ULTIMO AVISO DE GUSTAV AQUÍ

Gustav muy cerca de la isla Pequeño Caimán, se sigue intensificando.

En el último reporte del centro nacional de huracanes, el centro de Gustav se encontraba a tan solo 40 km al sur de la isla Pequeño Caimán y Caimán Brac, a 145 km al este de la isla Gran Caimán y a 585 km de la costa oeste de Cuba. Se sigue moviendo hacia el noroeste a 18 km/h y se espera que este movimiento continúe durante los próximos días.

El último reporte del avión cazahuracanes registró vientos de 130 km/h  con ráfagas más intensas, con esta fuerza, Gustav es un huracán categoría 1 de la escala Saffir-Simpson, Gustav será un huracán de categoría 3 al momento de cruzar la costa oeste de Cuba. Los vientos con fuerza de huracán se extienden a un radio de hasta 45 km mientras que los vientos con fuerza de tormenta tropical hasta 260 km.

La presión reportada por el avión cazahuracanes fue de 975 hPa aun bajando rápidamente señal.

En la imagen de satélite podemos apreciar la presencia de un ojo durante periodos de tiempo, durante esta noche la estructura del centro estará mejor definida.

En México, las posibilidades de presenciar vientos de tormenta tropical en Cozumel han bajado a 15% mientras que la posibilidad de vientos de huracán mantiene casi nula en 1%.

CONDICIONES EN VIVO

We can all agree that there are no facts about the future.  However, that doesn't mean that the future lacks a rich structure by which it can be explored when standing in the present.  There is a decision pattern that can provide the context for every estimate or scenario of the future.  Stated another way, every assumption has a decision context; it can be unambiguously placed within a Decision Network model of the business situation.  There are no exceptions!

It's been almost 2 decades since I made a list of assumptions to describe or back-up my view of the future.  Every assumption that I can think of ends of being a fragment of decision data such as:

• Criterion: Must limit or value that a stakeholder associates with a specific requirement/goal in a specific decision
• Alternative - possible courses of action that we or a competitor might take for a specific decision
• Performance estimate - the anticipated effectiveness of a specific alternative against a specific criterion/factor and our basis-of-estimate
• Risk - a potential failure mode associated with a specific alternative and its probability and seriousness
• Opportunity -a potential windfall associated with a specific alternative and its probability and potential benefit
• Derived requirements - inherent consequence associated with an alternative that constrains other decisions, i.e. creates a decision-to-decision dependency that would otherwise not exist
• Tasks - Work and resources required to inform a specific decision or to implement an alternative
• Alternative dependencies - Timing/composition relationships between alternatives across multiple decisions that constrain roadmap time estimates

These bits of data don't float in free space somewhere, but they are firmly attached (and only have meaning) in context of a specific decision (a pre-existing, fundamental question/issue that demands an answer/solution).  If you have a proven and comprehensive decision pattern and decision-centric information model, every assumption can be precisely described and placed within this decision model.  This makes your assumptions more:

• Visible
• Clear
• Testable
• Actionable

So the next time you're tempted to build a list of assumptions (or are trying to get your head around a list created by someone else), take a moment and ask, "What decision does this assumption belong to?"  and "What type of decision data is it?"  Or even better, subscribe to my Decision Driven® Strategy web service and paste it precisely where it fits.

Northwest winds across northern Florida triggered some heavy migration into the Sunshine State last night, while easterly winds over south Florida pushed moderate levels of migrants inland. Last night also marked another departure from the Keys towards Cuba, a sure sign that fall migration is again underway. Here's the radar from 7:00pm last night through 5:00am this morning.
Frames are every 1/2 hour. Click on the thumbnail to view the full-sized animation.

Looking at the southeast composite you can really see the heavy migration all along the northern border of Florida. Most of these birds were heading SSE, being brought in on a northwesterly tailwind. Winds turned northeasterly, and eventually easterly, as one moved south through the state (and was due east in Miami at 5:00am). This change in wind direction is reflected in a decrease in migration activity as the Miami and Key West radars showed only light (Key West) to moderate (Miami) migration levels. With easterly winds over South Florida, expect the best birding conditions to be inland or on the west coast. Given the push into the Keys early this morning, Key West should see some good birds at first light. The best bet, though, appears to be north Florida, where migrant hotspots from the Panhandle to Jacksonville should be seeing good numbers and diversity this morning. As always, I look forward to hearing about your experiences in the field!

Good Birding,

David

Please don't forget to become a member of the Badbirdz/Woodcreeper flock today. You can read the Become a Member post to find out more information.

My assistant is sitting on 10 invoices which total $30K which I have ordered her to input. Her response, initially, was that my predecessor didn't make her do that. My predecessor was not that familiar with GAAP (Generally Accepted Accounting Principles) which has certain concepts such as - Matching Principle (all the costs involved in earning a particular revenue must be recognised at the same time that the revenue is recognised) and Conservatism (if there is liability to pay for something, we must recognise that liability immediately).  We got $30K in services in August, ergo we must recognise the costs incurred in earning this month's revenue.

She's going to input the invoices, but she's grumbling that she may not have time. I told her that if she doesn't have the time photocopy the pesky invoices and I'll accrue them.

And not only is my assistant just full of the joys of life, one of my co-workers was trying to wrap her head around the fact that the Accounts Receivable Clerk has no access to the Accounts Payable Subledger (that whole segregation of duties thingy). Took me nearly an hour but I explained to her how she can process a particular transaction across two different subledgers by using her own assistant.

Yesterday it was helping her figure out how to complete her Q3 Forecast. She didn't know that if you hold your mouse button down in Excel and drag across a column or row that there will be a preliminary sum that one can check against the calculated forecast (ie, to make sure she's entering the numbers correctly). Oh the joys of working with technoboobs!

Approach.

In many organizations a modern information infrastructure for KRI reporting will be missing. This doesn't mean KRI's cannot be reported. It does mean however that it will cost a lot of effort. It also limits the reporting to Key Risk effects only. Reporting more forward looking metrics like risk causes and control effectiveness as well as putting Key Risk effects into the right business context are simply not do-able when reports are build manually.

The following questions need to be answered before setting up KRI reporting:

1. To whom will the KRI's be reported, the board, product owners or operational managers?

Each management reporting level does have it's own characteristics. The first difference is the level of aggregation. The board probably only wants a specification of KRI's aggregated at organization level "board minus one". Sometimes also a risk type view (like country or compliance risk) or a product view is also desired. To make the information interesting, the Key Risk Effects preferably are expressed as forecasts of relative impact on personal objectives. This way the KRI report is positioned as a tool to manage personal performance contracts too.

2. What are the main objectives at each management level and how specific are these objectives?

Different management responsibilities result in different objectives, although it is a best practice to align strategic, tactical and operational objectives. The level of reporting also impacts the characteristics of the reported KRI's. At strategic level a KRI should reflect the outcome of different scenario's. At operational level a YTD metric combined with a year end forecast is probably more than sufficient. Finding specific objectives with owners is not that simple. Some of the required attributes could be missing. An objective should have at least

• an owner
• an end date
• objective
• upper and lower thresholds
• near real-time measurement

Referring to performance management and balanced score card approaches you find some type of objectives categorized at the different decision levels:

1. Strategic
   • Financial
   • Market share
   • Human capital
   • Shareholder value
   • Sustainability
   • Control efficiency
2. Tactical
   • Financial
   • Commercial
   • Operational excellence
   • Control efficiency
3. Operational
   • Costs
   • Excellence
   • Percentage hands free processing
   • Control efficiency

3. What Key Risk effect information is readily available that can signal impact on objectives and are the metrics and thresholds aligned with each other?

Find readily available Key Risk effect information that signal impact on one of more of the aforementioned objectives. This information is usually already available in a different context. Some example Key Risk effects are:

• General provisions
• Operational losses
• Complaints and legal claims
• Regulator fines
• Employee training budget
• Staff turnover
• Accepted risks
• Information quality
• Known high risks
• Software patch backlog
• Change management frequency

Bottom line is that metrics are used that signal a potential direct negative impact on objectives. Some of these KRI's appear to be backward looking, but can be made forward looking using regression techniques. Ideally there is enough history information available that can be used to reliably forecast end-of-year results. The next thing that needs to be checked is if these metrics are normalized. In other words, does the information from one source match with that of another source. For example: the recording of complaints doesn't necessarily use the same product categories as for instance the financial accounting or sales force system. Relating KRI's to objectives is not that difficult provided some alignment is inplace. Some examples:

• Expected loss frequency impact on operational excellence.
• Expected loss amount impact on RAROC or Economic Capital.
• Expected loss amount impact on efficiency ratio.
• Expected complaint frequency impact on customer attrition.
• Expected number of risks without mitigation impact on control objectives.
• Expected internal fraud frequency impact on control objectives
• Expected change frequency impact on service availability

4. Is it possible to transfer the presented Key Risk effect information into owned actions?

For reported KRI's it is a requirement that these KRI's have business owners. It should be clear who is responsible for managing the KRI. KRI's at different dimensions (organization, product, distribution channel, customer segment) can have different owners. When building a KRI reporting environment it helps to have a clear understanding how these different dimensions relate to each other. When an organization has a mature performance management environment, this should not be that difficult. In the situation this is lacking this impacts the effort needed to construct the KRI solution. Another thing that requires planning is the functionality needed after the reporting is in place. When KRI's signal that objectives are at risk, management will demand action to address the risk. This requires people with analytical skills, high quality information and the tools to execute the analysis. In many cases it doesn't make sense to report KRI's when it is not possible to analyze the underlying information.

5. Is it possible to measure the quality of the Key Risk effect information and is the owner willing to provide the requested information for this purpose?

One of the first things management usually wants to know is how reliable the KRI information is. To make sure management doesn't draw the wrong conclusions the KRI solution needs to be extended. The following quality measures should be considered:

• Try to construct groups of KRI's which improve the interpretation of presented metrics. For instance construct a KRI group of complaints, claims and losses. These KRI's are related and trending of the individual KRI's in most cases should correlate.
• Extract information directly from your core systems. Think of information from systems like the General Ledger, marketing information, product specific operational data, human resource administration etc. The KRI system should not use manually corrected information. When information extracted from core systems is not reliable this is an issue that should be solved and not circumvented. It can help to get these issues on the priority list to make this visible in the KRI reporting.
• Demand that the presented information is not older than one day. This way business can respond quickly to changes in the risk profile and is also able to see quickly whether or not initiated actions have the desired effect. It forces the organization also to implement a fully automated and transparent KRI reporting solution. This reduces the risk of human error or manipulation of information and in the long term also is more cost efficient.
• Request from the information owner a statement of completeness and correctness to get insight in the quality of information. Many KRI's use information from business supporting processes like financial accounting, complaints and claims, audit, credit and operational loss registration, human resource administration etc. This is information not validated by customers and the quality cannot not always be guaranteed.
• Ensure there is an information delivery contract which makes the information owner responsible for the timely notification of changes in the core systems. This way adjustments in the reporting environment can be planned.

Conclusion.
Creating a professional KRI reporting environment is a demanding task. The main success criteria to succeed are:

1. Alignment with performance management preferably at the individual level. This way the KRI-reporting can be positioned as a tool that supports management with managing their objectives (and bonus).
2. Top down approach with adequate and persistent backing from senior management.
3. The creation of an information value chain that extracts and processes fully automated information from multiple core systems.
4. Creative professional analysts familiar with predictive modeling and with access to the information and tooling to analyze and model.
5. Consistent and transparent risk and performance reporting at strategic, tactical and operational level to align management of priorities.

UPP and EMAAR have been weighing on the DFMGI.

UPP is now below 4.00 and heads towards the FIBO 50% retrace of 3.82-3.85. EMAAR has lost its strong multi-year support within the 9 handle and is probably headed towards 8.00

The Dubai Financial Market General Index has recorded A NEW LOW (closing and intraday) for 2008.

RSI 14 still looks very oversold, which doesn't bode well for the market in the near-term.

Also, a wedge or triangle was developing and the index broke out of its lower side.

EMAAR @ around 8 could also mean the DFM GI hovering around 4,650 , a major FIBO retrace of the bull run that started almost a year ago and died early this year.

I don't see EMAAR trading below 8 by October, although it's possible, and would probably happen after a decent bounce in price. Having said that, I think we've seen decent corrections in a lot of the major stocks in the past month and a half, so I can't see the index going below 4,650 in the short-term.

FORECAST

DFM GI stabilizes around 4,650

Look for a BOUNCE of at least 15%

EMAAR around 8.00

time-frame : by October.

Only 1 more day to take the woodcreeper/badbirdz-reloaded, online survey! To the 52 of you who took the survey so far, thanks! To those of you considering taking it, let me assure you that It's quick, painless, and will really help me improve the site, so please take a few seconds to click a couple of buttons. :)
Thanks in advance -David

After checking the radar again, I had to change the post title from "Little migration..." to "Very little migration...". Here's the radar from 7:00pm last night through 5:00am this morning.

Frames are every 1/2 hour. Click on the thumbnail to view the full-sized animation.

Okay... so Fay is finally exiting state left. Good. Good riddance. This storm has put a serious damper on early fall migration (although it has displaced a few pelagic birds at seemingly unlikely sites throughout the state, which, for the birder, is pretty cool). The radar showed no migration over the entire state with the one exception being a small pulse of birds out of the Everglades, across Florida Bay, into the Keys. I'm guessing these were shorebirds, because the winds were clearly southerly and to my knowledge there are no passerines that need to get that far south so quickly as to fight a head wind over water... at least not in late August.

Looking ahead it appears that the southerly flow will stick around until the early part of the week. Coupled with some severe thunderstorms in northern Florida, I don't think we'll see any major influx of new birds until later in the week. There is some talk of easterly winds tomorrow and Monday, which might allow some smaller localized movements if the southerlies slacken over south Florida.
Of course, I'm always happy to hear about the conditions on the ground, so make sure to stop by and let us know what you're seeing!

Good Birding,

David

Please don't forget to become a member of the Badbirdz/Woodcreeper flock today. You can read the Become a Member post to find out more information.

AVISO 3          3:00PM Hora Local - 4:00PM CTM

Se ha emitido una alerta de Tormenta Tropical para la peninsula de Baja California Sur.

A las 3:00 PM hora local, el gobierno de México ha emitido un aviso de tormenta tropical para la peninsula de Baja California desde Santa Fe por el lado Oeste pasando por el sur hasta Buena Vista en el Este. Un aviso de tormenta tropical significa que condiciones de Tormenta Tropical son posibles en el área por lo general dentro de las próximas 36 horas.

El centro de la Tormenta Tropical Julio se ubicó a 405 km al Sur Sureste de Cabo San Lucas México, Julio se mueve al Noroeste a 19 km/h, movimiento que conservará por los próximos 2 días, con esta trayectoria el centro de la Tormenta estará pasando muy cerca o por la costa oeste de la peninsula para el día lunes.

El centro de la tormenta actualmente se encuentra en una zona que no es muy favorable para una intensificación, según los modelos de pronóstico, dentro de las próximas 24 horas encontrara condiciones favorables para aumentar la intensidad de sus vientos, pero no lo suficiente para alcanzar la categoría 1 de huracán. Este sistema, al seguir avanzando hacia el norte se encontrara con aguas muy frías lo que provocara un debilitamiento paulatino mientras siga avanzando, esto se suma la interacción con la península que no es nada favorable.

La trayectoria permanece muy incierta aun por un sistema de alta presión en altura que se encuentra cerca de Sinaloa, esto es lo que ha provocado la curvatura de la tormenta hacia el norte. Estaremos informando de cualquier cambio respecto a esta.

Sus vientos máximos sostenidos son de 65km/h con rachas mayores.

Su presión mínima central estimada es de 1005 Milibares.

Atención para colonias y comunidades en zonas de riesgo, favor de tomar las medidas adecuadas, respetar las indicaciónes de las autoridades locales y de protección Civil.

Reportó
MetMEX Tropical
Jorge Alberto Garza Cossío.

Okay, back to birds... "Wow!" Yeah, that pretty much sums up my reaction every morning after checking the Florida radar... but not because of migration. That stinkin' storm is STILL over Florida! Unfortunately that has meant very little in terms of migration for the Sunshine State... but it has meant for some cool radar images. Check out the composite image first, and see how the storm jogs west early this morning, into the panhandle. Then check out the local radar loops from Miami and Key West and see how apparent the windshift is from SW to S. Pretty awesome! Here's the radar from 7:00pm last night through 5:00am this morning.

Frames are every 1/2 hour. Click on the thumbnail to view the full-sized animation.
As I said before, there was little to no migration over Florida under the current weather conditions. The only notable exception was a pulse of birds leaving the Keys heading south, eventually hitting a strong headwind as the winds turned northerly after midnight (which will probably result in some exhausted birds making landfall in Cuba this morning). Unfortunately the forecast is calling for continued southerly winds through the weekend, putting migration on hold until the weather pattern shifts later next week.

Good Birding

David

P.S. Come check out my migration forecast for the Mid-Atlantic on Birdcapemay.org

Please don't forget to become a member of the Woodcreeper/Badbirdz flock today. For more information, please check out the Become a Member post.

They try to profile their customers. They believe they need to learn about what the customer does what he likes what hobbies he has. Or more granular, what has the customer bought in the past. I remember the Swimming with Sharks by McKay. He has a hundred item profile list of to get to know his customers or to get to know Jack.

What do Sales Men need to know?

The need to know a concept of like minded peers. That people will behave the same way or in similar fashion to people that have recently bought from you. The current context of the prospect is the most important data to get. Current needs and current context. This can be learned by asking and by evaluating data that is current not past data.

Many companies, manufacturing representatives in particular, try to plan by looking at order data or commission reports. The revenue statement will not direct you to current business. Only real time sales prospect data or business pipeline data will bring consumable buying data.

You Do Not Have to Know Jack

This is logical. This is real simple. The rear view mirror view does not direct you to the office every day or to home when day is done. The POS statement should not direct or solely direct strategy for any sales organization. Feedback from prospects or review from the most recent buyers of your products or services are the path to strategy and to sales growth.

How do you Track Emergent Behaviors?

If you are an etailer, you can add algorythms to your site to measure engagement. link, entry trails, queries, mouse movement, exit trails, time on page and more. Virtual bookmarks or a behavioral finger prints can be created to be analyzed if you have a web site and have traffic. Way cool.

If you are a direct salesman, observe. Learn the environment. Get to the context of the engagement. People are way to busy to engage with you unless there is context data or a reason to engage. One observation may be noise. Several engagements observed and which create context shows affinity and like peer behavior.

Forecast Data can Show Emergent Behavior

Accurate sales pipeline information cam be had using the right sales tool. A sales software that can get near realtime data from directs and in-directs sales. CRM, salesforce.com, ms crm, even our product Dataforcecrm crash into the wall. There is no easy and reasonable way to get data from channels. Too expensive and too training intensive. DataForceCRM, being FREE software comes close but still user training is high.

Revolutionary software like onlinesalessoftware.net easily get sales data from in directs. Hundreds of in direct salespeople can collaborate using simple, light on line sales software and a tool called LeadNET. Data can drive lead generation, new products, new tactics and new sales. This is emergent behavior. Here is just one example where accurate sales data can drive strategy. I sell four products, case erectors, sealers, labellers and wrappers. My forecast for Q4 looks like this:

• Case erectors 800000USD
• Labellers 780000USD
• Printers 23000USD
• Sealers 42000USD

This may tell me, by the way this company sells only through distributors, that salesmen are Printer and Sealer stupid and unable to sell these products. More likely, since even a dummy can sell something sometimes, the products have issues. With this data I can determine what the issue may be. I can find out why the 2 other products which are bundled with the leading leading products are not performing. Here are some tactics:

• Increase laggard product data flow to sales teams.
• Do competitive analysis to detect laggard product weaknesses.
• Train sales qualification techniques.
• Or.... focus on the most popular products and own this space.

Automobile sector plays a vital role in Turkey’s economy and it has taken an important place in the export mix from the country. The automobile export in 2007 from Turkey was nearly 75% of its total auto production, a straight growth of 18% from the previous year. Increasing export volumes are making Turkey the next export hub for automobile, says the research report – “Turkey Automobile Sector Forecast (2008-2012)”

The emergence of Turkey as an export center is attracting major players from across the world to invest in the auto sector. In fact, FDI inflow in the sector has been continuously increasing from past few years on account of Turkey’s strategic location and closeness with both European and the Middle East countries. Various automobile giants have made Turkey a gateway to enter the European auto markets and taking the benefits of government incentives.

The report studies the Turkish automobile market, comprising of passenger cars, commercial vehicles, tractors, and automotive component market, comprehensively. It also evaluates the export market and opportunities for the automobile industry and its associated industries.

Key Findings

Free Trade Zones (FTZs) are designed to encourage trade to and from Turkey, boosting the automobile sector in the country.
Passenger car segment has the largest share in all aspects of the automobile industry i.e. exports, production, imports, and sales.
Production of automobiles in Turkey grew by 11% in 2007 over 2006.
Automotive component production grew at a CAGR of 21.55% during 2003–2007; therefore, the annual automobile production is estimated to increase to 1.8 Million by 2012.
Exports by the Turkish automobile industry are projected to surge at a CAGR of 11.49% during 2008-2012.
Key Issues and Facts Analyzed

What are the driving factors for the Turkish automobile industry?
What are the trends in automobile component industry?
What are the opportunities for the automobile industry and its associated industries?
Which segment of the automobile sector holds major share?
What would be the projected growth of automobile industry in various aspects?
Who are the major players in the Turkish automobile industry in terms of production, exports and sales?
Research Methodology Used

Information Sources
The information has been taken from authentic and reliable sources like books, newspapers, trade journals, and white papers, industry portals, government agencies, trade associations, monitoring industry news and developments, and through access to more than 3000 paid databases.

Analysis Method
Methods, like historical trend analysis, linear regression analysis using software tools, judgmental forecasting, and cause and effect analysis, have been used for a prudent analysis.

Table of Contents :-

1. Analyst View
2. Automobile Industry - Turkey vs European Countries
3. Why is Automobile Sector Performing Well?
3.1 Booming Economy
3.2 Government Initiatives & Incentives
3.3 Location
3.4 Production Cost
3.5 Infrastructure
3.6 Foreign Direct Investment
4. Turkey - Automobile Industry
4.1 Domestic Market
4.1.1 Production
4.1.2 Sales
4.1.3 Import
4.2 Export Market
4.2.1 By Volume
4.2.2 By Value
4.2.3 By Vehicle Type
4.2.4 By Country
4.3 Performance by Segment to 2012
4.3.1 Passenger Cars
4.3.2 Pick-up Trucks
4.3.3 Buses
4.3.4 Trucks
4.3.5 Farm Tractors
5. Automotive Component Industry
5.1 Domestic Market
5.1.1 Production
5.1.2 Demand
5.1.3 Import
5.2 Export Market
5.2.1 Spare Parts & Accessories
5.2.2 Tyres & Tubes
5.2.3 Batteries
5.2.4 Safety Glass
6. Industry Analysis
6.1 Opportunities
6.1.1 Component Manufacturers
6.1.2 New Infrastructure Set-up
6.1.3 Untapped Domestic Market
6.1.4 Steel & Aluminium Industry
6.1.5 Insurance Market
6.1.6 Alternative Fuel Cars
6.2 Roadblocks
6.2.1 Steel Price
6.2.2 Interest Rates
6.2.3 Surging Oil Prices
7. Key Players
7.1 Ford Motor Company
7.2 Hyundai Motor Company
7.3 Toyota
7.4 Renault SA
7.5 Tofas

List of Tables :-

Table 3-1: Turkey - Population Breakup by Age-group (%), 2007
Table 3-2: Turkey - Transportation Infrastructure
Table 4-1: Turkey - Affordability Rank for Automobile
Table 4-2: Turkey - Automobile Exports by Country (in Million US$), Jan-May 2007 & Jan-May 2008
Table 6-1: Turkey & EU - Automotive Penetration (per ‘000 Population), June 2007
Table 7-1: Ford Motor Company - Strength & Weakness
Table 7-2: Hyundai Motor Company - Strength & Weakness
Table 7-3: Toyota - Strength & Weakness
Table 7-4: Renault SA - Strength & Weakness

List of Figures :-

Figure 2-1: Turkey - Growth in Automobile Production w.r.t Leading European Countries (%), 2007
Figure 2-2: Turkey - Automotive Trade with EU (in Billion Euro), 2003, 2005 & 2007
Figure 3-1: Turkey - Labor Cost in Automotive Industry w.r.t Other Regions (in US$/Hour), 2004
Figure 3-2: Slovakia - Rating w.r.t Other European Countries on the Availability of Skilled Labor, 2007
Figure 4-1: Turkey - Automobile Production (in ‘000 Units), 2003-2007
Figure 4-2: Turkey - Automobile Production* Structure (%), 2007
Figure 4-3: Turkey - Share of Top 5 Players in Automobile Production* (%), 2007
Figure 4-4: Turkey - Forecast for Automobile Production** (in Million Units), 2008*-2012
Figure 4-5: Turkey - Automobile Retail Sales* (in ‘000 Units), 2003-2007
Figure 4-6: Turkey - Domestic Automobile Wholesales* (in ‘000 Units), 2003-2007
Figure 4-7: Turkey - Domestic Automobile Wholesales* Structure (%), 2007
Figure 4-8: Turkey - Share of Top 5 Players in Domestic Automobile Wholesales* (%), 2007
Figure 4-9: Turkey - Automobile Imports (in Billion US$), 2003-2007
Figure 4-10: Turkey - Automobile Imports (in ‘000 Units), 2003-2007
Figure 4-11: Turkey - Automobile Imports* Structure (%), 2007
Figure 4-12: Turkey - Automobile Exports* (in ‘000 Units), 2003-2007
Figure 4-13: Turkey - Automobile Exports (in Billion US$), 2003-2007
Figure 4-14: Turkey - Share of Top 5 Players in Automobile Exports* (%), 2007
Figure 4-15: Turkey - Automobile Exports* Structure (%), 2007
Figure 4-16: Turkey - Forecast for Automobile Exports (in Billion US$), 2008*-2012
Figure 4-17: Turkey - Passenger Cars Production (in ‘000 Units), 2003-2007
Figure 4-18: Turkey - Share of Players in Passenger Cars Production* (%), 2007
Figure 4-19: Turkey - Domestic Passenger Car Wholesales (in ‘000 Units), 2003-2007
Figure 4-20: Turkey - Passenger Car Exports (in ‘000 Units), 2003-2007
Figure 4-21: Turkey - Passenger Car Imports (in ‘000 Units), 2003-2007
Figure 4-22: Turkey - Forecast for Passenger Car Registrations (in ‘000 Units), 2008*-2012
Figure 4-23: Turkey - Forecast for Passenger Car Stock (per ‘000 Population), 2008*-2012
Figure 4-24: Turkey - Pick-up Trucks Production (in ‘000 Units), 2003-2007
Figure 4-25: Turkey - Share of Top 5 Players in Pick-up Trucks Production* (%), 2007
Figure 4-26: Turkey - Domestic Pick-up Truck Wholesales (in ‘000 Units), 2003-2007
Figure 4-27: Turkey - Pick-up Truck Exports (in ‘000 Units), 2003-2007
Figure 4-28: Turkey - Buses Production by Body Type (in Units), 2003-2007
Figure 4-29: Turkey - Share of Top 5 Players in Buses Production* (%), 2007
Figure 4-30: Turkey - Domestic Bus Wholesales by Body Type (in Units), 2003-2007
Figure 4-31: Turkey - Bus Exports by Body Type (in Units), 2003-2007
Figure 4-32: Turkey - Trucks Production (in Units), 2003-2007
Figure 4-33: Turkey - Domestic Truck Wholesales (in Units), 2003-2007
Figure 4-34: Turkey - Truck Exports (in Units), 2003-2007
Figure 4-35: Turkey - Farm Tractors Production (in Units), 2006 & 2007
Figure 4-36: Turkey - Farm Tractor Exports (in Units), 2006 & 2007
Figure 4-37: Turkey - Forecast for Commercial Vehicle Registrations (in ‘000 Units), 2008*-2012
Figure 5-1: Turkey - Automotive Components Production (in Million US$), 2003-2007E
Figure 5-2: Turkey - Automotive Components Demand (in Million US$), 2003-2007E
Figure 5-3: Turkey - Automotive Component Imports (in Million US$), 2003-2007E
Figure 5-4: Turkey - Automotive Component Exports (in Million US$), 2003-2007
Figure 5-5: Turkey - Automotive Component Exports by Segment (%), 2007
Figure 5-6: Turkey - Spare Parts & Accessories Exports (in Million US$), 2003-2007
Figure 5-7: Turkey - Tyres & Tubes Exports (in Million US$), 2003-2007
Figure 5-8: Turkey - Batteries Exports (in Million US$), 2003-2007
Figure 5-9: Turkey - Safety Glass Exports (in Million US$), 2003-2007
Figure 6-1: Turkey - Forecast for Premium from Passenger Cars Insurance (in Million US$), 2008*-2012
Figure 6-2: Turkey - LPG Powered Cars (in ‘000 Units), 2004, 2007 & 2008E
Figure 6-3: Global - Carbon Steel Price (in US$/Metric Ton), May 2007 & May 2008
Figure 6-4: Global - Crude Oil Price (in US$/Barrel), 2007-2009F

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The US is one of the largest and fastest growing wine markets of the world. It has expanded rapidly over the past decade. Further, on the back of rising interest of young population, increasing share of core drinkers, and surging wine consumption among women, the market will continue to grow at a fast pace in coming years too, says “US Wine Market Forecast to 2012.

This research analyzes the market development and offers unique insight into the US wine market. The forecasts and estimations given in this report are not based on a complex economic model but are intended as a rough guide to the direction in which the market is likely to move.

Key Research Findings of the Report

• The US wine market, in terms of consumption, is forecasted to grow at a CAGR of about 7.7%, and 4% in value and volume terms during 2008-2012.

• Table/Still wine is the largest consumed wine in the US.

• Increasing wine drinking frequency among women and young population will drive the US market in future.

• The US is expected to become market leader in wine consumption by 2012 end, surpassing Italy and France, the current market leaders.

• As on 2007 end, image seekers and savvy shoppers accounted for over one-third of premium wine consumption in the US.

• As on 2007 end, California is America’s top wine producer, making 90% of all the US wine.

Key Issues & Facts Analyzed in the Report

• Which are the fastest growing products in the US wine market?

• What are the key factors fueling growth into the market?

• What is the consumer behavior?

• What are the various opportunity areas?

• What are the key challenges for the market?

• How the market is likely to move in future?

Key Players Discussed in the Report

This section provides business profile of key players in the US wine market. The key players discussed in the report are Constellation Brands, E&J Gallo Winery and W.J. Deutsch & Sons, Ltd.

Research Methodology Used

Information Sources
Information has been sourced from books, newspapers, trade journals, white papers, industry portals, government agencies, trade associations, monitoring industry news and developments, and through access to more than 3000 paid databases.

Analysis Methods
The analysis methods include ratio analysis, historical trend analysis, linear regression analysis using software tools, judgmental forecasting, and cause and effect analysis.

Table of Contents :-

1. Analyst View
2. Global Wine Market - An Overview
3. US in Context of Global Wine Market
3.1 Production
3.2 Consumption
3.3 Import
3.4 Export
4. What Makes US Wine Market Attractive?
4.1 Medical Benefits
4.2 Drinking Frequency
4.3 Women Wine Consumers
4.4 Younger Generation
4.5 Government Support
5. US Wine Market - Performance
5.1 Production
5.2 Consumption
5.3 Products
5.3.1 Table
5.3.2 Dessert
5.3.3 Champagne/Sparkling
5.4 Color Mix
5.4.1 Red
5.4.2 White
5.4.3 Blush
5.5 Provinces
5.5.1 California
5.5.2 Washington
5.5.3 Oregon
5.5.4 New York
5.6 Trade
5.6.1 Import
5.6.2 Export
5.7 Distribution Networks
6. Consumer Behavior
6.1 Price Sensitivity
6.2 Key Premium Wine Consumers
6.3 Consumer Segment by Generation
6.4 Consumer Segment by Gender
7. Growth Prospects
7.1 Retail Food Stores
7.2 Drug Stores
7.3 Viticulture
7.4 Hotel & Restaurants
7.5 Beverage Containers
7.6 Celebrity-branded Wines
7.7 Online Marketing
8. Roadblocks & Recommendations
8.1 Price War
8.2 Ineffective Advertising
8.3 Substitute Products
8.4 Proliferation of Brands
9. Key Players
9.1 Constellation Brands, Inc.
9.2 E&J Gallo Winery
9.3 W.J. Deutsch & Sons, Ltd.

List of Tables :-

Table 5-1: US - Wine Production in Top 10 States (in Gallon), 2006-07*
Table 5-2: US - Number of Wineries by State (1975, 1995 & 2005-2007)
Table 5-3: California - Wine Industry Statistics, 2007
Table 5-4: Oregon - Still & Sparkling Wine Sales by Variety (in Cases), 2006 & 2007" "Figure 2-1: Global - Wine Consumption (in Billion US$), 2002-2007E

List of Figures :-

Figure 2-2: Global - Wine Consumption (in Billion Liter), 2002-2007E
Figure 2-3: Global - Wine Consumption* by Region (%), 2006
Figure 3-1: Global - Wine Production* by Region (%), 2007
Figure 3-2: Global - Wine Production* by Country (%), 2007
Figure 3-3: US - Share in Global Wine Consumption* (%), 2006
Figure 3-4: Global - Wine Imports* by Country (%), 2007
Figure 3-5: Global - Wine Exports* by Country (%), 2007
Figure 4-1: Relative Risk of Death with Frequency of Wine Consumption
Figure 4-2: Reduction in Salmonella based Food Poisoning on Wine Consumption (Units/ml)
Figure 4-3: US - Per Capita Wine Consumption (in Gallon), 2002-2006
Figure 4-4: US - Wine Consumption* Frequency (%), 2000 & 2007
Figure 4-5: US - Core & Marginal Wine Consumption by Gender (%), 2007
Figure 4-6: US - Wine Consumption by Generation (%), 2007
Figure 5-1: US - Wine Production (in Million Gallon), 2002-2006E
Figure 5-2: US - Wine Sales (in Million Gallon), 2002-2007
Figure 5-3: US - Wine Sales (in Billion US$), 2002-2007
Figure 5-4: US - Forecast for Wine Sales (in Million Gallon), 2008-2012
Figure 5-5: US - Forecast for Wine Sales (in Billion US$), 2008-2012
Figure 5-6: US - Wine Sales* by Product (%), 2007
Figure 5-7: US - Table Wine Sales (in Million Gallon), 2002-2007
Figure 5-8: US - Forecast for Table Wine Sales (in Million Gallon), 2008-2010
Figure 5-9: US - Table Wine Import by Top 5 Markets (in ‘000 Cases), 2006
Figure 5-10: US - Dessert Wine Sales (in Million Gallon), 2002-2007
Figure 5-11: US - Champagne/Sparkling Wine Sales (in Million Gallon), 2002-2007
Figure 5-12: US - Core Wine Consumption by Color Mix (%), 2007
Figure 5-13: US - Marginal Wine Consumption by Color Mix (%), 2007
Figure 5-14: US - Red Wine Sales* (in Million Gallon), 1995, 2006 & 2007
Figure 5-15: US - White Wine Sales* (in Million Gallon), 1995, 2006 & 2007
Figure 5-16: US - Blush Wine Sales* (in Million Gallon), 1995, 2006 & 2007
Figure 5-17: California - Wine Production (in Million Gallon), 2002-2006E
Figure 5-18: Washington - Winery Revenue (in Million US$), 1999 & 2006
Figure 5-19: Washington - Wine Production (in Million Gallon), 2004-2006
Figure 5-20: Oregon - Wine Grape Production (in Tons), 1976-2006
Figure 5-21: New York - Number of Wineries (1975, 1995 & 2005-2007)
Figure 5-22: US - Share of Imported Wine in Domestic Consumption (%), 2007
Figure 5-23: US - Imported & Domestic Wine Consumption* by Generation (%), 2007
Figure 5-24: US - Imported & Domestic Wine Consumption* by Segment (%), 2007
Figure 5-25: US - Wine Imports* by Country (%), 2007
Figure 5-26: US - Wine Exports (in Million US$), 2005-2007
Figure 5-27: US - Share of Export in Wine Production (%), 2000-2006
Figure 5-28: US - Wine Exports* by Country (%), 2007
Figure 5-29: US - Wine Exports by Product (%), 2007
Figure 5-30: US - Wine Distribution Networks (%), 2006
Figure 6-1: US - Wine Purchasing Frequency of Core Drinkers by Price Point, 2007
Figure 6-2: US - Wine Purchasing Frequency of Marginal Drinkers by Price Point, 2007
Figure 6-3: US - Wine Industry Revenue by Price Category (%) 1995 & 2006
Figure 6-4: US - Key Premium Wine Consumers by Segment (%)
Figure 6-5: US - Core Wine Consumers by Generation (%), 2007
Figure 6-6: US - Marginal Wine Consumers by Generation (%), 2007
Figure 6-7: US - Male & Female Wine Drinkers by Generation (%), 2007
Figure 7-1: US - Online Wine Sales from Winery Sites (%), 2003, 2005 & 2007
Figure 9-1: Constellation Brands, Inc. - Net Sales by Product (%), 2007

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"These shenanigans have become so common that they're almost invisible. The budgeting process is so deeply embedded in corporate life (...) creating incentives to game the system."

Read Michael C. Jesen's paper, "Corporate Budgeting Is Broken - Let's Fix It." on Harvard Business Review. Requires registration.

Related posts:

• Do you really need business modeling?
• The problem with budgeting (1)
• The problem with budgeting (2)
• The problem with budgeting (3)

Jensen's paper discusses budgeting pitfalls driven by questionable revenue and expense recognition tactics.

This is mostly due to pay for performance incentive systems driving managers to either delay or accelerate "the numbers" when aiming to hit or miss specific targets.

Jensen's solution approach is based on setting up a linear compensation plan that rewards performance, one that is  independent of budget targets.

Peter Horvath, whose paper I quoted in one of my previous posts, recommends a 15 month rolling forecast updated on a quarterly basis. This enables entrepreneurs to better operate in highly dynamic markets where moving targets happen to be the reality of the business.

Rolling forecasts and budgets are meant to free us from the stiff one off annual budgeting process. His recipe relies on reducing detail through the use of aggregate budgets.

I realize the above might read a bit cryptic to some. So another post with additional insights on this subject will follow. In the meantime, I will continue to welcome your comments and emails.

Picture credits: Hemera Technologies Inc., a wholly owned subsidiary of Jupiter Images Corporation.

J. de Francisco
Chicago, IL     22 August 08

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I put together a little video to tell you a bit more about how the Tarot can help you. Have a look and let me know what you think.

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[wpvideo RSNmlEoc]

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