How should telcos meet the "over the top" service provider challenge? By taking full control over the trading space that exists inside every network.

1. Meeting the OTT challenge
Martin Geddes
Martin Geddes Consulting Ltd
© 2013 All Rights Reserved

2. What has to change?
NOW FUTURE
PURPOSE-FOR-
FITNESS
FITNESS-FOR-
PURPOSE

3. 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

4. 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

5. The Facts
Situation

6. OTT voice and messaging are hurting
telephony and SMS revenue

7. Selling data speed and mechanisms

8. Value is measured in data volume
Revenue model:
Proportional to average volumetric demand

9. Cost model
Size to peak demand
Planned upgrades
Volume-driven capacity
planning rules
Unplanned upgrades
Driven by churn
and complaints

10. 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”

11. 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

12. 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

13. 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

14. 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?

15. What’s wrong
Complication

16. Speed (and volume) are not value
Dangerous myth:
More Speed is Always Better

17. Contention exists!
Need to consider
variability, not just speed.
Source: Predictable Network Solutions Ltd

18. Black cygnets: small “bad
coincidences” create bad experiences

19. These coalesce under high load

20. And create ever more
‘black swan’ application failures

21. The application
Hierarchy of Need
3. Reasonable bounds on loss and delay
2. Sufficient stationarity
1. Sufficient capacity
Note: exact requirements are application-dependent

22. 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

23. What you need to know
Some theory

24. Capacity demand
TWO sources of network demand
Schedulability demand

25. Capacity demand
LOW HIGH
Feasible Infeasible
MAX CAPACITY
TWO fundamental resource limits
Feasible
MAX SCHEDULABILITY
Schedulability
demand
Infeasible
LOW
HIGH

26. Problem
Schedulability
demand is growing fast
VoIP, gaming, 2-way video,
UC, HTML5 web, WebRTC…

27. Problem
Solving schedulability issues
(i.e. non-stationarity)
with capacity is
inefficient and ineffective

28. Problem
Monoservice network
means costs track the
worst-case schedulability
limit of loading

29. 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

30. The consequence
Undesirable
future

31. 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

32. Failure of technology to keep
up with ever rising demand
forces shorter upgrade cycles
Rising load makes
service quality fall,
forcing upgrades
ServiceQuality
Time
UndepreciatedAssetValue
Time
Mathematically unsustainable

33. 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

34. Race to the bottom?

35. The alternative
Desirable future

36. 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

37. Packaged (OTT) cloud applications
• Available when and where
you need it
• Right quantity and quality
• At a cost you can afford
• Easy to consume

38. How to get there?
The Question

39. 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?

40. What do I need to do?
The Answer

41. Bandwidth Quality
Need to frame the problem
differently to make it soluble

42. 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.

43. TELCOEND 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

44. 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

45. 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

46. 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

47. It’s all about the trading space
The logistics companies out-competed the shipping
companies because they controlled the resource
trading space

48. Get in touch to discuss the necessary
changes to network design,
operations, marketing & product
management to meet OTT challenge
Martin Geddes
mail@martingeddes.com