Meeting the OTT challenge

Martin Geddes

Martin Geddes Consulting Ltd

© 2013 All Rights Reserved

What has to change?

NOW FUTURE

PURPOSE-FOR-FITNESS

FITNESS-FOR-PURPOSE

Core thesis

1. Networks are (option) trading spaces – That match supply and demand across all timescales

2. Your business is statistical multiplexing for fun and profit – Supply and demand meet here, and trades are made

3. Success primarily depends on how well you do this – Regardless of the (OTT) business model on top or who pays

4. Your current business is mathematically unsustainable – Because you have not taken full control over your network trading space

5. There is a way to take control – Get away from supply-push “bandwidth” approach & purpose-for-fitness

6. Move to a sustainable demand-driven “quality” model

What to do?

1. Characterise demand and create fit-for-purpose supply

2. Align your design, marketing, operations to deliver

3. Execute to create differentiation in cost and QoE

4. Enable new OTT business models

The Facts

Situation

OTT voice and messaging are hurting telephony and SMS revenue

Selling data speed and mechanisms

Value is measured in data volume

Revenue model: Proportional to average volumetric demand

Cost model

Size to peak demand

Planned upgrades Volume-driven capacity

planning rules

Unplanned upgrades Driven by churn and complaints

Key properties of data demand

• User have a sense of entitlement

– Want properties of circuits

– Uncontended, on-demand un-impaired capacity

• Ability to attach any device or application

– Demand shocks can and do happen (iPhone, Olympics, emergency events, etc.)

• Distribution of use is shifting

– Not just the average; peaks are getting “peakier”

Key properties of data supply offer

• One-size-fits-all: Single class of service

• One-sided market: End user pays

– No “toll free” data or upstream revenue

• No quality assurance or performance SLAs

• Little visibility of actual user experience

Supply-push model: Purpose-for-fitness

The market is evolving

• Rapid growth in demand

– SaaS/cloud, mobile workers, tablets, automotive, small cells, M2M, smart grids, etc.

• These require new supply capabilities

– Very different cost and quality profiles

The market is evolving

• Government and regulatory focus shifting to “digital dividend”

– Tackling economic/social issues

– It’s not going to be about negotiating roaming and termination rates in future

All operators are facing tough questions

1. How to sustain voice and messaging revenue and differentiation positioning?

2. How to relate to OTTs (block, bundle, ignore, service, join in, partner…)?

3. How to address growing market needs at an affordable cost?

What’s wrong

Complication

Speed (and volume) are not value

Dangerous myth: More Speed is Always Better

Contention exists!

Need to consider variability, not just speed.

Source: Predictable Network Solutions Ltd

Black cygnets: small “bad coincidences” create bad experiences

These coalesce under high load

And create ever more ‘black swan’ application failures

The application

Hierarchy of Need

3. Reasonable bounds on loss and delay

2. Sufficient stationarity

1. Sufficient capacity

Note: exact requirements are application-dependent

So 4G won’t solve your problems

Downstream delay over a 3G connection – 4G doesn’t change this unwanted variability

Too much variability for TCP to work well.

Source: Predictable Network Solutions Ltd

What you need to know

Some theory

Capacity demand

TWO sources of network demand

Schedulability demand

Capacity demand LOW HIGH

Feasible Infeasible

MAX CAPACITY

TWO fundamental resource limits

Feasible

MAX SCHEDULABILITY Sc

he

du

lab

ility

d

em

and

Infeasible

LOW

HIGH

Problem

Schedulability demand is growing fast

VoIP, gaming, 2-way video, UC, HTML5 web, WebRTC…

Problem

Solving schedulability issues (i.e. non-stationarity)

with capacity is inefficient and ineffective

Problem

Monoservice network means costs track the

worst-case schedulability limit of loading

Summary so far

• “Bandwidth” is your current input and output – This is not a good proxy for fitness-for-purpose

– Other factors also matter to QoE

• Revenue is from fit-for-purpose experiences – But you have stopped paying attention to user needs

– Dependability is not on sale, at any price

• Costs are being driven by schedulability issues – Every flow has the same cost structure as your most

quality-demanding users/flows

– But schedulability isn’t part of costing & ops model

The consequence

Undesirable future

Telecoms is a capital killer ($60bn/year shortfall, every year)

Source: PwC http://www.pwc.com/en_GX/gx/communications/publications/assets/pwc_capex_final_21may12.pdf

Failure of technology to keep

up with ever rising demand

forces shorter upgrade cycles

Rising load makes

service quality fall,

forcing upgrades

Serv

ice

Qu

alit

y

Time

Un

dep

reci

ated

Ass

et V

alu

e

Time

Mathematically unsustainable

More, more, more (aka 2G/3G/4G/5G cycle of doom)

More supply

More elastic demand

Faster saturation of backhaul

More non-stationarity

More complaints and churn

Race to the bottom?

The alternative

Desirable future

What do we want?

• Demand – increased benefits

– Able to match a wide range of quantity, quality and cost needs

– Can package offers to fit segments

• Supply – decreased costs

– Costs scale sub-linearly with users

– Predictable in-life operational costs

Packaged (OTT) cloud applications

• Available when and where you need it

• Right quantity and quality

• At a cost you can afford

• Easy to consume

How to get there?

The Question

The big question

How can we exploit the trades (and demand-shift by scheduling)

and match supply to demand to create the

right QoE and cost trade-offs?

Then, given that capability, what should our OTT strategy be?

What do I need to do?

The Answer

Bandwidth Quality Need to frame the problem

differently to make it soluble

What has to change?

NOW FUTURE

PURPOSE-FOR-FITNESS

FITNESS-FOR-PURPOSE

Focus on enabling outcomes – not shifting data Make bad experiences rare(r).

Lower cost of delivering good experiences.

TELCO END USER

Manage benefits, costs and risks across supply chain

BENEFIT

COST

RISK (failed call)

Made the sales call

Price of phone call

Didn’t make sale

Second car

Revenue

Tin, opex

SLA breach or churn

Unplanned capacity upgrade

Time wasted

Reputational loss

INSURANCE Contingency fund (lawsuit, PR)

Frustration

Excess risk has to be (self-)insured

Manage QoE risk through network resource “trades”

The “tails” of loss and delay + their structure

are what cause application QoE failure, and whose mitigation

drives cost.

Source: Predictable Network Solutions Ltd

Lower cost of good experiences by time-shifting delay-insensitive traffic

• Reduce cost by lowering peaks

– Currently encouraging people not to time-shift.

– Users behave in a predatory way.

• Mark bulk traffic

– Cheaper to post bulk mail if pre-sorted.

Microseconds to minutes

Peak demand

Summary: Do’s and Don’ts

• Do: – Explore the nature of the market – who is paying for what?

– Think systemically; optimise globally

– Become aware your implicit bandwidth thinking and its dangers

– Exploit packet-based statistical multiplexing

• Don’ts: – Focus on supply inputs and volume; it’s about outcomes

– Mistake trades for QoS

– Sell circuits – you will be arbitraged (cf ISPs in 1990s)

– Think you can solve this without differentiation

It’s all about the trading space

The logistics companies out-competed the shipping companies because they controlled the resource

trading space

Get in touch to discuss the necessary changes to network design,

operations, marketing & product management to meet OTT challenge

Martin Geddes mail@martingeddes.com