Can the OSS mammoths survive extinction?

Startups win with data. Mammoths go extinct with products.”
Jay Sharma
.

Interesting phraseology. I love the play on words with the term mammoths. There are some telcos that are mammoth in size but are threatened with extinction though changes in environment and new competitors appearing.

I tend to agree with the intent of the quote, but also have some reservations. For example, products are still a key part of the business model of digital phenoms like Google, Facebook, etc. It’s their compelling products that allow them to collect the all-important data. As consumers, we want the product, they get our data. We also want the products sold by the Mammoths but perhaps they don’t leverage the data entwined in our usage (or more importantly, the advertising revenues that gets attracted to all that usage) as well as the phenoms do.

Another interesting play on words exists here for the telcos – in the “winning with data.” Telcos are losing at data (their profitability per bit is rapidly declining to the point of commoditisation), so perhaps a mindset shift is required. Moving the business model that’s built on the transport of data to a model based on the understanding of, and learning from, data. It’s certainly not a lack of data that’s holding them back. Our OSS / BSS collect and curate plenty. The difference is that Google’s and Facebook’s customers are advertisers, whilst the Mammoths’ customers are subscribers.

As OSS providers, the question remains for us to solve – how can we provide the products that allow the Mammoths to win with data?

PS. The other part of this equation is the rise of data privacy regulations such as GDPR (General Data Protection Regulation). Is it just me, or do the Mammoths seem to attract more attention in relation to privacy of our data than the OTT service providers?

Analytics and OSS seasonality

Seasonality is an important factor for network and service assurance. It’s also known as time-of-day/week/month/year specific activity.

For example, we often monitor network health through the analysis of performance metrics (eg CPU utilisation) and set up thresholds to alert us if those metrics go above (or below) certain levels. The most basic threshold is a fixed one (eg if a CPU goes above 95% utilisation, then raise an alert). However, this might just create unnecessary activity. Perhaps we do an extract at 2am every evening, which causes CPU utilisation to bounce at nearly 100% for long perids of time. We don’t want to receive an alert in the middle of the night for what might be expected behaviour.

Another example might be a higher network load for phone / SMS traffic on major holidays or during disaster events.

The great thing about modern analytics tools is that as long as they have long time series of data, then they can spot patterns of expected behaviour at certain times/dates that humans might not be observing and adjust alerting accordingly. This reduces the number of spurious notifications for network assurance operators to chase up on.

10 ways to #GetOutOfTheBuilding

Eric Ries’ “The Lean Startup,” has a short chapter entitled, “Get out of the Building.” It basically describes getting away from your screen – away from reading market research, white papers, your business plan, your code, etc – and out into customer-land. Out of your comfort zone and into a world of primary research that extends beyond talking to your uncle (see video below for that reference!).

This concept applies equally well to OSS product developers as it does to start-up entrepreneurs. In fact the concept is so important that the chapter name has inspired it’s own hashtag (#GetOutOfTheBuilding).

This YouTube video provides 10 tips for getting out of the building (I’ve started the clip at Tendai Charasika’s list of 10 ways but you may want to scroll back a bit for his more detailed descriptions).

But there’s one thing that’s even better than getting out of the building and asking questions of customers. After all, customers don’t always tell the complete truth (even when they have good intentions). No, the better research is to observe what they do, not what they say. #ObserveWhatTheyDoNotWhatTheySay

This could be by being out of the building and observing customer behaviour… or it could be through looking at customer usage statistics generated by your OSS. That data might just show what a customer is doing… or not doing (eg customers might do small volume transactions through the OSS user interface, but have a hack for bulk transactions because the UI isn’t efficient at scale).

Not sure if it’s indicative of the industry as a whole, but my experience working for / with vendors is that they don’t heavily subscribe to either of these hashtags when designing and refining their products.

Does your OSS collect primary data to #ObserveWhatTheyDoNotWhatTheySay? If it does, do you ever make use of it? Or do you prefer to talk with your uncle (does he know much about OSS BTW)?

Are your OSS better today than they were 5 years ago?

Are your OSS better today than they were 5 years ago?
(or 10, 15, 20 years depending on how long you’ve been in the industry) 

Your immediate reaction to this question is probably going to be, “Yes!” After all, you and your peers have put so much effort into your OSS in the last 5 years. They have to be better right?

On the basis of effort, our OSS are definitely more capable… but let me ask again, “Are they better?”

How do they stack up on key metrics such as:

  1. Do they need less staff to run / maintain
  2. Do they allow products to be released more quickly to market
  3. Do they allow customer services to be ready for service (RFS) faster
  4. Are mean times to repair (MTTR) faster when there’s a problem in the network
  5. Are bills more accurate (and need less intervention across all of the parties that contribute)
  6. Are there less fall-outs (eg customer activations that get lost in the ether)
  7. Are we better at delivering (or maintaining) OSS on budget
  8. Are your CAPEX and OPEX budgets lower
  9. Are our front-office staff (eg retail, contact centres, etc) able to give better outcomes for customers via our OSS/BSS
  10. Are our average truck-rolls per activation lower
  11. Are the insights we’re identifying generating longer-run competitive advantages
  12. etc, etc

Maybe it’s the rose-coloured glasses, but my answer to the initial question when framed against these key metrics is, “Probably not,” but with a couple of caveats.

Our OSS are certainly far more complicated. The bubble in which we operate is far more complicated (ie network types, product offerings, technology options, contact channels, more touchpoints, etc). This means more variants for our OSS / BSS to handle. In addition, we’ve added a lot more functionality (ie complexity of our own).

Comparison of metrics will vary greatly across different OSS operators – some for the better, some worse. Maybe I’m just working on projects that are more challenging now than I was 5, 10, 15 years ago.

Do you have the data to confirm / deny that your OSS is better than in years past?

PS. Oh, and one last call-out. You’ll notice that the metrics above tend to be cross-silo. I have no doubt that individual OSS products have improved in terms of functionality, usability, processing speeds, etc. But what about our end-to-end workflows through our OSS/BSS suite of products?

The unfair OSS advantage

My wife and I attended a Christmas party over the weekend and on the trip home we discussed customer service. In particular we were discussing the customer service training she’d had, as well as the culture of customer service reinforcement she’d experienced via leaders and peers in her industry. She doesn’t work in ICT or OSS (obviously?).

In our industry, we talk the customer experience talk via metrics like NPS (Net Promoter Score). However, I don’t recall ever working with a company that provided customer service training or had a strong culture of reinforcing customer service behaviours. Some might claim that it’s just an unwritten rule / expectation.

Conversely, some players in our industry go the opposite way and appear to have the mentality of trying to screw over their customers. Their customers know it and don’t like it but are locked in for any number of reasons.

As OSS implementers, the more consistent trend seems to be a culture of technical perfection. I know I’ve dropped the ball on customer service in the past by putting the technical solution ahead of the customer. I feel bad about that on reflection.

Perhaps what we don’t realise is that we’re missing out on an unfair advantage.

As Seth Godin states in this blog, “Here’s a sign I’ve never seen hanging in a corporate office, a mechanic’s garage or a politician’s headquarters:
WE HAVE AN UNFAIR ADVANTAGE:
We care more.

It’s easy to promise and difficult to do. But if you did it, it would work. More than any other skill or attitude, this is what keeps me (and people like me) coming back
.”

Could it be a real differentiator in our fragmented market?

Do you want dirty or clean automation?

Earlier in the week, we spoke about the differences between dirty and clean consulting, as posed by Dr Richard Claydon, and how it impacted the use of consultants on OSS projects.

The same clean / dirty construct applies to automation projects / tools such as RPA (Robotic Process Automation).

Clean Automation = simply building robotic automations (ie fixed algorithms) that manage existing process designs
Dirty Automation = understanding the process deeply first, optimising it for automation, then creating the automation.

The first is cheap(er) and easy(er)… in the short-term at least.
The second requires getting hands dirty, analysing flows, analysing work practices, analysing data / logs, understanding operator psychology, identifying inefficiencies, refining processes to make them better suited to automation, etc.

Dirty automation requires analysis, not just of the SOP (Standard Operating Procedure), but the actual state-changes occurring from start to end of each iteration of process implementation.
This also represents the better launching-off point to lead into machine-learning (ie cognitive automation), rather than algorithmic or robotic automation.

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

Do you want dirty or clean OSS consulting?

The original management consultant was Frederick Taylor, who prided himself in having discovered the “one best way” which would be delivered by “first-class men”. These assumptions, made in 1911, are still dominant today. Best practice is today’s “one best way” and recruiters, HR and hiring managers spend months and months searching for today’s “first-class men”.

I call this type of consulting clean because the assumptions allow the consultant to avoid dirty work or negative feedback. The model is “proven” best practice. Thus, if the model fails, it is not the consultants’ fault – rather it’s that the organisation doesn’t have the “first-class employees” who can deliver the expected outcome. You just have to find those that can. Then everything will be hunky dory.

All responsibility and accountability are abdicated downwards to HR and hiring managers. A very clean solution for everybody but them.

It’s also clean because it can be presented in a shiny manner – lots of colourful slide-decks promising a beautiful outcome – rational, logical, predictable, ordered, manageable. Clean. In today’s world of digital work, the best practice model is a new platform transforming everything you do into a shiny, pixelated reality. Cleaner than ever.

The images drawn by clean consultants are compelling. The client gets a clearly defined vision of a future state backed up by evidence of its efficacy.

But it’s far too often a dud. Things are ignored. The complex differences between the client and the other companies the model has been used on. The differences in size, in market, in demographic, in industry. None matter – because the one best way model is just that – one best way. It will work everywhere for everyone. As long as they keep doing it right and can find the right people to do it.

The dirty consultant has a problem that the clean consultant doesn’t have. It’s a big problem. He doesn’t have an immediate answer for the complex problem vexing the client. He has no flashy best practice model he strongly believes in. No shiny slide deck that outlines a defined future state.

It’s a difficult sell.

What he does have is a research process. A way of finding out what is actually causing the organisational problems. Why and how the espoused culture is different from organisational reality. Why and how the supposed best practice solution is producing stressed out anxiety or cynical apathy.

This process is underpinned by a fundamentally different perspective on the world of work. Context is everything. There is no solution that can fit every company all of the time. But there’s always a solution for the problem. It just has to be discovered.

The dirty consultant enters an organisation ready and willing to uncover the dirty reasons for the organisation not performing. This involved two processes – (1) working out where the inefficiencies and absurdities are, and (2) finding out who knows how to solve them.”

The text above all comes from this LinkedIn post by Dr Richard Claydon. It’s also the longest quote I’ve used in nearly 2000 posts here on PAOSS. I’ve copied such a great swathe of it because it articulates a message that is important for OSS.

There is no “best practice.” There is no single way. There are no cookie-cutter consulting solutions. There are too many variants at play. Every OSS has massive local context. They all have a local context that is far bigger than any consultant can bring to bear.

They all need dirty consulting – assignments where the consultant doesn’t go into the job knowing the answers, acknowledging that they don’t have the same local, highly important context of those who are at gemba every day, at the coal-face every day.

There is no magic-square best-fit OSS solution for a given customer. There should be no domino-effect selection of OSS (ie the big-dog service provider in the region has chosen product X after a long product evaluation so therefore all the others should choose X too). There is no perfect, clean answer to all OSS problems.

Having said that, we should definitely seek elements of repeatability – using repeatable decision frameworks to guide the dirty consulting process, to find solutions that really do fit, to find where repeatable processes will actually make a difference for a given customer.

So if the local context is so important, why even use a consultant?

It’s a consultant’s role to be a connector – to connect people, ideas, technologies, concepts, organisations – to help a customer make valuable connections they would otherwise not be able to make.

These connections often come from the ability to combine the big-picture concepts of clean consulting with the contextual methods of dirty consulting. There’s a place for both, but it’s the dirty consulting that provides the all-important connection to gemba. If an OSS consultant doesn’t have a dirty-consulting background, an ability to frame from a knowledge of gemba, I wonder whether the big-picture concepts can ever be workable?

What are your experiences working with clean consultants (vs dirty consultants) in OSS?

6 principles of OSS UI design

When we talk about building capabilities by design, there are a set of four core capabilities that you should keep in mind:

  • Designed for self-sufficiency: Enable an environment where the business user is capable of acquiring, blending, presenting, and visualizing their data discoveries. IT needs to move away from being command and control to being an information broker in a new kind of business-IT partnership that removes barriers, so that users have more options, more empowerment, and greater autonomy.
  • Designed for collaboration: Have tools and platforms that allow people to share and work together on different ideas for review and contribution. This further closes that business-IT gap, establishes transparency, and fosters a collective learning culture.
  • Designed for visualization: Data visualizations have been elevated to a whole new form of communication that leverages cognitive hardwiring, enriches visual discovery, and helps tell a story about data to move from understanding to insight.
  • Designed for mobility: It is not enough to be just able to consume information on mobile devices, instead users must be able to work and play with data “on the go” and make discovery a portable, personalized experience.

Lindy Ryan in the book, “The Visual Imperative: Creating a Visual Culture of Data Discovery.”

When it comes to OSS specifically, I have two additional design principles:

  • Designed for Search – there is so much data in our OSS / BSS suites; some linked, some not; some normalised, some not; some cleansed, some not; This design principle allows abstraction from all those data challenges to allow operators to make psuedo-natural language requests for information. Noting that this could be considered an overlap between points 1 and 3 in the prior list
  • Designed for user journeys – in an omni-channel world, the entry point and traversal of any OSS workflow could cross multiple channels (eg online, retail store, IVR, app, etc). This makes pre-defined workflows almost impossible to design / predict. Instead, on OSS / BSS suite must be able to handle complete flexibility of user journeys between state / event transitions

Been done before, been done before

What percentage of the work you do each day is work where the process (the ‘right answer’) is known? Jobs where you replicate a process instead of inventing one…
The place where we can create the most value is when we do a job where exploration and a new solution is what’s needed. Not rote, but exploration. Which means we’re doing something that’s not been done before, something that might not work.
This isn’t something to avoid, it’s the work we need to seek out
.”
Seth Godin
in this blog.

From the perspective of OSS experts, this blog from Seth Godin has three distinct perspectives:

  • The OSS operators’ perspective – Where we want super-repeatability, consistency and quality. We can accommodate exploration, but only if we’re monitoring Darwinian change and using it to evolve to become ever fitter and faster. Operator roles are all about coercing large volumes of activities through the funnel as quickly and accurately as possible, supported by our OSS tools and processes.
  • The OSS installer’s perspective – Where we want the out of the box installation to also be highly efficient, repeatable and consistent. In most cases, we don’t want room for exploration during an install
  • The OSS builders’ perspective – Where we want to follow Godin’s explorative lead, where we want to configure / customise an OSS by seeking something that’s never been done before in the hope that the solution is better than has ever been done before (in readiness to hand over to operators and installers)

Some people enjoy rote, consistency and repeatability, knowing what they’re going to do each day before the day starts. OSS needs these personalities.

But for the OSS builder roles, rote isn’t something to avoid, it’s the work we need to seek out, perhaps more passionately and laterally than we may care to admit.

If OSS is my hammer, am I only seeing nails?

OSS is a powerful multi-purpose tool, much like a hammer.

If OSS is my only tool, do I see all problems as nails that I have to drive home with my OSS?

The downside of this is that it then needs to be designed, built, integrated, tested, released, supported, upgraded, data curated and maintained. The Total Cost of Ownership (TCO) for a given problem extends far beyond the time-frame envisaged during most solutioning exercises.

To be honest, I’ve probably been guilty of using OSS to solve problems before seeking alternatives in the past.

What if our going-in position was that answers should be found elsewhere – outside OSS – and OSS simply becomes the all-powerful last resort? The sledgehammer rather than the ball-pein hammer.

With all this big data I keep hearing about, has anyone ever seen any stats relating to the real life-time costs of OSS customisations made by a service provider to its off-the-shelf OSS? If such data exists, I’d love to see what the cost-benefit break-even point might look like and what we could learn from it. I assume we’re contributing to our very own Whale Curve but have nothing to back that assumption up yet.

An uncommon list of OSS books

Since reading the first book on this list, I’ve become a very avid and wide-ranging reader. The seeds sown by the book list below have immensely helped enrich the content you see here on the PAOSS blog and other PAOSS content.

You’ll begin to notice a very curious thing about this list though. There are only two books in the entire list that are actually about OSS. I have many OSS books in my library, but most struggle for relevance beyond the author’s frame of reference – they have been written from the specific technical experiences of the author, which are rarely transferable to other OSS. Either the technologies are now out of date and/or the details / terminologies were pertinent only to that OSS time and place. It’s one of the reasons that PAOSS content is specifically intended to abstract from technology and deliver insights, methodologies, processes and frameworks that have a broader relevance and greater longevity (hopefully).

The remaining books in the list have not been written with OSS in mind but definitely provide insights and perspectives that are transferable to the challenges we face in the OSS industry. In no particular order (except the first being the first…)

Rich Dad, Poor DadRich Dad, Poor Dad
by Sharon L. Lechter Robert T. Kiyosaki
This was the book that changed it all for me. Whilst its intent is to educate on personal finance, the effect it had was to lift my eyes beyond the purely technical. Like 95%+ of people in our industry, I had previously only ever focused on delivering the best technical solution I could with the assumption that this would deliver a great customer outcome. I now know that the challenges we face are far  bigger than that!
Insanely Simple: The Obsession That Drives Apple's SuccessInsanely Simple: The Obsession That Drives Apple’s Success
by Ken Segall
The greatest OSS (but non-OSS) book I’ve read. The first half of this book in particular delivers powerful examples of simplification at all levels of an organisation as experienced by an advertising executive working alongside Steve Jobs at Apple. The OSS and communications industry need more people who are able to wield the simple stick like Steve did.
ReworkRework
by Jason Fried, David Heinemeier Hansson
These gentlemen have built a strong business around the Basecamp project management suite of tools. In Rework, just like their blog at 37signals, they provide brilliant contrarian insights into how to run a software business… Or any business for that matter. Efficiency and simplicity are the mantra ahead of the Red-Bull fuelled heroics spouted by many organisations in the software industry. One of my all-time favourite business books.
Enchantment: The Art of Changing Hearts, Minds, and ActionsEnchantment: The Art of Changing Hearts, Minds, and Actions
by Guy Kawasaki
Guy defines enchantment as, “the process of delighting people with a product, service, organisation or idea. The outcome of enchantment is voluntary and long-lasting support that is mutually beneficial.” If there was ever an industry that was in need of enchantment, it is the OSS industry right now.
Rain: What a Paperboy Learned About BusinessRain: What a Paperboy Learned About Business
by Jeffrey J. Fox
An easy to digest story about a boy with a paper-route learning the key tenets of rainmaking, the ability to delight customers and make sales (and projects) happen.
The Presentation Secrets of Steve Jobs: How to Be Insanely Great in Front of Any AudienceThe Presentation Secrets of Steve Jobs: How to Be Insanely Great in Front of Any Audience
by Carmine Gallo
There are two acronyms that pervade in the OSS / telco / tech industry; DBA (Death by Acronym) and DBP (Death by Powerpoint). This book provides some stunning insights into how to make a compelling presentation on your latest OSS project.
Killing Giants: 10 Strategies to Topple the Goliath in Your IndustryKilling Giants: 10 Strategies to Topple the Goliath in Your Industry
by Stephen Denny
There are a number of goliath incumbents in our industry. However, I suspect that most of the required disruption is coming from the Davids of our industry, despite the burning platforms at the goliaths. Interesting reading for a different perspective on innovation and change.
Jack Welch & The G.E. Way: Management Insights and Leadership Secrets of the Legendary CEOJack Welch & The G.E. Way: Management Insights and Leadership Secrets of the Legendary CEO
by Robert Slater
This book describes a number of key strategies for how Jack Welch pared back the weighty bureaucracy of General Electric upon his ascension to CEO. I suspect our industry needs similarly brutal change leadership to thrive into the future
The Best Service is No Service: How to Liberate Your Customers from Customer Service, Keep Them Happy, and Control CostsThe Best Service is No Service: How to Liberate Your Customers from Customer Service, Keep Them Happy, and Control Costs
by Bill Price, David Jaffe
There is a distinct difference between the customer service models of the typical communications service provider (CSP) and digital service providers (DSP) like Google, Facebook, Amazon, et al. Most CSPs can only wish for the level of customer self-service that the DSPs enjoy. I was working on a project for a customer-facing business unit of a CSP whilst reading this book and the parallels were almost scary.
Essentialism: The Disciplined Pursuit of LessEssentialism: The Disciplined Pursuit of Less
by Greg McKeown
Think: Less but better. A motto for our industry, one individual at a time.
Anything You Want: 40 Lessons for a New Kind of EntrepreneurAnything You Want: 40 Lessons for a New Kind of Entrepreneur
by Derek Sivers
Derek Sivers was a professional musician before starting his own business, one that helped sell the CDs of the long tail of the music industry, musicians overlooked by the big labels. This might sound barely relevant to the OSS industry but there is an uncommon clarity in the way that Sivers views businesses, customers and delivery. Many of his thoughts really struck a chord with me (bad pun intended).
Brick by Brick: How LEGO Rewrote the Rules of Innovation and Conquered the Global Toy IndustryBrick by Brick: How LEGO Rewrote the Rules of Innovation and Conquered the Global Toy Industry
by David Robertson, Bill Breen
Bespoke creativity took this icon of childrens’ toys to the brink of bankruptcy. Perhaps counter-intuitively, paring it back to the basic building blocks (another bad pun) allowed creativity and profitability to thrive at Lego.
Principles: Life and WorkPrinciples: Life and Work
by Ray Dalio
Built around the principles that Ray Dalio codified at his company, Bridgewater Associates. Many of his principles of team and culture seem like common sense, but helpfully compiled into a single volume. Not all OSS teams have these principles mastered.
Blue Ocean Strategy, Expanded Edition: How to Create Uncontested Market Space and Make the Competition IrrelevantBlue Ocean Strategy, Expanded Edition: How to Create Uncontested Market Space and Make the Competition Irrelevant
by W. Chan Kim, Renée Mauborgne
This book provides frameworks for shifting an organisation out of fragmented, highly competitive markets (bloody red oceans) into a unique market segment (blue oceans). I’ve even added some of the concepts in this book into a framework that helps my clients plot differentiated strategic roadmaps and product evaluations.
Leading ChangeLeading Change
by John P. Kotter
OSS projects are challenging to implement. Through harsh experience, I’ve learnt that even technically perfect implementations are prone to fail if the organisational change effort hasn’t been managed well. Whilst there are newer change management methodologies available, I still find that Kotter’s 8 steps provide a valuable framework for building OSS change management strategies around.
Everything Is Negotiable: How to Get the Best Deal Every TimeEverything Is Negotiable: How to Get the Best Deal Every Time
by Gavin Kennedy
Introduces some fascinating negotiation tactics such as “The Mother Hubbard” (ie the cupboard is bare). There is more negotiation required in OSS than I first gave it credit for.
Endless Referrals: Network Your Everyday Contacts into SalesEndless Referrals: Network Your Everyday Contacts into Sales
by Bob Burg
In the early days of my career, I’d gone from one project to the next, with my head down focusing on delivery. This book opened my eyes to the value of staying in touch with past colleagues and adding value to my network. The results have surprised me so I recommend this book’s teachings to anyone who is purely tech-focused.
The Idea Factory: Bell Labs and the Great Age of American InnovationThe Idea Factory: Bell Labs and the Great Age of American Innovation
by Jon Gertner
Put simply, this is probably the most inspiring book I’ve read in relation to the communications industry. The groundbreaking innovations (including OSS) that were developed within R&D powerhouses like Bell Labs during the 1900’s are staggering and something that we can barely even aspire to today. It’s no coincidence that the OSS Call for Innovation references this book
nullLinchpin: Are You Indispensable?
by Seth Godin
A call to action to become a linchpin, someone who delivers in territory where there is no map / rule-book, someone who inspires those around them. OSS needs more linchpins.
Made to Stick: Why Some Ideas Survive and Others DieMade to Stick: Why Some Ideas Survive and Others Die
by Chip Heath, Dan Heath
The term “stickiness” was popularised by Malcolm Gladwell in “The Tipping Point.” This book borrows the term and looks to explain why an idea or concept remains sticky. OSS tend to be so sticky, in many cases to the detriment of the customer experience, but our industry is also in desperate need for powerfully sticky new ideas and approaches.
The E-Myth Revisited: Why Most Small Businesses Don't Work and What to Do About ItThe E-Myth Revisited: Why Most Small Businesses Don’t Work and What to Do About It
by Michael E. Gerber
The ideas in this book are based on growing small businesses, but there are certainly take-aways for OSS. The biggest for me is the need for repeatability. We need to codify and systematise if we are to refine and improve.
Purple Cow, New Edition: Transform Your Business by Being RemarkablePurple Cow, New Edition: Transform Your Business by Being Remarkable
by Seth Godin
In a cluttered or fragmented marketplace, like OSS, it is difficult to stand out from all other suppliers. Seth Godin introduces the concept of the purple cow – when you’re on a long trip in the countryside, seeing lots of brown or black cows soon gets boring, but if you saw a purple cow, you’d immediately take notice. This book provides the impetus to make your products stand out and drive word of mouth rather than having to differentiate via your marketing.
Creativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True InspirationCreativity, Inc.: Overcoming the Unseen Forces That Stand in the Way of True Inspiration
by Ed Catmull, Amy Wallace
From the creative brilliance of Pixar Studios comes this book of how to cultivate inspired creativity. My biggest take-away was the amount of time and money Pixar spends on upgrading its hardware and software platforms between films…. unlike some of our OSS that are still rooted in tech from the 1990s.
The 4-Hour Workweek: Escape 9-5, Live Anywhere, and Join the New RichThe 4-Hour Workweek: Escape 9-5, Live Anywhere, and Join the New Rich
by Timothy Ferriss
Starts off strongly but drops away rapidly in the second half IMHO. The words of a friend of mine aptly paraphrase what Tim Ferris talks about in this book, “Only do what only you can do.” Prioritise your efforts on what make you truly unique and use other efficiency tools and/or engage others to do the rest
OSS Essentials: Support System Solutions for Service ProvidersOSS Essentials: Support System Solutions for Service Providers
by Kornel Terplan
Finally, a book that’s actually about OSS. Whilst covering some obsolete technologies, this is one of the very few OSS books that retains a longevity of relevance (it was published in 2001)
Million Dollar Consulting: The Professional's Guide to Growing a Practice, Fifth EditionMillion Dollar Consulting: The Professional’s Guide to Growing a Practice, Fifth Edition
by Alan Weiss
Alan Weiss has the ability to cut through the waffle that’s offered in many consultancy how-to manuals. He provides insightful and often contrarian advice that will make you a more professional consultant, no matter what area of expertise you cover.
Mastering your OSS: Operational Support System Implementation Tips and TechniquesMastering your OSS: Operational Support System Implementation Tips and Techniques
by Ryan Jeffery
This is the best OSS book that I’ve written (so far), but with new material in the pipeline, watch this space for even better publications. It provides the frameworks, processes, insights and recommendations that will help guide you through the myriad of challenges, technical or otherwise, that you will face in the world of OSS.
Power Listening: Mastering the Most Critical Business Skill of AllPower Listening: Mastering the Most Critical Business Skill of All
by Bernard T. Ferrari
Bernard Ferrari advises the use of the Pareto Principle to listening. In other words, spending 80% of the time listening and only 20% talking. It’s such an important trait for all technical resources, yet perhaps somewhat uncommon unfortunately. As the “hired gun,” there is a tendency to start firing from both barrels verbally as soon as you meet with the customer. But the most insightful insights are the ones that are understandable to the customer. They have to be relevant in terminology, desired outcomes, roles/responsibilities, respective capabilities, etc, etc. You only get that context from Power Listening.
The Click Moment: Seizing Opportunity in an Unpredictable WorldThe Click Moment: Seizing Opportunity in an Unpredictable World
by Frans Johansson
Johansson also introduces the concept of the “smallest executable step” as a mechanism for harnessing the apparent randomness of our modern, rapidly changing world. He suggests that we make many small bets rather than one massive bet as a means of improving success rates. OSS are complex systems so any small deviation makes predictions of completion time, resources and cost difficult. As implementers, it’s our job to remove as much complexity as possible
 Harder Than I Thought: Adventures of a Twenty-First Century LeaderHarder Than I Thought: Adventures of a Twenty-First Century Leader
by Robert D. Austin, Richard L. Nolan
More than anything else, one paragraph has stuck with me from this guide to project change leadership, “….once you start a company transformation, it’s like a stampede. If you try to lead from the front, you get trampled; if you try to lead from the back, you have no impact. Best to lead from the side by carefully nudging and turning the stampede to avoid everyone going over the cliff.”
Waging War on Complexity Costs: Reshape Your Cost Structure, Free Up Cash Flows and Boost Productivity by Attacking Process, Product and Organizational ComplexityWaging War on Complexity Costs: Reshape Your Cost Structure, Free Up Cash Flows and Boost Productivity by Attacking Process, Product and Organizational Complexity
by Stephen A. Wilson, Andrei Perumal.
Amongst other things, this book introduces the concept of The Whale Curve, a model that breaks products into the profitable or the cannibalistic.
Cryptocurrency: How Bitcoin and Digital Money are Challenging the Global Economic OrderCryptocurrency: How Bitcoin and Digital Money are Challenging the Global Economic Order
by Paul Vigna, Michael J. Casey
You may (or may not) be interested in cryptocurrencies right now, but this book provides brilliant context for two concepts that are likely to have a big impact on future OSS – blockchains and smart contracts.

What have I missed? What should I be adding to my reading list? Alternatively, which books on the list do you think I’ve over-rated?

The madness of most OSS training

When you’ve just implemented a new OSS, what does the training look like? A 2-3 week classroom course series? A train-the-trainer series, which then trickles down to the workforce?

If this is what your OSS training looks like (or even closely resembles), then this is madness. Unfortunately, this is the model that I’ve seen most predominantly in the wild. Many OSS build contracts / RFPs even mandate this type of knowledge transfer.

It’s madness because classroom courses don’t tend to be very good for absorbing the context or nuance of using an OSS. OSS training tends to be generic, without the local context of using the customer’s process flows, naming conventions, device types, topologies, services, etc.

Alan Weiss articulates this well, “…skills building occurs best when it includes application on the job, oversight by immediate supervisors, accountability for implementation, and rewards for success. None of that is accomplished in a classroom.”

What are the better alternatives then? Embedded training including:

  1. Have the customer operatives deeply embedded in the implementation project, absorbing knowledge in “real” situations as it is being built
  2. Offer supported sandpit environments that reflect PROD (Production environments) and allow operatives the time to build scenarios from their own contexts in the sandpit
  3. Provide handover support, where the installation team is on hand to support operational teams during an initial period after handover
  4. Master classes where operatives ask questions within their specific contexts, noting that this technique is only suitable after students have already developed a significant base of knowledge

Whilst PAOSS offers virtual class-based OSS training (which are generic by nature, not product-specific), I’ve found embedded knowledge transfer is far more successful and is my strongly recommended approach.

Who can make your OSS dance?

OSS tend to be powerful software suites that can do millions of things. Experts at the vendors / integrators know how to pull the puppet’s strings and make it dance. As a reader of PAOSS, chances are that you are one of those experts. I’ve sat through countless vendor demonstrations, but I’m sure you’ll still be able to wow me with a demo of what your OSS can do.

Unfortunately, most OSS users don’t have that level of expertise, nor experiences or training, to pull all of your OSS‘s strings. Most only use the tiniest sub-set of functionality.

If we look at the millions of features of your OSS in a decision tree format, how easy will it be for the regular user to find a single leaf on your million-leaf tree? To increase complexity further, OSS workflows actually require the user group to hop from one leaf, to another, to another. Perhaps it’s not even as conceptually simple as a tree structure, but a complex inter-meshing of leaves. That’s a lot of puppet-strings to know and control.

A question for you – You can make your OSS dance, but can your customers / users?

What can you do to assist users to navigate the decision tree? A few thoughts below:

  1. Prune the decision tree – chances are that many of the branches of your OSS are never / rarely used, so why are they there?
  2. Natural language search – a UI that allows users to just ask questions. The tool interprets those questions and navigates the tree by itself (ie it abstracts the decision tree from the user, so they never need to learn how to navigate it)
  3. Use decision support – machine assistance to guide users in navigating efficiently through the decision tree
  4. Restrict access to essential branches – design the GUI to ensure a given persona can only see the clusters of options they will use (eg via the use of role-based functionality filtering)

I’d love to hear your additional thoughts how to make it easier for users to make your  (their) OSS dance.

Do we actually need less intellectual giants?

Have you ever noticed that almost every person who works in OSS is extremely clever?
No?

They may not know the stuff that you know or even talk in the same terminologies that you and your peers use, but chances are they also know lots of stuff that you don’t.

OSS sets a very high bar. I’ve been lucky enough to cross into many different industries as a consultant. I’d have to say that there are more geniuses per capita in OSS than in any other industry / sector I’ve worked in.

So why then are so many of our OSS a shambles?

Is it groupthink? Do we need more diversity of thinking? Do we actually need less intellectual giants to create pragmatic, mere-mortal solutions?

Our current approach appears to be flawed. Perhaps Project Platypus gives us on alternate framework?

Actually, I don’t think we need less intellectual giants. But I do think we need our intellectual giants to have a greater diversity of experiences.

The augmented analytics journey

Smart Data Discovery goes beyond data monitoring to help business users discover subtle and important factors and identify issues and patterns within the data so the organization can identify challenges and capitalize on opportunities. These tools allow business users to leverage sophisticated analytical techniques without the assistance of technical professionals or analysts. Users can perform advanced analytics in an easy-to-use, drag and drop interface without knowledge of statistical analysis or algorithms. Smart Data Discovery tools should enable gathering, preparation, integration and analysis of data and allow users to share findings and apply strategic, operational and tactical activities and will suggest relationships, identifies patterns, suggests visualization techniques and formats, highlights trends and patterns and helps to forecast and predict results for planning activities.

Augmented Data Preparation empowers business users with access to meaningful data to test theories and hypotheses without the assistance of data scientists or IT staff. It allows users access to crucial data and Information and allows them to connect to various data sources (personal, external, cloud, and IT provisioned). Users can mash-up and integrate data in a single, uniform, interactive view and leverage auto-suggested relationships, JOINs, type casts, hierarchies and clean, reduce and clarify data so that it is easier to use and interpret, using integrated statistical algorithms like binning, clustering and regression for noise reduction and identification of trends and patterns. The ideal solution should balance agility with data governance to provide data quality and clear watermarks to identify the source of data.

Augmented Analytics automates data insight by utilizing machine learning and natural language to automate data preparation and enable data sharing. This advanced use, manipulation and presentation of data simplifies data to present clear results and provides access to sophisticated tools so business users can make day-to-day decisions with confidence. Users can go beyond opinion and bias to get real insight and act on data quickly and accurately.”
The definitions above come from a post by Kartik Patel entitled, “What is Augmented Analytics and Why Does it Matter?.”

Over the years I’ve loved playing with data and learnt so much from it – about networks, about services, about opportunities, about failures, about gaps, etc. However, modern statistical analysis techniques fall into one of the categories described in “You have to love being incompetent“, where I’m yet to develop the skills to a comfortable level. Revisiting my fifth year uni mathematics content is more nightmare than dream, so if augmented analytics tools can bypass the stats, I can’t wait to try them out.

The concepts described by Kartik above would take those data learning opportunities out of the data science labs and into the hands of the masses. Having worked with data science labs in the past, the value of the information has been mixed, all dependent upon which data scientist I dealt with. Some were great and had their fingers on the pulse of what data could resolve the questions asked. Others, not so much.

I’m excited about augmented analytics, but I’m even more excited about the layer that sits on top of it – the layer that manages, shares and socialises the aggregation of questions (and their answers). Data in itself doesn’t provide any great insight. It only responds when clever questions are asked of it.

OSS data has an immeasurable number of profound insights just waiting to be unlocked, so I can’t wait to see where this relatively nascent field of augmented analytics takes us.

My least successful project

Many years ago I worked on a three-way project with 1) a customer, 2) a well-known equipment vendor and 3) a service provider (my client). Time-frames were particularly tight, not so much because of the technical challenge, but because of the bureaucratic processes of the customer and the service provider. The project was worth well in excess of $100M, so it was a decent-sized project as part of a $1B+ program.

The customer had handed the responsibility of building a project schedule to the equipment vendor and I, which we duly performed. The Gantt chart was quite comprehensive, running into thousands of lines of activities and had many dependencies where actions by the customer were essential. These were standard dependencies such as access to their data centres, uplift to infrastructure, firewall burns, design approvals, and the list goes on. The customer had also just embarked on a whole-of-company switch of project management frameworks, so it wasn’t hard to see that related delays were likely.

The vendor and I met with the customer to walk through the project plan. About half-way in, the customer asked the vendor whether they were confident that timelines could be met. The vendor was happy to say yes. I was asked the same question. My response was that I was comfortable with the vendor’s part, I was comfortable with our part (ie the service provider’s), but that the customer’s dependencies were a risk because we’d had push-back from their Project Manager and each of the internal business units that we knew were impacted (not to mention the other ones that were likely to be impacted but we had no visibility of yet).

That didn’t go down well. I copped by far the biggest smashing of my career to date. The customer didn’t want to acknowledge that they had any involvement in the project – despite the fact that they were to approve it, house it, host it, use it and maintain aspects of it. It seemed like common sense that they would need to get involved.

Over the last couple of decades of delivery projects, one trend has been particularly clear – the customer gets back what they put in. That project had at least twelve PMs on the customer side over the 18 month duration of the project. It moved forward during stints under the PMs who got involved in internal solutioning, but stagnated during periods under PMs that just blame-stormed. Despite this, we ended up delivering, but the user outcomes weren’t great.

As my least successful project to date (hopefully ever), it was also one of my biggest “learnings” projects. For a start, it emphasised that I needed to get better at hearts and minds change management. There were many areas where better persuasion was required – from the timelines / dependencies to the compromised architecture / hardware that was thrust upon us by the customer’s architects. What seemed obvious to me was clearly not so obvious to the customer stakeholders I was trying to persuade.

You have to love being incompetent

You have to love being incompetent in order to be competent.”
James Altucher
.

Not sure that anyone loves feeling incompetent, but James’ quote is particularly relevant in the world of OSS. There are always so many changes underway that you’re constantly taken out of your comfort zone. But the question becomes how do you overcome those phases / areas of incompetence?

Earlier in my career, I had more of an opportunity to embed myself into any area of incompetence, usually spawned by a technical challenge being faced, and pick it up through a combination of practical and theoretical research. That’s a little harder these days with less hands-on and more management responsibilities, not to mention more demands on time outside hours.

In a way, it’s a bit like stepping up the layers of TMN management pyramid.
TMN Pyramid
Image courtesy of www.researchgate.net.

With each step up, the context gets broader (eg more domains under management), but more abstracted from what’s happening in the network. Each subsequent step northbound does the same thing:

  • It abstracts – it only performs a sub-set of the lower layer’s functionality
  • It connects – it performs the task of connecting and managing a larger number of network elements than the lower layer

Conversely, each step down the management stack should produce a narrower (ie not so many device interconnections), but deeper field of view (ie a deeper level of information about the fewer devices).

The challenge of OSS is in choosing where to focus curiosity and improvements – diving down the stack into new tech or looking up and sidewards?

Deciding whether to PoC or to doc

As recently discussed with two friends and colleagues, Raman and Darko, Proofs of Concept (PoC) or Minimum Viable Product (MVP) implementations can be a double-edged sword.

By building something without fully knowing the end-game, you are potentially building tech-debt that may be very difficult to work around without massive (or complete) overhaul of what you’ve built.

The alternative is to go through a process of discovery to build a detailed document showing what you think the end product might look like.

I’m all for leaving important documentation behind for those who come after us, for those who maintain the solutions we create or for those who build upon our solutions. But you’ll notice the past-tense in the sentence above.

There are pros and cons with each approach, but I tend to believe in documentation in the “as-built” sense. However, there is a definite need for some up-front diagrams/docs too (eg inspiring vision statements, use cases, architecture diagrams, GUI/UX designs, etc).

The two biggest reasons I find for conducting PoCs are:

  • Your PoC delivers something tangible, something that stakeholders far and wide can interact with to test assumptions, usefulness, usability, boundary cases, etc. The creation of a doc can devolve into an almost endless set of “what-if” scenarios and opinions, especially when there are large groups of (sometimes militant) stakeholders
  • You’ve already built something – your PoC establishes the momentum that is oh-so-vital on OSS projects. Even if you incur tech-debt, or completely overhaul what you’ve worked on, you’re still further into the delivery cycle than if you spend months documenting. Often OSS change management can be a bigger obstacle than the technical challenge and momentum is one of change management’s strongest tools

I’m all for deep, reflective thinking but that can happen during the PoC process too. To paraphrase John Kennedy, “Don’t think, don’t hope, (don’t document), DO!” 🙂