Characteristics of Jack Welch's tenure at GE Contrasted with Jeff Immelt's tenure

1. Jack Welch:
1. chemical engineer, joined GE plastics
2. set and monitored performance targets
1. managers committed to ambitious targets, and were forced to meet them by forcing their subordinates to meet them
3. provide powerful incentives for achievement
4. "stretch" toward company goals (set lofty goals and achieve them in due course)
5. did away with bureaucracy 
6. periodic declaration of strategic initiatives promulgated to all employees
7. "Work out" to incorporate ground-level ideas about process improvement (aspects of Lean)
8. From 1981-2001 GE grew from $30B to $126B
9. Jeff Immelt:
1. Economics and Applied math major, joined GE plastics
   
10. "Where Welch ruled through intimidation and thrived as something of a cult figure, Immelt opts for the friendlier, regular-guy approach. He prefers to tease where Welch would taunt. Immelt likes to cheer people on rather than chew them out. that style has given him a very different aura within GE.He may not be a demigod, but its his man-of the people nature that draws praise from the top ranks to the factory floor."
11. Different economic climate
1. "the exuberance of the late 1990s and the inevitable downturn have created difficult times. Entire industries have collapsed, poor business models have been exposed [ENRON], large companies have filed for bankruptcy and corporate credibility has been called into question."
12. Immelt sought to weather the challenging economic climate by diversifying the GE portfolio
13.  "We all want the stock to go up. But to do that we have to manage the company. In fact, the only way you can run GE is to believe that performance will ultimately drive the stock"
14. "If the annual report has to be the size of the NY City phone-book, thats life."
15. Searching for new top line growth to improve the bottom line. Where could profitable growth be found in the post 9-11 2000's?
16. Identify key global trends for GE to seek opportunities. These were evolving themes and Immelt iterated 
1. Demography- find where there are young (movies) and old (pacemakers)
2. Infrastructure- linked to the next item of emerging markets and government investment
3. Emerging Markets- China, India, Eastern Europe, Russia, Middle East, Africa, Latin America, SE Asia offered 3 X world average growth
4. Environment
17. Like his predecessor, J. Welch, Immelt set ambitious targets of 8% organic growth (excluding M&A growth)
1. exit slow growth businesses
2.  "we don't acquire businesses because we can. We don't go for unrelated fields. We acquire companies that give us new growth platforms where GE capability can improve financial performance and build shareholder value."
18. In opposition to Jack Welch, Immelt focused on his affinity for technology.
1. $100M upgrade to GE corporate R&D center in Niskayuna, NY
2. New global research centres in Shanghai and Munich, Germany
3. By 2008, GE Global Research had over 2500 researchers working in NY, Bangalore, Shanghai and Munich. 
19. Different from Welch, who focused on R&D for short term product development, Immelt focused on longer term development
1. Number of projects reduced from 1000 to 100.
2. For choice technology areas, the focus was not on short term projects, but on large research fields such as :
1. nanotech
2. advanced propulsion
3. biotech
20. Effective Portfolio Management was a key aspect of Immelt's Group Strategy
1. "We did a lot of heavy lifting in our portfolio because we didn't have enough juice. We saw where we needed to go and we found that we wouldn't get there with our existing businesses. So, we bought homeland security, biotech, water-businesses that would give us a stronger foundation for innovation." -Growth as a Process: An Interview with Jeff Immelt, Harvard Business Review, June, 2006.
21. 5 Major acquisition areas between 2001-2009
1. broadcast and entertainment
1. TV networks
1. Telemundo
2. Bravo 
3. Oxygen Media
2. Vivendi Universal Entertainment
2. healthcare
1. diagnostics & equipment
1. Amersham 
2. Abbott
2. financial services
1. HPSC
3. energy
1. alternative energy
1. Enron wind energy 
2. Chevron Coal Gassification
3. Astro Power
2. emission reduction
1.  BHA Group Holdings
3. oil and gas
1. Vetco Gray 
2. Hydril Pressure Control 
4. finance
1. equipment leasing
2. commercial finance
3. credit cards
4. consumer finance

Management Consultancy Presentation (To Goldrock Consulting)

Just to Recap, this project was for Management consultancy where we were asked to help a consulting firm rebuild trust with its longstanding client in the midst of difficulty in implementing Lean and SAP training. Our fictional consulting group from UEBS, called Oculus, made recommendations to the fictional firm named Goldrock.

Scribd

Sainsburrys Bank HR Talk: Jane Brydon

1. What's working and what isn't as a firm?
1. Justin King- CEO of supermarket
2. since 2007, 8-9000 firings
3. engaging colleagues is difficult ("hellish and tough environment")
4. be honest
2. 21M customers a week, 1000 stores, 145,000 employees
1. Tesco main competitor
2. Nectar loyalty scheme (an engagement measure)
3. ethical and renewal image -> emotional link -> goodwill 
4. BOS -> Lloyds
3. How do you make financial services engaging for customers?
1.  provide double nectar points, leverage Sainsburrys customer base (unique selling opportunity)
2. simplicity of communication (to colleagues, to customers)
4. Questions:
1. Leadership training? (mentioned poor leaders)
1. Line Managers, no one-to-one meetings, career leadership
1. simple things? what?
2. Mandatory line management skills, bonus linked
3. who chooses objective? do senior managers choose their own?
4. Do you use Belbin to select teams?
2. Does Sainsburrys promote cycling for healthier employees?
3. Did RBS lose customers to Sainsburrys due to scandals?
4. how did you differentiate yourselves?
5. innovative banking -> Virgin train station banking. What about Sainsburry's?
6. How do you measure colleague engagement? (FS average 65%, Sainsburry's 54%, current Nov 2011 84%)
7. What resources can we give you to help you do your job?
8. How do you feel about our brand?
9. How do you feel about our products?
10. How do you feel about our leaders?
11. How do you feel about your boss?
12. Do I care and share the vision?
13. Kudos systems (people have difficulty in saying thank you)
14. Oscar-style ceremony to show appreciation (recognition)

Manage Employee Engagement

1. How can we engage employees?
1. Research shows that it depends.
2. HR practices
3. Understand people's motivation
4. Create value for the employee, incentive-based?
5. recognition and rewards
6. understand employees' ideas and values
7. people attach meaning to various things (cognates)
8. evolutionary past: emotions allow survival (evolutionary advantage to emotions)
9. anticipation
10. EMO text analysis (software)
11. see: Chomsky on emotions in linguistics
12. are people in your organization talking positively or negatively
13. "tweet" emotional analysis (soccer fans)
14. are emotions fundamentally irrational?
15. are logs of communication biased towards negativity? (people withhold positive comments)
2. Emotional maps
1. brand mapping
2. most employees talk about other functional teams (this can often be negative)
3. ex: complain about the HR department, complain about management team

MC: Individual Assessment

Due March 5th at 12 PM.

Statistics Problem Sets and Remaining Schedule

Week 2

Exercise 1

Week 3

Week 4

1. Call Centers have high turnover rates because of the stressful environment. The national average is approximately 50%. The director of HR for a large bank has compiled data about 70 former employees at one of the bank's call centers.  Use Call Center Data and Pivot Tables to determine the average length of service for:
1. Males and females in the sample
1. Males 1.8 Years average length of service
2. Females 2.0 Years average length of service
2. Individuals with and without a college degree
1. 1.5 Years with College Degree
2. 2.1 Years without College Degree
3. Males and females with and without prior call center experience.
1. 1.7 Years with experience for males
2. 1.8 Years with experience for females
3. 1.8 Years without experience for males
4. 2.2 Years without experience for females
4. Conclusion: We should target inexperienced females for hiring. They stay longer! 
2. Construct a PivotTable to find the average credit score, years of credit history, revolving balance, and revolving utilization based on whether the applicant was a homeowner and whether the application was approved. Credit Approval Decisions



Homeowners, Approved or not















Homeowners, Approved Only



Homeowners, Dis-Approved Only



Non-Homeowners, Approved Only






Non-Homeowners, Dis-Approved Only

1. Ave Credit Score: 652.3
2. Ave Years Credit History: 11.2 Years
3. Ave Revolving Balance: $13,939
4. Note: Utilization not shown above, but just check the utilization box to add it as an additional data item. 
5. Conclusions: Approved Homeowners have on average, 3 times the credit history than Approved Non-homeowners. This is most likely due to their mortgage.
6. Approved Non-homeowners have almost twice the revolving credit balance, on average, as their Home-owning counterparts.
7. Disapproved Homeowners have, on average, a lower credit score than their non-home owning counterparts, although they have a longer credit history (10.7 yrs on average) and a lower revolving credit balance ($14,867)
3. The Spreadsheet Energy Production & Consumption provides various energy data from 1949 to 2007.




1. construct and area chart showing the fossil fuel production as a proportion of total energy production
2. construct line charts for each of the variables
3. construct a line chart showing the total energy production and consumption during these years
4. construct a scatter diagram for total energy exports and production
5. discuss what the information in the chart conveys
1. There is a growing gap in the total consumption and production of energy.
2. Fossil Fuel Consumption is rising in a fixed proportion to total consumption.
3. Fossil fuel production is flat, and not keeping pace with fossil fuel consumption.
4. Referring to the Call-Center Data, how strongly is length of service correlated with starting age? 

1. The correlation coefficient is obtained using the Excel CORREL(array 1, array 2) function.
2. R=-0.61 meaning that as the starting age increases, the length of service tends to decrease.
3.  This means that the firm is retaining fewer employees who join the company later in life.
5.  Compute the mean, variance and standard deviation for all of the variables in the File: Major League Baseball

6.  Construct a chart to show the proportion of funds in each investment category in the spreadsheet: Retirement Portfolio.

7.  Week 2, Question 1: Based on the data in the spreadsheet Consumer Transportation Survey, develop a probability mass function and cumulative distribution function (both tabular and as charts) for the random variable Number of Children. What is the probability that an individual in this survey has:

1. Less than 2 children -> Answer 72%
2. At least 2 children -> Answer 28%
3. 5 or more children-> Answer 0%
8.  Week 2, Question 2: A Bus company knows that travel time is normally distributed with a mean time of 15 mins, and a standard deviation of 2 mins. What is the probability that:

1. Answers above.
9. Week 2, Question 3
10. Week 3, Question 1: Using the data in the spreadsheet Accounting Professionals, find and interpret the 95% CI for the following
1.  mean years of service
2. proportion of employees with a graduate degree
11. Week 3, Question 2: Using the spreadsheet Consumer Transportation survey, develop 90%, 95%, and 99% confidence intervals for the following:

1. mean hours per week spent in vehicles
2. average weekly miles driven
3. proportion satisfied with vehicles
4. proportion with at least 1 child
12. Week 3, Question 3: Trade associations such as the United Dairy Farmers frequently conduct surveys to identify characteristics of their membership. If this organization conducted a survey to estimate the annual per-capita consumption of milk and wanted to be 90% confident that the estimate was no more than +/-0.3 gallons away from the actual average, what sample size is needed? Past data have indicated that the standard deviation is approximately four gallons.
1. standard error of z distribution: Zval*(s / sqrt (n))
2. s = 4
3. z(90) = -1.64
4. 0.3 = -1.64 * 4 / sqrt (n)
5. n= 478.151 or 479 people (round up) (note there is rounding error due to rounding to 2 decimal places, excel will report 481...)
13.  Week 4, Question 1: A reporter claims that a call center (Call Center Data) has an average tenure of no more than 3 years. Test this hypothesis.
1. Set H0 (Null Hypothesis) to disprove the reporter, that tenure exceeds 3 years.
2. Set H1 (Alternative Hypothesis) to Reporter's claim (< 3 years)
3. Because H1 is <, a lower tail test is called for. Calculate the "Lower Critical Value" for t. Use the Excel Function T.INV(0.05, 69) for 95% confidence and DOF = 69.
4. This lower critical value should equal -1.67.
5. Now calculate your test statistic = sample mean - hypothesis mean (3) / standard error of the mean = -8.4
6. -8.4 < -1.67 within the rejection region of the left-tail. Therefore, reject the Null Hypothesis. You 95% confident that the mean will be less than 3 years.
14. Week 4, Question 2: Use the spreadsheet called "Sales Data". An industry trade publication stated that the average profit per customer was $4450. Can this company claim that they meet the standard? 
1. Set H0 to prove that our sales average = 4450. This is a two tailed test. H1 states that our sales average does not equal 4450. Calculate the upper and lower limits for rejection, using the following formula in excel: =-T.INV.2T(0.05, 59) (lower limit). T.INV.2T(0.05, 59) (upper limit). Next calculate the t-test statistic = ( sample mean - 4450 ) / sample standard dev / sqrt(60) We fail to reject the Null Hypothesis, and we state that we are at the industry mean sales.
2. To prove that we exceed the average, set H0: our average < industry average and H1: our average > industry average using a upper tail test. The upper limit is -T.INV(0.05,59) (minus because the excel function gives you the lower test by default... Conclude that our average cannot be higher, and fail to reject H0. We have a smaller or equal mean to the industry...
15. Week 4, Question 3: Assume equal variance between two populations and
1. test H0: service length for males = for females
2. test H0: service length for experience = no experience
3. test H0: service length no college = with college
4. test hypothesis for variance equality. Repeat above problems with unequal variances as required.


 

To Apply Pivot tables, you need data with Column labels in the first row.

What is a Pivot Table you say? According to Microsoft: 

PivotTable report An interactive, cross-tabulated Excel report that summarizes and analyzes data, such as database records, from various sources, including ones that are external to Excel.

Here's how to access this feature: 

How to access Pivot Tables

1. Select any cell in the data set and choose PivotTable from the Data Tab
2. Select Pivot Table

Make a new worksheet from your new Pivot Table

Accounting: ROI Dangers

ROI suffers from  the problems of manipulation, short-termism, inflation and prediction. To address these problems, the following frameworks have been developed:

• balanced scorecard
• performance pyramid
• performance prism
• critical success factor

Accounting: ROA Dangers

Take the example of British Aerospace and their ageing asset, the Concorde. The supersonic planes  were kept in order to boost the company's ROA. The reason was that the book value had been depreciated to a single Pound (£), and the ROA boost that they provided BA was useful for propping up the stock price.

Accounting: Ratio Interpretation

1. Sales Growth: An Increase is good unless:
1. Profit margins are shrinking
2. Growth in asset investment is greater
3. Credit control is worsening
4. Signs of over-trading are present! 
5. Growth isn't converted into cash!
2.  Ratios are a tool for comparison and for questions
3. Corporate Valuation Examples
1. ABC plc (a non-quoted company)
2. Non-current Assets (£M) 80
3. Current Assets 45
4. Current Liabilities 28
5. Non-current liabilities 40
6. Equity: share capital (£1 shares) 10
7. Retained Earnings £47
8. Total 125
4. The following of ABC's assets have market value in excess of their balance sheet value
1. Property B/S value= 30, Market = 40
2. Inventory value=15, Market=30
5.  What is the Book Value?
1. Look at the B/S
2. Book Value = Equity / Number of Issued Shares
3. Equity = RE + SC = 57
4. Number of Shares = 10
5. £5.70 per share

Accounting Examples

Bank

1. Share Capital = £1000
2. Earnings = £1000
3. Manager owns 10 shares @ £1 per share
4. Bank buys back 990 shares for £990 -> £2000 - £990 = 1010
5. New Share Capital Figure = £10
6. Earnings = £1000
7. Change in Earnings: -£990
8. Capital Redemption Reserve +£990

DA: Statistics Summary (Windows 7, Teaching Lab PC's)

 

Launch Excel via PHstat

Click on File, Options

Enable Analysis and Solver Add-ins

Data Classification (p32, p81)

1. Categorical- ex: separated by region, customer type 
1. Use Proportions to describe this data-type 
2. Cross Tabulation- tabular method that displays the number of observations in a data set for different subcategories of two or more categorical variables
3. The subcategories of the variables must be ME and exhaustive, meaning that each observation can be classified in only one sub-category
4. Common Marketing Research Tool
2. Ordinal- ex: ranking data (1st - Last)
3. Interval-  no natural zero. ex: temperature in C or Fahrenheit
4. Ratio- have a natural zero. Sales dollars ($0 is natural zero for 0 sales activity)
5. Types of Data
1. Cross-sectional- data that are collected over a single period of time
2. Time-series- data collected over time
6. Number of Variables
1. Univariate- single variable
2. Multivariate- two or more variables 

PM: Estimating

1.  Projects by definition, include a large degree of uncertainty.
2. "To predict costs. The art of approximating the probable worth (or cost), extent, quantity, quality, or character of something based on information available at the time." -NASA
3. You have decided to repaint your living room. You want to go buy the paint but you must first figure out how much you need. How many gallons will you need, and how much will it cost?
1. Basic Information:
2. 1 gallon of paint covers 350 sq ft. and costs 27 Pounds
3. Room is 16X14ftX8 with one door 3X7 and three windows (3X4)
4. Paint all surfaces with 2 coats. No fractional gallons.
5. Solution: 108 pounds
4. You have the least amount of information at the beginning of a project, but the greatest need for estimation. Making the correct choices early can save money later.
5. Proposal Estimate: +/- 50 % feasibility (AACE: Concept screening -> class 5)
6. Budget Estimate: +/- 20 % viability (AACE: feasibility -> class 4, pre-design)
7. Sanction: +/- 10 % obtain funding (AACE: budget estimate -> class 3)
8. Control: +/- 5 % measure progress, assign resources (AACE: definitive class 2)
9. Tender: +/- 2 % prepare tender (AACE: detailed -> class 1)
1. CTR:Cost, Time, Resource
10. Estimating Methods:
1. subjective: historical project comparisons
2. parametric: proportional
3. analytical
11. Cost Components 
1. labor
2. materials
3. equipment (buy/lease) Cap-Ex vs Op-Ex
12. Data sources
1. supplier quotations
2. trade literature, technical literature
3. company historical data
4. computer systems
5. government figures
13. Estimating Accuracy 
1. level of accuracy depends on:
1. relative size of part and project
2. level of WBS
3. error in the part & in the project

CS: Zara Case (309-113-1)

1. Zara Case (309-113-1)
2. Strategy:
1. vertical integration
2. long incubation period (before going to other countries)
3. selective international expansion
4. aggressive in European Markets, cautious in the US
3. Comptetitors
1. Hennes & Mauritz (Sweden) 
2. Mango (Spain)
3. Top Shop (UK)
4. Market Positioning:
1. Fashion on horizontal, Price on Vertical
5. Technology usage:
1. flexible production
2. lean
6. Recommendations:
1. Online Shopping 
2. Globalization of brand? 
7. References:
1. Zara Enters India (FT)
2. Zara: Taking the Lead in Fast-Fashion (BBW)
3. Inditex's strong growth driven by emerging markets
1. Spain's Inditex, owner of the Zara fashion label, reported robust first-quarter earnings driven by rapid growth in emerging markets...
4. Inditex sets the pace for fashion retailers

 

PM: Offshore Windfarm Project (List of UK Farms)

1. 2000: Blyth Harbour, Northumberland
2. North Hoyle, Wales
3. Scroby Sands, Norfolk
4. Kentish Flats, Kent

Land leased from the Crown Estate
The following Images are taken from their "Guide to Offshore Windfarms"

 

 

Courtesy of Seagreen Energy

Financial Analysis: David Hatherly (Enron)

1. Four Feedback Failures of Accounting (Enron)
1. Failure to identify the performance of intangibles
2. Failure to link reward with risk
3. Failure to separate present performance and expected future performance (productive gains and speculative gains)
4. Failure to focus on the legacy value of promises
2. Rewards are "headlined" while risks are hidden in the footnotes
3. Enron's year 2000 annual report:
1. "We are participating in a New Economy, and the rules have changed dramatically. What you own is not as important as what you know. Hard wired businesses such as energy and communications, have turned into knowledge-based industries that place a premium on creativity. Enron has been and always will be the consummate innovator because of our extraordinary people..."
4. Enron's History:
1. Natural Gas producers/supplier, expands through acquisitions
2. Expands to other utilities as producer/supplier, became asset heavy
3. grew to an international scale utility producer/supplier, gained US political support
4. expanded into new markets into other utilities, obtained regulation easing
5. entered into long term contracts from supplier side, sold long term contracts to customers, creates a time mis-match, creates risk
6. Enron's Activities mirrored Banks: borrow short term but lend long-term (risky before even consideration of investment banking) 
7. Began an "online trading" scheme (only business to have value when they crashed)
8. Dispose of utility assets, began SPV (special purpose vehicle development)
9. Began a move into Broadband, in order to mirror their energy trading scheme
5. Energy/Communications
1. transportation and distribution
2. wholesale services
3. retail energy services
4. broadband services
6. Year 2000 Balance Sheet (millions, USD)
1. Fixed Assets and other investments: 22,496
2. Debt: (13,547) -> 8949
3. Intangibles: 3638
4. Cash: 1374
5. Other current assets: 16,989
6. Current liabilities: (16,232)
7. Working Capital: 2131
8. Deferred creditors (4336)
9. Price risk assets 1088 (3248) (net position on all of the futures and options entered into)
1. fair value stated (according to Enron)
10. Equity: 11,470 (book equity, not the market value of shares because market will )
7. Enron Income Statement
1. Natural Gas: 50,500
2. Electricity: 33,823
3. Metals: 9,234
4. Other: 7,232 100,189
5. Costs and expenses: 98,836
6. Operating Income: 1,953
7. Other Income and Deductions
1. gains on sale of assets: 146
2. interest (net), tax (1120)
8. Separating Productive and Speculative gain
1. traditional vs. casino banking! 
9. Enron's Profit making methods
1. selling options/futures (fees)
2. selling bundled long term contracts for NPV on a market
3. underlying asset value increase/decrease (depending on contract)
4. traditional energy rates (legal) 
10. Banking is a highly geared business
1. borrowings are greater than our equity (extremely risky)

Angus Cockburn: Aggreko

1. 1985: Edinburgh University Graduate
1. Scottish chartered account
2. IMD MBA
2. Restructuring and turnaround at Pringles
3. Aggreko
1. Power Infrastructure as a Service
1. 30kW->2MW
2. 1MW->container
2. chillers, heaters for temperature control
3. head office in Glasgow
4. quirky niche business
5. power supplies (emergency especially)
6. London Olympics
7. 1962: business founded in Netherlands
8. Industrial Work
9. new growth areas in gas generation
10. over-spec for global mobility of assets (generators)
11. IPP= Intl' Power Projects
12. average control value approx $16,000
13. Returns on Capital Employed 27%
14. 20 ft. ISO container
4. Competitor
1. GE energy rentals (acquired)
2. Caterpillar
3. Cummins
4. Siemens
5. APR
5. Core Competencies
1. logistics outsourced (centralized?)
2. IT outsourced
3. market understanding (city generation)
6. Culture
1. Pace
2. Passion
3. Performance
4. 30 people in the head office
5. Entrepreneurial and Customer Focused
7. Threats
1. security in developing countries 
2. Local Tax authorities
3. Tax on CO2 emissions (carbon trading)
8. Questions:
1. Does Aggreko hire security contractors? In house security
1. Pakistan PatrolRisk, Egis
2. How to you adapt to local infrastructure?
3. What functions do you outsource, which do you keep in-house? Engineering in house, logistics (trucking) outsourced,
4. Efficiency in asset use, systems development growth area?
5. How long did it take to implement the ERP system? 6 years
9. Financial Measures
1. last 12 mos utilization -> project out
2. price
3. WACC=7.5%, hurdle rate 11% (IRR)
10. Business Summary:



2009 Summary: Courtesy of Aggreko

1.  

Eviews Software (Statistics)

This is the software used by our MSc in Finance students, and I think it makes much more sense than fooling around with plug-ins in Excel. With a couple of clicks you can get a lot of data out of Excel tables.