Dan Pink’s 6 critical OSS senses

I recently wrote an article that spoke about the obsolescence of jobs in OSS, particularly as a result of Artificial Intelligence.

But an article by someone much more knowledgeable about AI than me, Rodney Brooks, had this to say, “We are surrounded by hysteria about the future of artificial intelligence and robotics — hysteria about how powerful they will become, how quickly, and what they will do to jobs.” He then describes The Seven Deadly Sins of AI Predictions here.

Back into my box I go, tail between my legs! Nonetheless, the premise of my article still holds true. The world of OSS is changing quickly and we’re constantly developing new automations, so our roles will inevitably change. My article also proposed some ideas on how to best plan our own adaptation.

That got me thinking… Many people in OSS are “left-brain” dominant right? But left-brained jobs (ie repeatable, predictable, algorithmic) can be more easily out-sourced or automated, thus making them more prone to obsolescence. That concept reminded me of Daniel Pink’s premise in A Whole New Mind where right-brained skills become more valuable so this is where our training should be focused. He argues that we’re on the cusp of a new era that will favor “conceptual” thinkers like artists, inventors and storytellers. [and OSS consultants??]

He also implores us to enhance six critical senses, namely:

  • Design – the ability to create something that’s emotionally and/or visually engaging
  • Story – to create a compelling and persuasive narrative
  • Symphony – the ability to synthesise new insights, particularly from seeing the big picture
  • Empathy – the ability to understand and care for others
  • Play – to create a culture of games, humour and play, and
  • Meaning – to find a purpose that will provide an almost spiritual fulfillment.

I must admit that I hadn’t previously thought about adding these factors to my development plan. Had you?
Do you agree with Dan Pink or will you continue to opt for left-brain skills / knowledge enhancement?

Bringing Eminem’s blank canvas to OSS

“When you start out in your career, you have a blank canvas, so you can paint anywhere that you want because the shit ain’t been painted on yet. And then your second album comes out, and you paint a little more and you paint a little more. By the time you get to your seventh and eighth album you’ve already painted all over it. There’s nowhere else to paint.”
Eminem. (on Rick Rubin and Malcolm Gladwell’s Broken Record podcast)

To each their own. Personally, Eminem’s music has never done it for me, whether his first or eighth album, but the quote above did strike a chord (awful pun).

It takes many, many hours to paint in the detail of an OSS painting. By the time a product has been going for a few years, there’s not much room left on the canvas and the detail of the existing parts of the work is so nuanced that it’s hard to contemplate painting over.

But this doesn’t consider that over the years, OSS have been painted on many different canvases. First there were mainframes, then client-server, relational databases, XaaS, virtualisation (of servers and networks), and a whole continuum in between… not to mention the future possibilities of blockchain, AI, IoT, etc. And that’s not even considering the changes in programming languages along the way. In fact, new canvases are now presenting themselves at a rate that’s hard to keep up with.

The good thing about this is that we have the chance to start over with a blank canvas each time, to create something uniquely suited to that canvas. However, we invariably attempt to bring as much of the old thinking across as possible, immediately leaving little space left to paint something new. Constraints that existed on the old canvas don’t always apply to each new canvas, but we still have a habit of bringing them across anyway.

We don’t always ask enough questions like:

  • Does this existing process still suit the new canvas
  • Can we skip steps
  • Can we obsolete any of the old / unused functionality
  • Are old and new architectures (at all levels) easily transmutable
  • Does the user interface need to be ported or replaced
  • Do we even need a user interface (assuming the rise of machine-to-machine with IoT, etc)
  • Does the old data model have any relevance to the new canvas
  • Do the assurance rules of fixed-network services still apply to virtualised networks
  • Do the fulfillment rules of fixed-network services still apply to virtualised networks
  • Are there too many devices to individually manage or can they be managed as a cohort
  • Does the new model give us access to new data and/or techniques that will allow us to make decisions (or derive insights) differently
  • Does the old billing or revenue model still apply to the new platform
  • Can we increase modularity and abstraction between modules

“The real reason “blockchain” or “AI” may actually change businesses now or in the future, isn’t that the technology can do remarkable things that can’t be done today, it’s that it provides a reason for companies to look at new ways of working, new systems and finally get excited about what can be done when you build around technology.”
Tom Goodwin
.

50 exercises to ignite your OSS innovation sessions

Every project starts with an idea… an idea that someone is excited enough to sponsor.

  1. But where are your ideas being generated from?
  2. How do they get cultivated and given time to grow?
  3. How do they get pitched? and How do they get heard?
  4. How are sponsors persuaded?
  5. How do they then get implemented?
  6. How do we amplify this cycle of innovation and implementation?

I’m fascinated by these questions in OSS for the reasons outlined in The OSS Call for Innovation.

If we look at the levels of innovation (to be honest, it’s probably more a continuum than bands / levels):

  1. Process Improvement
  2. Incremental Improvement (new integrations, feature enhancement, etc)
  3. Derivative Ideas (iPhone = internet + phone + music player)
  4. Quantum Innovation (Tablet computing, network virtualisation, cloud delivery models)
  5. Radical Innovations (transistors, cellular wireless networks, Claude Shannon’s Information Theory)

We have so many immensely clever people working in our industry and we’re collectively really good at the first two levels. Our typical mode of working – which could generally be considered fire-fighting (or dare I say it, Agile) – doesn’t provide the time and headspace to work on anything in the longer life-cycles of levels 3-5. These are the levels that can be more impactful, but it’s these levels where we need to carve out time specifically for innovation planning.

If you’re ever planning to conduct innovation fire-starter sessions, I really recommend reading Richard Brynteson’s, “50 Activities for Building Innovation.” As the title implies, it provides 50 (simple but powerful) exercises to help groups to generate ideas.

Please contact us if you’d like PAOSS to help facilitate your OSS idea firestarter or road-mapping sessions.

How the investment strategy of a $106 billion VC fund changed my OSS thinking

What is a service provider’s greatest asset?

Now I’m biased when considering the title question, but I believe OSS are the puppet-master of every modern service provider. They’re the systems that pull all of the strings of the organisation. They generate the revenue by operationalising and assuring the networks as well as the services they carry. They coordinate the workforce. They form the real-time sensor networks that collect and provide data, but more importantly, insights to all parts of the business. That, and so much more.

But we’re pitching our OSS all wrong. Let’s consider first how we raise revenue from OSS, be that either internal (via internal sponsors) or external (vendor/integrator selling to customers)? Most revenue is either generated from products (fixed, leased, consumption revenue models) or services (human effort).

This article from just last month ruminated, “An organisation buys an OSS, not because it wants an Operational Support System, but because it wants Operational Support,” but I now believe I was wrong – charting the wrong course in relation to the most valuable element of our OSS.

After researching Masayoshi Son’s Vision Fund, I’m certain we’re selling a fundamentally short-term vision. Yes, OSS are valuable for the operational support they provide, but their greatest value is as vast data collection and processing engines.

“Those who rule data will rule the entire world. That’s what people of the future will say.”
Masayoshi Son.

For those unfamiliar with Masayoshi Son, he’s Japan’s richest man, CEO of SoftBank, in charge of a monster (US$106 billion) venture capital fund called Vision Fund and is seen as one of the world’s greatest technology visionaries.

As this article on Fortune explains Vision Fund’s foundational strategy, “…there’s a slide that outlines the market cap of companies during the Industrial Revolution, including the Pennsylvania Railroad, U.S. Steel, and Standard Oil. The next frontier, he [Son] believes, is the data revolution. As people like Andrew Carnegie and John D. Rockefeller were able to drastically accelerate innovation by having a very large ownership over the inputs of the Industrial Revolution, it looks like Son is trying to do something similar. The difference being he’s betting on the notion that data is one of the most valuable digital resources of modern day.”

Matt Barnard is CEO of Plenty, one of the companies that Vision Fund has invested in. He had this to say about the pattern of investments by Vision Fund, “I’d say the thing we have in common with his other investments is that they are all part of some of the largest systems on the planet: energy, transportation, the internet and food.”

Telecommunications falls into that category too. SoftBank already owns significant stakes in telecommunications and broadband network providers.

But based on the other investments made by Vision Fund so far, there appears to be less focus on operational data and more focus on customer activity and decision-making data. In particular, unravelling the complexity of customer data in motion.

OSS “own” service provider data, but I wonder whether we’re spending too much time thinking about operational data (and how to feed it into AI engines to get operational insights) and not enough on stitching customer-related insight sets together. That’s where the big value is, but we’re rarely thinking about it or pitching it that way… even though it is perhaps the most valuable asset a service provider has.

Posing a Network Data Synchronisation Protocol (NDSP) concept

Data quality is one of the biggest challenges we face in OSS. A product could be technically perfect, but if the data being pumped into it is poor, then the user experience of the product will be awful – the OSS becomes unusable, and that in itself generates a data quality death spiral.

This becomes even more important for the autonomous, self-healing, programmable, cooperative networks being developed (think IoT, virtualised networks, Self-Organizing Networks). If we look at IoT networks for example, they’ll be expected to operate unattended for long periods, but with code and data auto-propagating between nodes to ensure a level of self-optimisation.

So today I’d like to pose a question. What if we could develop the equivalent of Network Time Protocol (NTP) for data? Just as NTP synchronises clocking across networks, Network Data Synchronisation Protocol (NDSP) would synchronise data across our networks through a feedback-loop / synchronisation algorithm.

Of course there are differences from NTP. NTP only tries to coordinate one data field (time) along a common scale (time as measured along a 64+64 bits continuum). The only parallel for network data is in life-cycle state changes (eg in-service, port up/down, etc).

For NTP, the stratum of the clock is defined (see image below from wikipedia).

This has analogies with data, where some data sources can be seen to be more reliable than others (ie primary sources rather than secondary or tertiary sources). However, there are scenarios where stratum 2 sources (eg OSS) might push state changes down through stratum 1 (eg NMS) and into stratum 0 (the network devices). An example might be renaming of a hostname or pushing a new service into the network.

One challenge would be the vast different data sets and how to disseminate / reconcile across the network without overloading it with management / communications packets. The other would be that format consistency. I once had a device type that had four different port naming conventions, and that was just within its own NMS! Imagine how many port name variations (and translations) might have existed across the multiple inventories that exist in our networks. The good thing about the NDSP concept is that it might force greater consistency across different vendor platforms.

Another would be that NDSP would become a huge security target as it would have the power to change configurations and because of its reach through the network.

So what do you think? Has the NDSP concept already been developed? Have you implemented something similar in your OSS? What are the scenarios in which it could succeed? Or fail?

I’m predicting the demise of the OSS horse

“What will telcos do about the 30% of workers AI is going to displace?”
Dawn Bushaus

That question, which is the headline of Dawn’s article on TM Forum’s Inform platform, struck me as being quite profound.

As an aside, I’m not interested in the number – the 30% – because I concur with Tom Goodwin’s sentiments on LinkedIn, “There is a lot of nonsense about AI.
Next time someone says “x% of businesses will be using AI by 2020” or “AI will be worth $xxxBn by 2025” or any of those other generic crapspeak comments, know that this means nothing.
AI is a VERY broad area within computer science that includes about 6-8 very different strands of work. It spans robotics, image recognition, machine learning, natural language processing, speech recognition and far more. Nobody agrees on what is and isn’t in this.
This means it covers everything from superintelligence to artificial creativity to chatbots
.”

For the purpose of this article, let’s just say that in 5 years AI will replace a percentage of jobs that we in tech / telco / OSS are currently doing. I know at least a few telcos that have created updated operating plans built around a headcount reduction much greater than the 30% mentioned in Dawn’s article. This is despite the touchpoint explosion and increased complexity that is already beginning to crash down onto us and will continue apace over the next 5 years.

Now, assuming you expect to still be working in 5 years time and are worried that your role might be in the disappearing 30% (or whatever percentage), what do you do now?

First, figure out what the modern equivalents of the horse are in the context of Warren Buffett’s quote below:

“What you really should have done in 1905 or so, when you saw what was going to happen with the auto is you should have gone short horses. There were 20 million horses in 1900 and there’s about 4 million now. So it’s easy to figure out the losers, the loser is the horse. But the winner is the auto overall. [Yet] 2000 companies (carmakers) just about failed.”

It seems impossible to predict how AI (all strands) might disrupt tech / telco / OSS in the next 5 years – and like the auto industry, more impossible to predict the winners (the technologies, the companies, the roles). However, it’s almost definitely easier to predict the losers.

Massive amounts are being invested into automation (by carriers, product vendors and integrators), so if the investments succeed, operational roles are likely to be net losers. OSS are typically built to make operational roles more efficient – but if swathes of operator roles are automated, then does operational support also become a net loser? In its current form, probably yes.

Second, if you are a modern-day horse, ponder which of your skills are transferable into the future (eg chassis building, brakes, steering, etc) and which are not (eg buggy-whip making, horse-manure collecting, horse grooming, etc). Assuming operator-driven OSS activities will diminish, but automation (with or without AI) will increase, can you take your current networks / operations knowledge and combine that with up-skilling in data, software and automation tools?

Even if OSS user interfaces are made redundant by automation and AI, we’ll still need to feed the new technologies with operations-style data, seed their learning algorithms and build new operational processes around them.

The next question is double-edged – for both individuals and telcos alike – how are you up-skilling for a future without horses?

The concept of DevOps is missing one really important thing

There’s a concept that’s building a buzz across all digital industries – you may’ve heard of it – it’s a little thing called DevOps. Someone (most probably a tester) decided to extend it and now you might even hear the #DevTestOps moniker being mentioned.

In the ultimate of undeserved acknowledgements, I even get a reference on Wikipedia’s DevOps page. It references this DevOps life-cycle diagram from an earlier post that I can take no credit for:

However, there is one really important chevron missing from the DevOps infinite loop above. Can you picture what it might be?

If I show you this time series below, does it help identify what’s missing from the DevOps infinite loop? I refer to the diagram below as The Tech-Debt Wreck
The increasing percentage of tech debt
If I give you a hint that it primarily relates to the grey band in the time series above, would that help?

Okay, okay. I’m sure you’ve guessed it already, but the big thing missing from the DevOps loop is pruning, or what I refer to as subtraction projects (others might call it re-factoring). Without pruning, the rapid release mantra of DevOps will take the digital world from t0 to t0+100 faster than at any time before in our history.

As a result, I’m advocating a variation on DevOps… or DevTestOps even… I want you to preach a revised version of the label – let’s start a movement called #DevTestPruneOps. Actually, the pruning should go at the start, before each dev / test cycle, but by calling it #PruneDevTestOps, I fear its lineage might get lost.

A summary of RPA uses in an OSS suite

This is the sixth and final post in a series about the four styles of RPA (Robotic Process Automation) in OSS.

Over the last few days, we’ve looked into the following styles of RPA used in OSS, their implementation approaches, pros / cons and the types of automation they’re best suited to:

  1. Automating repeatable tasks – using an algorithmic approach to completing regular, mundane tasks
  2. Streamlining processes / tasks – using an algorithmic approach to assist an operator during a process or as an alternate integration technique
  3. Predefined decision support – guiding operators through a complex decision process
  4. As part of a closed-loop system – that provides a learning, improving solution

RPA tools can significantly improve the usability of an OSS suite, especially for end-to-end processes that jump between different applications (in the many ways mentioned in the above links).

However, there can be a tendency to use the power of RPAs to “solve all problems” (see this article about automating bad processes). That can introduce a life-cycle of pain for operators and RPA admins alike. Like any OSS integration, we should look to keep the design as simple and streamlined as possible before embarking on implementation (subtraction projects).

RPA in OSS feedback loops

This is the fifth in a series about the four styles of RPA (Robotic Process Automation) in OSS.

The fourth of those styles is as part of a closed-loop system such as the one described here. Here’s a diagram from that link:
OSS / DSS feedback loop

This is the most valuable style of RPA because it represents a learning and improving system.

Note though that RPA tools only represent the DSS (Decision Support System) component of the closed-loop so they need to be supplemented with the other components. Also note that an RPA tool can only perform the DSS role in this loop if it can accept feedback (eg via an API) and modify its output in response. The RPA tool could then perform fully automated tasks (ie machine-to-machine) or semi-automated (Decision support for humans).

Setting up this type of solution can be far more challenging than the earlier styles of RPA use, but the results are potentially the most powerful too.

Almost any OSS process could be enhanced by this closed-loop model. It’s just a case of whether the benefits justify the effort. Broad examples include assurance (network health / performance), fulfilment / activations, operations, strategy, etc.

Using RPA as an alternate OSS integration

This is the third in a series about the four styles of RPA (Robotic Process Automation) in OSS.

The second of those styles is Streamlining processes / tasks by following an algorithmic approach to simplify processes for operators.

These can be particularly helpful during swivel-chair processes where multiple disparate systems are partially integrated but each needs the same data (ie reducing the amount of duplicated data entry between systems). As well as streamlining the process it also improves data consistency rates.

The most valuable aspect of this style of RPA is that it can minimise the amount of integration between systems, thus potentially reducing solution maintenance into the future. The RPA can even act as the integration technique where an API isn’t available or documentation isn’t available (think legacy systems here).

Onboarding outsiders as a new OSS business model

The majority of these new services [such as healthcare, content and media, autonomous vehicles, smart homes etc.] require partnerships and will be based on a platform business model where the customer is not aware of who is providing which part of the service and to be quite frankly honest, wont care. All as they will care about is the customer experience and the end-to-end delivery of their service that they have paid for. This is where the opportunity for the telco comes and we need to think beyond data!
Aaron Boasman-Patel
here on TM Forum Inform.

Are your OSS tools already integrating with third-party services?

Do your catalog / orchestration engines already call upon microservices from outside your organisation? Perhaps it’s something as simple as providing a content service bundled with a service provider’s standard bitpipe service. Perhaps it’s also bundled with an internal-facing analytics service or an outward-facing shopping cart service.

A telco isn’t going to want to (or be able to) provide all of these services but can use partnerships and catalog items to allow each unique customer to build the bundled offer they want.

This is where catalogs and microservices potentially represent a type of small-grid model. There are already many APIs from third-party providers and the catalog / orchestration tools already exist to support the model. For many telcos, it will take a slight mindset shift – to embrace partnerships (ie to discard the “not invented here” thinking); to allowing their many existing bit-pipe subscribers to sell and bill through the telco platform (embrace sell-through); to build platforms and processes to allow for simple certification and onboarding of third-parties.

If your current OSS isn’t already integrating with third-party services, is it on your roadmap? Then again, does it suit your proposed future business models?

It’s hard to do big things in a small way

it’s hard to do big things in a small way, so I suspect incumbents have more of an advantage than they do in most industries.”
Nic Brisbourne
.

The quote above came from a piece about the rise of ConstructTech (ie building houses via means such as 3D printing). However, it is equally true of the OSS industry.

Our OSS tend to be behemoths, or at least the ones I work on seem to be. They’ve been developed over many years and have millions of sunk person-hours invested in them. And they’ve been customised to each client’s business like vines wrapped around a pillar. This gives enormous incumbency power and acts as a barrier to smaller innovators having a big impact in the world of OSS.

Want an example of it being hard to do big things in a small way? Ever heard of ONAP? AT&T is a massive telco with revenues to match, committed to a more software-centric future, and has developed millions of lines of code yet it still needs the broader industry to help flesh out its vision for ONAP.

There are occasionally niche products developed but it’s definitely hard to do big things in a small way. The small grid analogy proposed earlier gives more room for the long tail of innovation, allowing smaller innovators to impact the larger ecosystem.

Write a comment below if you’d like to point out an outlier to this trend.

The two types of disruptive technologists

OSS is an industry that’s undergoing constant, and massive change. But it still hasn’t been disrupted in the modern sense of that term. It’s still waiting to have its Uber/AirBnB-moment, where the old way becomes almost obsoleted by the introduction of a new way. OSS is not just waiting, but primed for disruption.

It’s a massive industry in terms of revenues, but it’s still far from delivering everything that customers want/need. It’s potentially even holding back the large-scale service provider industry from being even more influential / efficient in the current digital communications world. Our recent OSS Call for Innovation spelled out the challenges and opportunities in detail.

Today we’ll talk about the two types of disruptive technologists – one that assists change and one that hinders.

The first disruptive technologist is a rare beast – they’re the innovators who create solutions that are distinctly different from anything else in the market, changing the market (for the better) in the process. As discussed in this recent post, most of the significant changes occurring to OSS have been extrinsic (from adjacent industries like IT or networking rather than OSS). We need more of these.

The second disruptive technologist is all too common – they’re the technologists whose actions disrupt an OSS implementation. They’re usually well-intended, but can get in the way of innovation in two main ways:
1) By not looking beyond incremental change to existing solutions
2) Halting momentum by creating and resolving a million “what if?” scenarios

Most of us probably fall into the second category more often than the first. We need to reverse that trend individually and collectively though don’t we?

Would you like to nominate someone who stands out as being the first type of disruptive technologist and why?

What is your OSS answer : question ratio?

Experts know a lot…. obviously.
They have lots of answers… obviously.

There are lots of OSS experts. Combined, they know A LOT!!

Powerful indeed, but not sure if that’s what we need right now. I feel like we’re in a bit of an OSS innovation funk. The biggest improvements in OSS are coming from outside OSS – extrinsic improvement.

Where’s the intrinsic improvement coming from? Do we need someone to shake it up (do we need everyone to shake it up?)? Do we need new thinking to identify and create new patterns? To re-organise and revolutionise what the experts already know. Or do we need to ask the massive questions that re-frame the situation for the experts?

So, considering this funky moment in time, is the real expert the one who knows lots of answers… or the person who can catalyse change by asking the best mind-shift questions?

May I ask you – As an OSS expert, are you prouder of your answers…. or your questions?

To tackle that from a different angle – What is your answer : question ratio? Are you such an important expert that your day is so full of giving brilliant answers that you have no time left to ruminate and develop brilliant questions?

If so, can we take some of your answer time back and re-prioritise it please?

In the words of Socrates, “I cannot teach anybody anything, I can only make them think.

I found a way to save ten million dollars

Yesterday’s post about egos in OSS contained the following Dilbert cartoon:
Dilbert - I found a way to save a million dollars.
It reminded me of a story from many years ago.

I was working in a developing country, advising the board of a tier-one telco on the implementation of their first-ever OSS (they’d only ever operated their networks at NMS level previously). During the analysis phase I came across some data that showed an interesting opportunity for an innovation relating to their voice Points of Interconnect (PoI).

From a back-of-a-paper napkin analysis it seemed that a ~$50-100k investment could’ve resulted in an improvement to the company’s profit by at least $10M. I ran the concept, and the numbers, past their head of switching. His response was, “I think you’re right…. but I’m not going to recommend it.”

You could say that I was a little bewildered.

He then followed with, “You have to see this from my perspective. If I recommend this project and it succeeds, I receive no benefit. I’m not due for promotion for another two years at the earliest. I will barely receive any recognition at all, certainly no financial reward. The company receives all the benefits. But if the project fails, I will be put aside, passed over for any future promotions. It would be a career killer.”

He was right. I hadn’t seen it from his perspective… still not sure that I do, but as a consultant, I was only ever passing through their corporate culture rather than having a 4-5 decade career embedded within it.

It wasn’t within my OSS scope, but I quietly mentioned it to the board. They delegated the decision back to the head of switching. The project was not recommended to proceed, not even for further analysis.

It’s interesting the human factors that come into play when project investment is under evaluation isn’t it? What human factors have you seen influence purchasing decisions?

A deeper level of OSS connection,

Yesterday we talked about the cuckoo-bird analogy and how it was preventing telcos from building more valuable platforms on top of their capital-intensive network platforms. Thanks to Dean Bubley, it gave examples of how the most successful platform plays were platforms on platforms (eg Microsoft Office on Windows, iTunes on iOS, phones on physical networks, etc).

The telcos have found it difficult to build the second layer of platform on their data networks during the Internet age to keep the cuckoo chicks out of the nest.

Telcos are great at helping customers to make connections. OSS are great at establishing and maintaining those connections. But there’s a deeper level of connection waiting for us to support – helping the telcos’ customers to make valuable connections that they wouldn’t otherwise be able to make by themselves.

In the past, telcos provided yellow pages directories to help along these lines. The internet and social media have marginalised the value of this telco-owned asset in recent years.

But the telcos still own massive subscriber bases (within our OSS / BSS suites). How can our OSS / BSS facilitate a deeper level of connection, providing the telcos’ customers with valuable connections that they would not have otherwise made?

OSS that keep the cuckoos out of the nest

The cuckoo bird is infamous for laying its eggs in other birds’ nests. The young cuckoos grow much faster than the rightful occupants, forcing the other chicks out – if they haven’t already physically knocked the other eggs overboard. (See “brood parasitism”, here).
Analogies exist quite widely in technology – a faster-growing “tenant” sometimes pushes out the offspring of the host. Arguably Microsoft’s original Windows OS was an early “cuckoo platform” on top of IBM’s PC, removing much of IBM’s opportunity for selling additional software. 

In many ways, Internet access itself has outgrown its own host: telco-provided connectivity. Originally, fixed broadband (and the first iterations of 3G mobile broadband) were supposed to support a wide variety of telco-supplied services. Various “service delivery platforms” were conceived, including IMS, yet apart from ordinary operator telephony/VoIP and some IPTV, very little emerged as saleable services.

Instead, Internet access – which started using dial-up modems and normal phone lines before ADSL and cable and 3G/4G were deployed – has been the interloping bird which has thrived in the broadband nest instead of telcos’ own services. It’s interesting to go back and look at the 2000-era projections for walled-garden, non-Internet services.

The problem is that everyone wants to be a platform player. And when you’re building and scaling a new potential platform, it’s really hard to turn down a large and influential “anchor tenant”, even if you worry it might ultimately turn out to be a Trojan Horse (apologies for the mixed metaphor). You need the scale, the validation, and the draw for other developers and partners.

This is why the most successful platforms are always the one which have one of their own products as the key user. It reduces the cannibalisation risk. Office is the anchor tenant on Windows. iTunes, iMessage and the camera app are anchors on iOS. Amazon.com is the anchor tenant for AWS.

Unfortunately, the telecoms industry looks like it will have to learn a(nother) tough lesson or two about “cuckoo platforms”.”
Dean Bubley from Disruptive Wireless.

The link above provides some really interesting perspectives from Dean in relation to OTT business models and the challenges that telcos have faced in trying to build valuable platforms to sit on top of their capital-intensive network platforms. I really recommend having a read of the full article by clicking on the link.

I loosely equate this to the OSI stack where telcos own the L1 to L2 (L3 in many cases) platform, but haven’t been so successful at creating dominant platforms in the layers above that. That’s also why there are two distinct business model categories – the traditional CSP (Communications Service Provider) that services L1 to 2/3 and acts like a utility or REIT or the more competitive DSP (Digital Service Provider). One Telco group can have both by leveraging their trillion dollar treasure chest.

Traditional OSS service the CSP (as well as some of the aspects of the DSP model) but we probably need to create some innovative new concepts if we’re going to assist our telco customers to build DSP platforms and / or to keep the cuckoos out of the nest.

Raising the OSS horizon

With the holiday period looming for many of us, we will have the head-space to reflect – on the year(s) gone and to ponder the one(s) upcoming. I’d like to pose the rhetorical question, “What do you expect to reflect on?

It’s probably safe to say that a majority of OSS experts are engaged in delivery roles. Delivery roles tend to require great problem-solving skills. That’s one of the exciting aspects of being an OSS expert after all.

There’s one slight problem though. Delivery roles tend to have a focus on the immediacy of delivery, a short-term problem-solving horizon. This generates incremental improvements like new dashboards within an existing dashboard framework, refining processes, next release software upgrades, releasing new stuff that adds to the accumulation of tech-debt, etc, etc.

That’s great, highly talented, admirable work, often exactly what our customers are requesting, but not necessarily what our industry needs most.

We need the revolutionary, not the evolutionary. And that means raising our horizons – to identify and comprehend the bigger challenges and then solving those. That is the intent of the OSS Call for Innovation – to lift our vision to a more distant horizon.

When you reflect during this holiday period, how distant will your horizon be?

PS. Upon your own reflection, are there additional big challenges or exponential opportunities that should be captured in the OSS Call for Innovation?

What in OSS does nobody agree with you on?

Peter Thiel (co-founder of PayPal, Founders Fund and many other snippets in an impressive highlights reel) asks prospective entrepreneurs to tell him something they believe is true that nobody agrees with them about.

Today I’m asking you the same question and would love to hear your answers:

What do you believe to be true in OSS that nobody else seems to agree with you on?

The exciting thing about OSS is that it has so much potential, so many opportunities to do things better. And that means so many opportunities to do things differently, to come at things from a different angle to everyone else.

After all, success comes from doing things differently.

5 principles for your OSS Innovation Lab

Corporate innovation is far more dependent on external collaboration and customer insight than having a ‘lab’.”
Andy Howard
in a fabulous LinkedIn post.

Like so many other industries, OSS is ripe for disruption through innovation. Andy Howard’s post provides a number of sobering statistics for any large OSS vendors thinking of embarking on an Innovation Lab journey as a way of triggering innovation. Andy quotes the New York Times as follows, “The last three years have seen Nordstrom, Microsoft, Disney, Target, Coca-Cola, British Airways and The New York Times either close or dramatically downsize their innovation labs. 90% of innovation labs are failing.”

He also proposes five principles for corporate innovation success (Andy’s comments are in italics, mine follow):

  1. People. Will taking people out of the business and placing them into a new department change their thinking? No way. Those successful in corporate innovation are more entrepreneurial and more customer-centered, and usually come from outside of the organisation.
    Are you identifying (and then leveraging) those with an entrepreneurial bent in your organisation?
  2. Commercial intent. Every innovation project requires a commercial forecast. To progress, a venture must demonstrate how it could ultimately generate at least €100 million in annual revenue from a market worth at least €1 billion, and promise higher profit margins than usual.
    The numbers quoted above come from Daimler’s (wildly successful) Innovation Lab. Have you noticed that they’ve set the bar high for their innovation teams? They’re seeking the moonshots, not the incremental change.
  3. Organisational architecture. Whether it’s an innovation lab or simply an innovation department, separating the innovation team from the rest of the business is important. While the team may be bound by the same organisational policies, separation has cultural benefits. The most critical separation is not in terms of physical space, but in the team’s roles and responsibilities. Having employees attempt to function in both an ‘innovation’ role and ‘business as usual’ role is counterproductive and confusing. Innovation is an exclusive job.
    I’m 50/50 on this one. Having a gemba / coal-face / BAU role provides a much better understanding of real customer challenges. However, having BAU responsibilities can detract from a focus on innovation. The question is how to find a balance that works.
  4. External collaboration. Working with consultants and customers from outside of the organisation has long been a contributor to corporate innovation success. Companies attempting a Silicon Valley-style ‘lone genius’ breakthrough are headed towards failure. P&G’s ‘Connect and Develop’ innovation model, designed to bring outside thinking together with P&G’s own teams, is attributed with helping to double the P&G share price within five years.
    Where do you source your external collaboration on OSS innovation? Dirty or clean consultants? Contractors? Training of staff? Delegating to vendors?
  5. Customer insight. Innovations solve real customer problems. Staying close to customers and getting out of the building is how customer problems are discovered.
    As indicated under point 3 above, how do you ensure your innovators are also deeply connected with the customer psyche? Getting the team out of the ivory tower and onto the customer site is a key here