Realities and Myths of Scaling Up For Growth Transform to Outperform December 2010 CONFIDENTIAL AND...
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Transcript of Realities and Myths of Scaling Up For Growth Transform to Outperform December 2010 CONFIDENTIAL AND...
Realities and Myths of Scaling Up For Growth
Transform to Outperform
December 2010
CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited
Bancon plenary presentation document
McKinsey & Company | 2
The next decade will see massive scale-up of Indian banks in terms of size and complexity
SOURCE: McKinsey analysis
ESTIMATES
Scale-up in terms of size
▪ Increasing diversity of product/market segments (e.g., youth/retirement; urban/rural; emerging/large corporates)
Scale-up in terms of complexityScale-up in terms of complexity
5x
5.5x
4.1x
▪ More sophisticated customer needs and interactions (e.g., integration with corporate ERPs, supply chain financing)
▪ Increasingly expansive network of JVs, partners and alliances (e.g., payment specialists)
▪ Increasing competitive intensity (e.g., NBFC specialists, IT, Telco, Retailers)
▪ Increasing pace of regulatory change and globalization
Assets
Profits
Market Cap
6000 30,000
2010 2020
60 320
690 2,800
’000 cr
Performing banks will be 2-3X their current size in assets in next 3-4
years
Banks will enhance structures, talent and processes to cope with
complexity
McKinsey & Company | 3
However banks will need to see through the myths and realities associated with four barriers to scale-up
Balancing operating architectures for scale and responsiveness
1Differentiate customer experience while improving productivity
2Using IT as competitive weapon
3 Building required leadership & talent
4
McKinsey & Company | 4
Reality: Balance between need for scale and need for local responsiveness will vary by product/market CASE EXAMPLE
1
Key drivers
▪ Maturity of processing infrastructure
▪ Inherent riskiness of product/market
▪ Last mile constraints
▪ Availability of talent
1
2
3
4
Urban Retail Loan origination
Typical operating architecture for major Indian banks by product/market
SME loan processing
Urban CASA opening
Rural banking
▪ Highly centralized with typically 2-3 processing sites across nation in some cases
▪ Regionally centralized with 30-50 retail loan processing sites for home loans; servicing may be even more centralized
▪ Education and auto loans may be processed in the branches
▪ City-level centralized with 60-80 SME processing centres targeting 40 major cities which account for most of the opportunity
▪ Primarily done through branches
▪ In some select, high opportunity districts, may use district-level hubs
Centralized
Decentralized
McKinsey & Company | 5
Myth: Decentralised models are moreefficient than the centralised ones
DISGUISED CLIENTEXAMPLE
Mortgage Bank A – Centralized
Mortgage Bank B – Decentralized
Operating model
Single processing center nationwide
~20 processing centers, located at each wholesale branch
Scale
~20,000 loans p.a., processed at a single location
~20,000 loans p.a. processed across the network
Underwriting turn-time
>3 days 1-2 days
Unit cost per loan1
>$1,200 <$900
1
Drivers of performance▪ Superior coordination
from front to back office
▪ Standardised processes across all processing units
▪ Optimised network architecture across front- middle- back office
1
2
3
1 <____>
McKinsey & Company | 6
Reality: 5-7 major processes account for >70% of customer interactions and operations headcounts
Major processes
Typical performance focus
Average banks Best in classMetric
Account opening and depositsAccount opening and deposits
Application to issuance of welcome kit
5-7 days 1-2 hours
Home loan processingHome loan processing
Application to disbursement
12-15 days
<3 days
SME loan processingSME loan processing
Application to disbursement
18-20 days
5-7 days
Branch sales Branch sales
Quality of advice
Product specialist
Team-based
Customer careCustomer care
Time elapsed for resolving problem
SpeedPredict-ability
SOURCE: FIG O&T Practice
1
McKinsey & Company | 7
Myth: Inherent trade-off between customer experience and productivity
Median across 3 banks
Best in class
5-7
15-18-69%
3-5
1-2
+167%
<3
10-12-73%
Credit appraisal productivity
Impact of eliminating waste in home loan processing (composite across 3 big Indian banks)
Applications lost due to delays
Turn around timeSources of waste
Days
Files per day per FTE
Percent
2
▪ Multiple and error-prone hand-offs
▪ Complex procedures and documentation
▪ Mis-aligned capacity and demand
▪ One-size-fits all process
McKinsey & Company | 8
Reality: Lean methods have unlocked capacity and increased speed in developed and emerging markets
30
30
35
35
40
65
70
70
80
40
80
30
30
35
50
50
60
60
Australia
UK
UAE
Peru
Chile
US
Malaysia
Singapore
US
Branch
Branch
Branch
Cycle time reductionCapacity increaseCountry Channel
Branch
Branch
Intermediary
Field sales
Branch
Direct
SOURCE: McKinsey analysis
Percent
2
McKinsey & Company | 9
Reality: Information, not just technology will be the strategic weapon of future
SOURCE: 2010 Transforming Banking through IT Survey of Indian banks
7
73
Decrease
20
Keep same
Increase
Future IT spend
Planned future IT spend % of CIOs who selected the option
Future priority investment areas for IT% of of CEOs that ranked a given choice in Top 3
Alternate retail channels
Core Banking System
Support function systems (e.g., F&A, HR)
CEO response
10
11
29
43
54
Specialised product systems1
1 Examples include cash management, trade finance, treasury systems and others
MIS/CIM/Risk management
Increasing IT investments … ... with particular focus on MIS/CIS/Risk
1. Create an on-demand information architecture
2. Establish information governance
3. Build informa-tion analytics capability
…will make information a strategic weapon
3
McKinsey & Company | 10 SOURCE: 2010 Transforming Banking through IT Survey of Indian banks; McKinsey analysis
Challenges faced in using IT effectively
% of CIOs who ranked given choice in Top 3
% of CEOs who ranked given choice in Top 3
21
29
43
43
50
86
Organisation structure of IT is not aligned to support business units effectively
Difficult to justify economic benefit of IT
Revamping legacy systems
Gaining access to technical talent
Limited understanding in the business managers on how to use and manage IT
Business processes and practices do not change enough to fully realise the benefits of IT and automation
33
33
27
40
87
60
Reality: The main barrier to scaling with IT is not technology, it’s people and mindsets
3
McKinsey & Company | 11
Reality: Architectural simplification is key to scalable IT platforms
SOURCE: Corporate and Press releases
▪ Single technology platform – PARTENON
▪ 2 Regional IT development centres: Madrid and Chile
▪ Four regional operating centres– Madrid– Milton Keynes (UK)– Queretaro (Mexico)– Sao Paulo (Brazil)
▪ Significant cost savings: 25% reduction in transaction costs
▪ Rapid product delivery
3
McKinsey & Company | 12
Reality: Massive leadership gap – especially in public sectors
Addl. required in 2015
300-350
Others (faster promotions, direct hiring)
100
280-300
10
70-80
GapBaseline in 2010
Non-retiring pool
Estimation for officers of the rank of AGM and aboveIndex=100
SOURCE: McKinsey analysis
CASE EXAMPLE
The bank needs to aggressively accelerate capability building of its senior executives to enable them to lead a bigger, more complex organisation
4
McKinsey & Company | 13
It is crucial to embed new leadership skills by applying them in the fields, otherwise it is just theory that will soon be forgotten
3 weeks 3 monthsLearning through Formats
70% 10%Explanation (listening)
▪ Presentation/speech▪ Manual/flyers▪ Video▪ Discussion
72% 32%Example (seeing)
▪ See someone doing
85% 65%Experience(doing)
▪ Role play▪ Practical application day-
to-day
100% 100%Experience(teaching)
▪ Leading others to do▪ Coaching own team▪ Teaching other leaders
Effectivenessmeasured after
Reality: Adult learning research suggests learning is most effective when embedded in real life application
SOURCE: Pesquisa IBM; Whitmore, Coaching
4
McKinsey & Company | 14
Myth: Higher compensation will guard against attrition
6,108
3,542
3327
20
35
61
88
24
15
SOURCE: P360 benchmarking
Above average players
Below average players
Percent
US$/annum
Percent Percent
Percent
Cross-skilling ratio Team leader attrition
Agent compensationProportion of team leaders, ops managers grown internally
Attrition
4
McKinsey & Company | 15
61
12-18 42
< 12
18-24
>24 72
56 104
133
98
114
Higher employee tenure does not ensure higher productivity
Variation in employee productivity
652
341
48%
6.5
9.2
29%
1 Average time taken to service a request / answer a call2 Only agent compensation is considered for calculation
Average processing timeMinutes
Cost per transaction INR
ProductivityCalls/day
Cost per callINRMonths
Example 2: Credit card customer service
Example 1: Email customer service
4
McKinsey & Company | 16
Question
If you are 7 or below on the 10-point self-test, it is time …
1. Hand-offs across functions in all major processes are few and error-free
2. Network of processing sites has the right balance between centralization and de-centralization
3 Limited variance in productivity and TAT across processing sites
4. Ability to meet customer expectations at key moments of truth is monitored and at acceptable levels
5. Productivity of key resources (e.g., credit officers, RM) in major processes is competitive
6. Internal leadership benchstrength to manage larger and more complex businesses is sufficient
7. Your ability to recruit high quality talent and retaining it is high
8. Your training programs are working effectively in delivering the skills and mindsets you need
9. Your IT platform can scale effectively in supporting new products, channels and expected business volumes
10. Your ability to manage information for effective decision making is high