutter than the typical OSS. The graphs and activity lists that we know and love would still be available to users, but the way of interacting with the OSS to find the most important stuff quickly needs to get more intuitive. In future it may even get predictive in knowing what information will be of interest to you.
OSS interface of the future

Are we better off waiting for OSS technology to catch up?

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Yesterday’s post discussed Dave Duggal’s concept of 20th century OSS being all about centralizing command and control to gain efficiency through vertical integration and mass standardization, whilst 21st century OSS are about decentralization – gaining efficiency through horizontal integration of partner ecosystems and mass customization.

We talked about transitioning from a telco market driven by economies of scale (the 20th century benchmark) to a “market of one” (21st century target state), where fully personalised experience exists and is seamless across all channels.

Dave wrote the original article back in 2016. Two years on and some of the technology in our OSS is just starting to catch up to Dave’s concepts. To be completely honest, we still haven’t architected or built the decentralised OSS that truly offer wide-scale partner ecosystems or customer personalisation, particularly at a scale that is cost-viable.

So I’m going to ask a really pointed question. If our OSS are still better suited to 20th century markets and can’t handle the incalculable number of variants that come with a fully personalised customer experience, are we better off waiting for the technology to catch up before trying to build business models that cater to the “market of one?”

Why? Well, as Gadi Solotorevsky, Chief Technology Officer, cVidya in this post on TM Forum’s Inform says, “…digital customers aren’t known for their patience and or tolerance for errors (I should know – I’m one of them). And any serious glitch, e.g. an error in charging, will not only push them towards a competitor – did I mention how easy is to change digital service providers? It will probably find also its way to social media, causing a ripple effect. The same goes for the partners who are enabling operators to offer cool digital services in the first place.”

Better to have a business model that is simpler and repeatable / reliable at massive scale than attempt a 21st century model where it’s the fall-outs that are scaling.

I’d love to hear your thoughts.

BTW. Kudos to those organisations investing in the bleeding edge tech that are attempting to solve what Dave refers to as “the challenge of our times.” I’m certainly not going to criticise their bold efforts. Just highlighting the point that many operators have 21st century ambitions of their OSS whilst only having 20th century capabilities currently.

OSS feature parity. A functionality arms race

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OSS Vendor 1. “I have 1 million features.” (Dr Evil puts finger in mouth)
OSS Vendor 2. “Yeah, well I have 1,000,001 features in my OSS.”

This is the arms-race that we see in OSS, just like almost any other tech product. I imagine that vendors get into this arms-race because they wish to differentiate. Better to differentiate on functionality than price. If there’s a feature parity, then the only differentiator is price. We all know that doesn’t end well!

But I often ask myself a few related questions:

  • Of those million features, how many are actually used regularly
  • As a vendor do you have logging that actually allows you to know what features are being used
  • Taking the Whale Curve perspective, even if being used, how many of those features are actually contributing to the objectives of the vendor
    • Do they clearly contribute towards making sales
    • Do customers delight in using them
    • Would customers be irate if you removed them
    • etc

Earlier this week, I spoke about a friend who created an alarm management tool by himself over a weekend. It didn’t have a million features, but it did have all of what I’d consider to be the most important ones. It did look like a lot of other alarm managers that are now on the market. The GUI based on alarm lists still pervades.

If they all look alike, and all have feature parity, how do you differentiate? If you try to add more features, is it safe to assume that those features will deliver diminishing returns?

But is an alarm list and the flicking of tickets the best way to manage network health?

What if, instead of seeking incremental improvement, someone went back to the most important requirements and considered whether the current approach is meeting those customer needs? I have a strong suspicion that customer feedback will indicate that there are definitely flaws to overcome, especially on high event volume networks.

Clever use of large data volumes provides a level of pre-cognition and automation that wasn’t available when simple alarm lists were first invented. This in turn potentially changes the way that operators can engage with network monitoring and management.

What if someone could identify a whole new user interface / approach that overcame the current flaws and exceeded the key requirements? Would that be more of a differentiator than adding a 1,000,002nd feature?

If you’re looking for a comparison, there were plenty of MP3 players on the market with a heap of features, many more than the iPod. We all know how that one played out!

Pitching an OSS? Don’t call it OSS.

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““If you asked me how to sell cybersecurity, I wouldn’t call it cybersecurity.” The raw truth of the statement hit me like a lightning bolt between the eyes. Cybersecurity might loosely describe what we do, and we tell people it’s what we’re selling, but it’s not what people buy.
Safety. Assurance. Peace of mind. Confidence. These are the kinds of things that people buy, concepts which ordinary people can understand and relate to because they are feelings which they have experienced themselves. Cybersecurity is not a next gen firewall, or multi-layered endpoint protection with machine learning and threat sandbox technology. Cybersecurity is not risk management or ISO27001 policies. Cybersecurity is being able to use the Internet in any way I can imagine without having to worry I might lose my family photos, get robbed, or get in trouble with my boss. If you could (honestly) sell me “worry free Internet”, I’d buy it in a heartbeat, and so would everyone you know.”
Corch X, here.

Sound familiar?
If you asked me how to sell OSS, I wouldn’t call it OSS. Doh! Now you enlighten me… after I’ve already chosen the domain name, PassionateAboutOSS.com. After I’ve already written over 2,000 posts on topics like orchestration, microservices, cloud-native, DevOps, and every other technical buzzword. Time to start again from scratch.

One thing in my favour is that you, the audience I’m interacting with, also speaks in the same jargon. These are the terms we use to communicate with each other. To get things started. To get things done. To get things delivered.

That’s all fine if we’re only interacting with like-minded OSS experts. However, of the thousands of people who interact with our OSS / BSS, only a small percentage are OSS experts. A majority of people use the tools rather than designing, building or commissioning them.

The people who use the tools have a huge range of job roles and reasons for needing to use our OSS / BSS. Just like with cybersecurity, the core reasons could be Safety. Assurance. Peace of mind. Confidence. But they might also include Speed. Efficiency. Reliability. Repeatability. Simplicity. Monetisation. Insightful. And more.

The challenge we have is that so much of the benefit that our OSS and BSS deliver is intangible. We might talk about orchestration delivering speed, simplicity, reliability, etc. But how do we establish a more tangible link?

How do we achieve the equivalent of what the “Intel Inside” marketing ploy delivered, which made people associate an otherwise obscure integrated circuit with a premium feature to consider when they bought their next computing device. How do we ensure that people know that our OSS / BSS is the master of puppets that make our networks dance? It’s our OSS / BSS that are pulling all the strings of operationalisation, connecting customers with networks.

Would an EoL be beneficial for OSS?

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In the world of networking, it’s common for devices to go EOL (end-of-life). Capital spend and depreciation models are based around refresh cycles of around 5-7 years. Vendors reinforce this refresh cycle by designing obsolescence into maintenance, support and part supplies. Customers tend to simply submit to the risk of having no vendor support by buying the next generation replacements.

But how often do you hear of an OSS going EOL? Not often right? They tend to get written off only when the cost of upkeep outweighs new revenues.

I know, I can hear you saying that software is different from hardware and of course I agree with you. I’d partially counter by claiming that software architectures and development platforms also have a discernibly useful life just like physical network devices. If you doubt that, I’m sure you’ve seen OSS tools with origins in the 1990s that are still being developed upon. I tend to believe that product usefulness becomes asymptotic for its vendors. With the speed of change and proliferation of new platforms, useful lives are getting ever-shorter.

Would a pre-ordained product replacement life-cycle be beneficial for the OSS industry? It has some merits.

For a start, planned obsolescence enforces designs with interchangeability, in line with the small-grid OSS described yesterday. It promotes short-term enhancements to long-term visions. It becomes easier for customers to write off their investment and inject new capital into the vendor market. It penalises the amount of Frankenstein integrations that tend to become increasingly burdensome (to vendor and customer) into the future. It enforces those mythical beasts of telco software – subtraction projects. It promotes innovation to avoid the asymptotic benefit deterioration curve shown below:
Asymptotic OSS feature development

As the asymptote is being reached, a new jumping-off point commences with the new product.

But it’s a difficult status-quo to break. Vendors have invested millions of developer hours into their products. Taking a product EoL is effectively throwing that invested effort away. For carriers, it means the risk and cost of breaking integrations / processes and replacing them with new ones.

I’d love to hear your thoughts on whether an EOL model might be relevant / useful for your OSS.

The future of work and its impact on OSS

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Many years ago, I worked on a seriously big OSS transformation for one of the region’s biggest telcos. Everything was big on the project, the investment, the resources, the documentation. Everything except the outcomes. There was so much inefficiency that I often spoke about making one day of progress for every ten on site. Meetings, bureaucracy, impossible approval cycles, customer re-organisations, over-analysis, etc all added up to stagnation.

This contrasted so much with some of the amazing small teams I’ve worked alongside. Teams that worked cohesively, cleverly and just got stuff done with almost no resources. It’s one of the reasons I feel that the future of work, even for the very large organisations, will be via small teams. Outsourced to small, efficient teams / organisations. The gig economy, and the proliferation of tools that support it, make it an obvious approach to take, especially for very large organisations to leverage. Proof of work technologies, such as those building upon the discovery of blockchain, will provide further impetus to use smaller teams of experts.

Experts like a friend and colleague of mine who once built an alarm management tool in a weekend, by himself. It also happened to be more sophisticated than his employer’s existing tool that had taken years of combined developer effort by a larger team.

Maybe I’ll be proven wrong, but I see the transition to this model of work as being inevitable. The question I have is how to make our OSS more accommodating of this work model. Behemoth OSS stacks won’t. Highly modular OSS made up of many smaller components probably will, as long as they don’t succumb to the OSS chessboard analogy. The pulleys and strings will make it impossible for small, interchangable teams to decipher and manage.

A small-grid OSS model is the one I’d be backing in.

OSS – like a duck on a pond

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Let’s start with a basic question. “What does an OSS need to do?”

The basic answer is, “make operations easier.”

The real answer(s) is so much more nuanced than that of course. The term easier can also encapsulate other words such as faster, more accurate, more repeatable, cheaper, etc.

Designing, building, operating and maintaining a sizable network is extremely challenging, despite network operators around the world, and the vendors that supply to them, employing some of the best and brightest. So we design OSS and related tools / processes to make operations easier.

Yet I sometimes wonder whether we achieve that aim – to make operations easier. Seems to me that we tend to focus more on just replicating functions at a higher layer in the management stack. That is, moving the function to the OSS rather than EMS/NMS, without really making it much easier operationally.

Let’s start at the user interface (UI). How often are they intuitive enough for an experienced network operator to start doing tasks with negligible OSS expert guidance?
Let’s look at deployments. How often are the projects low on effort, risk, cost and complexity?
Let’s look at flexibility (ie in-flight modifications or transformations). How often do we actually deliver flexibility to our customers through our OSS. To ask the same as above, how often are our changes low on effort, risk, cost and complexity?

As a small step towards providing an answer, I wonder whether it’s a case of making the hard things look easy and the easy things look hard.

We want to make the really hard operational things much easier to do within an OSS because that’s the primary purpose of an OSS. That’s the example of a duck on a pond. The OSS is gliding along effortlessly across the top of the water, but under the water it is paddling furiously.

Conversely, we want to make the really easy* operational things look hard to do within an OSS so that we’re not constantly being asked to build functionality / complexity into our OSS that doesn’t warrant being there. It diffuses the intent of the OSS. Just because we can, doesn’t mean we should.

For fear of OSS investment

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Friday’s post discussed three analogies about the challenges of performing an OSS pivot.

The biggest challenge in initiating the transformation / replacement of any significant OSS is fear. There are many OSS out there whose “owners” want to change and need to change… but fear changing because a significant pivot would mean a “sell the farm” decision.

The fear is completely understandable. These are highly complex projects with so many potential pitfalls that invest massive amounts of resource (time, money, people). The risks can be huge for sponsors / stakeholders / investors. Failure of these projects can be career changing. The upside potential rarely balances the downside risk.

So, the only choice we have is to present pivots that aren’t “bet the farm” decisions.

The delivery approach of a bet the farm pivot tends to look like this:
The Bet-the-farm OSS Transformation Approach

The less risky, dependency-reduced, stepping-stone transformation tends to look a bit like this, but probably with a lot more verticals, as described here:
The Stepping-Stone OSS Transformation Approach

Do the laws of physics prevent you from making an OSS pivot?

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AIrcraft carrier
Image linked from GCaptain.com.

As you already know, the word pivot has become common in the world of business, particularly the world of start-ups. It’s a euphemism for a significant change in strategic direction. In the context of today’s post, I love the word pivot because it implies a rapid change in direction, something that’s seemingly impossible for most of our OSS and the customers who use them.

I like to use analogies. It’s no coincidence that some of the analogies posted here on PAOSS relate to the challenge in making strategic change in our OSS. Here are just three of those analogies:

The OSS intertia principle relates classical physics with our OSS, where Force equals Mass x Acceleration (F = ma). In other words, the greater the mass (of your OSS), the more force must be applied to reach a given acceleration (ie to effect a change)

The OSS chess-board analogy talks about the rubber bands and pulleys (ie integrations) that enmesh the pieces on our OSS chessboard. This means that other pieces get dragged out of position whenever we try to move any individual piece and chaos ensues.

The aircraft carrier analogy compares OSS (and the CSPs they service) with navies of old. In days gone by, CSPs enjoyed command of the sea. Their boats were big, powerful and mobile enough to move around world. However, their size requires significant planning to change course. The newer application and content communications models are analogous to the advent of aviation. The over the top (OTT) business model has the speed, flexibility, lower cost base and diversity of aircraft. Air supremacy has changed the competitive dynamic. CSPs and our OSS can’t quickly change from being a navy to being an airforce, so the aircraft carrier approach looks to the future whilst working within the constraints of the past.

When making day to day changes within, and to, your OSS does the ability to pivot ever come to mind?

Do you intentionally ensure it stays small, modular and limit its integrations to simplify your game of OSS chess?
If constrained by existing mass that you simply can’t eliminate, do you seek to transform via OSS‘s aviation equivalents?
Or like many of the OSS around the world, are you just making them larger, enmeshed behemoths that will never be able to change the laws of physics and achieve a pivot?

Do any of our global target architectures represent such behemoths?

Falsely rewarding based on OSS existence rather than excellence

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There’s a common belief that most jobs see people rewarded for presence rather than performance. That is, they’re encouraged to be on site from 9am to 5pm rather than being given free reign over their work schedules as long as key outcomes are met / exceeded.

In OSS vendor / product selection there’s a similar concept. Contracts are often awarded based on existence rather than excellence. When evaluating a product, if it’s able to do a majority of the functions in the long list of requirements then the box is ticked.

However, this doesn’t take into account that there are usually only a very small number of functions that any given customer’s OSS needs to perform at a very high level of efficiency. All the others are effectively just nice to have. That’s the 80/20 rule at work.

When guiding a customer through their vendor selections, I always take them through an exercise to identify the use-cases / functions that really matter. Then we ensure that the demos or proofs of concept focus closely on how excellent the OSS is at those most important factors.

OSS automations – just because we can, doesn’t mean we should

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Automation is about using machines / algorithms to respond faster than humans can, or more efficiently than humans can, or more accurately than humans can… but only if the outcomes justify the costs. When it comes to automations, it’s a case of, “just because we can, doesn’t mean we should.”

The more complex the decision tree you’re trying to automate, the higher the costs and therefore the harder it becomes to cost-justify. So the first step in any automation is taking a lateral thinking approach to simplifying the decision tree.

This recent post highlighted a graph from Nokia’s Bell Labs and the financial dependency that network slicing has on operational automation:
Nokia Network Slicing

Let’s use the Toyota Five Whys technique to work our way through the implications of this:

Statement 0: As CSPs, we need to drastically reduce complexity in the processes / decision-trees across our whole organisation.

Why 1? So that we can apply significant levels of automation

Why 2? So that we can apply technologies / techniques such as network slicing or virtualisation that are cost-justifiable

Why 3? So that we can offer differentiated, premium services

Why 4? So that our offerings don’t become commodities

Why 5? So that we retain corporate profitability to return to shareholders and/or invest in further interesting projects

I love that we’re looking to all number of automation technologies / techniques to apply to our OSS. However, we’re bypassing the all-important statement 0. We’re starting at Why 1 and partially missing the cost-justifiable part of Why 2. If our automation projects don’t prove cost-justifiable, then we never get the chance to reach whys 3, 4 and 5.

OSS that are profitable, difficult, or important?

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“Apple became the first company to be worth a trillion dollars. They did that by spending five years single-mindedly focusing on doing profitable work. They’ve consistently pushed themselves toward high margin luxury goods and avoided just about everything else. Belying their first two decades, when they focused on breakthrough work that was difficult and perhaps important, nothing they’ve done recently has been either…
Profitable, difficult, or important — each is an option. A choice we get to make every day. ‘None of the above’ is also available, but I’m confident we can seek to do better than that. ”
Seth Godin in this post.

I encourage you to view the entire post at the link above. It gives definitions (and examples) of organisations that focus on profitable, difficult or important activities.

In OSS, the organisations that focus on the profitable are the ones investing heavily on glossy sales / marketing and only making incremental improvements to products that have been around for years.

Then there are others that are doing the difficult and innovative and complex work (ie the sexy work for all of us tech-heads). This recent article about ONAP talks about the fantastic tech-driven ambitions of that program, but then distills it down to the business objectives.

That leaves us with the important – the business needs / objectives – and this is where the customers come in. Speak with any OSS customer (or customer’s customer for that matter) and you’ll tend to find frustrations with their OSS. Frustration with complexity, time to deliver / modify, cost to deliver / modify, risks, functionality constraints, etc.

This is a simplification of course, but do you notice that as an industry, our keen focus on the profitable and difficult might just be holding us back from doing the important?