11 30 05 Holloman Evaluating the Value of Agility

Category: Entertainment

Presentation Description

No description available.


Presentation Transcript

Evaluating the Value of Agility: Operationally Responsive Space: 

Evaluating the Value of Agility: Operationally Responsive Space IAMWG Kim Holloman, EBR November 30, 2005


Agenda Traditional Space Transforming Space Operationally Responsive Space (ORS) TacSat-1 Transforming Acquisition Real Options Analysis (ROA) Applying ROA to ORS Conclusions and Discussion

Traditional Space: 

Traditional Space Currently operational and tactical level consumers do not have direct access to space assets Solution: Transformational Communications Architecture (TCA) Transformational Communications Satellite (TSAT) System Provide internet-like capability Extends high bandwidth satellite capabilities to operational and tactical level, but … $14 - $16 Billion through 2016 and …

Issues with Traditional Space: 

Issues with Traditional Space Cost Over Runs Advanced Extremely High Frequency Satellites (AEHF) costs increased by 50% Evolved Expendable Launch Vehicles (EELV) costs increased by 81% [1] High Risks $11 Billion spent on launch failures in 1990s[2] TSAT: only one of seven critical technologies mature Congress cut funding [1] [1] GAO Report: Space Acquisition, July 12, 2005 [2] GOVEXEC.com Daily Briefing July 13, 2005


Requirements are not well defined at the beginning of the program “We get started using a Volkswagen frame and then all the add-ons… just completely overwhelm what we started with” Multiple stakeholders lead to cross cutting demands Technologies are not mature Drive is to include ‘cutting edge’ technology even if not tested Cost estimates are unreliable “Less than anticipated demand …” “ Business case did not anticipate …” Causes of Traditional Space Problems


Agenda Traditional Space Transforming Space Operationally Responsive Space (ORS) TacSat-1 Transforming Acquisition Real Options Analysis (ROA) Applying ROA to ORS Conclusions and Discussion

Transforming Space: 

Transforming Space Space capabilities are a prominent element within the collection of global advantages the United States enjoys today. Space is one of the “commons,” along with the sea and cyberspace, that constitute the triad of capabilities on which America’s global power rests. But several ominous trends now compel a reassessment of the current business model for meeting the nation’s needs for military space capabilities. While the existing model has served the nation well, a new business model is at hand and can now be readily grasped to propel us into the future.[1] [1] Cebrowski, Arthur and John Raymond, “Operationally Responsive Space: A New Defense Business Model.” Parameters, Summer 2005, pg. 67.

Operationally Responsive Space: 

Operationally Responsive Space What is needed? A way to provide operational and tactical level decision makers with timely and responsive space based ISR Solution: Operationally Responsive Space (ORS) Satellites Light weight, low cost, but with limited capabilities Launch Vehicles Commercial providers, low cost Command and Control: Virtual Mission Operations Center (VMOC) IP based information sharing and collaboration ‘portal’ Distributed command and control of ORS assets

ORS Concept of Operations: 

Automatic Orbit Maneuvers for Constellation Building Joint Task Force Commander Combatant Commander OPLAN Use Authorized JTF Commander Decides: 1. Payload Capability Needed 2. Area of Interest 3. Area for Direct Downlink 4. When to Call-Up Asset Schedule of Downlink Times & Locations 3-5 Days Launch Team Precise Orbit Calcs. Range Safety Clearance SC/Payload Integration PLD SW Load/Select Batt. Charge, Fueling Final LV Integration Launch Direct Downlink Request Mission Call-Up Key Elements of the System: Micro/Small Satellites Fast & Affordable Launch SIPRNET/VMOC Two Levels of Responsive: Call-Up Time for Existing Assets Response to a New, Unforeseen, Threat or Opportunity in 3-9 months 1-14 days Pending Mission ORS Concept of Operations


ORS Quick response time Joint Task Force (JTF) organic Selectable payloads Coverage for military conflicts and opportunities at any location on Earth About the same cost as unmanned aerial vehicle (UAV) Space assets are directly tasked via the VMOC (SIPRNET), which is also used to distribute the collected data and products.

Promise of ORS: 

Traditional Satellites UAV Tactical Micro-Sat Very Low RF Power Sensors Long Dwell Usually Lowest Cost for a Unique/New Capability Continuous Global Coverage by Several Constellations Broad Dissemination Most Easily Accomplished Well Defined & Understood Missions & Targets of Interest Satisfy a Broad Range of Operational Requirements High Cost Launch on Demand Tailored Mission Payloads Tailored Coverage Covert (LPI/LPD) & Low Power Sensors Allows Rapid Implementation of New Technologies Medium Cost Tactical Control Access to Denied Areas Global Access Long-Duration Missions Broad / Multi-Theater Coverage Receiver (S/C) is Covert & Safe Tactical Micro-satellites offer a Unique Combination of Capabilities Creating a Valuable Niche and Allowing a Robust, Tiered Network for Tactical or Operational Tasking Promise of ORS

Co-Evolutionary Development of ORS: 

Cooperative Buildup and Leveraging to Arrive at an Operational System Parallel Efforts in Launch, Networking, & TacSat Experimentation are Already Occurring TacSat Experiments TacSat-1, 2, …, N System Design, Prototyping, & Rqmts Development Operational Acquisition Launch Vehicle Developments Lower Cost Space S&T and RDT&E Operational Tactical System CONCEPT Network & Comms Developments TacSat Mission Deployments Co-Evolutionary Development of ORS


TacSat-1 Provide much lighter, and much cheaper ($17 million) micro satellite capability in the 100kg range Provide the ability to rapidly launch (specific objective: launch TacSat-1 within one year) Become an organic asset within the Joint Task Force by providing direct access to payload tasking and data via the SIPRNET (via the Virtual Mission Operations Center) Develop processes and lessons learned necessary to take a meaningful step toward realizing a tactical space capability.[1] [1] Raymond, Jay, Greg Glaros, Joe Hauser and Mike Hurley, “TacSat-1 and a Path to Tactical Space.” 2nd Annual Responsive Space Conference, April 19-22, 2004, Los Angeles, CA.

Proposed Benefits of ORS: 

Proposed Benefits of ORS It is hypothesized that a tactical space capability as provided by ORS will improve the ability of tactical- and operational-level decision makers to make better informed decisions. Individual decision makers will have timely access to space based information previously unavailable or difficult to obtain, which can enable them to improve awareness of their battle space situation. As more decision makers task and use space based information via the VMOC, a community of users will emerge which will provide value-added services available to all users.

Estimated Savings from ORS: 

Estimated Savings from ORS ORS promises to provide these needed capabilities at dramatically lower costs than traditional space capabilities. NASA estimates that using the VMOC architecture will result in a 25% savings in spacecraft development.[1] The OSD office of Networks and Information Integration estimates an 8-to-1 return on investment for implementing VMOC.[2] Is this possible? What about the acquisition process? [1] “Virtual Mission Operations Center Pilot Project Charter, Revision 2,” DoD Rapid Acquisition Incentive-Net Centricity (RAI-NC), March 16, 2003, pg. 2. [2] Jung, Catherine, “Space Command Names Chief of Staff Team Excellence Award Winners,” Observer, Vol. 49, no. 26, June 30, 2005.


Agenda Traditional Space Transforming Space Operationally Responsive Space (ORS) TacSat-1 Transforming Acquisition Real Options Analysis (ROA) Applying ROA to ORS Conclusions and Discussion

Transforming Acquisition: 

Transforming Acquisition “Transformation has been viewed as new weapons systems or communications, or even culture…. but there's another one, too, and that's transforming the way we do business in this place.” [1] “The Department is currently pursuing transformational business and planning practices such as adaptive planning, a more entrepreneurial, future-oriented capabilities-based resource allocation planning process, accelerated acquisition cycles built on spiral development, output-based management, and a reformed analytic support agenda.” [2] Goal: Agile Acquisition [1]“Transforming Acquisition Oversight” Elizabeth Flaharty Lynne Giordano [2] U.S. Defense Planning Guidance, 2003, pg. 6.

Challenge Problem: 

Challenge Problem Can we use ORS as a test case to develop an agile acquisition approach? How can we measure the value of agility? What guidelines exist to help program sponsors (PS) and project managers (PM) make investment decisions? How can we reduce the risk of investing in space?

Developing an Agile Acquisition Approach for ORS: 

Developing an Agile Acquisition Approach for ORS The business case conceptual model identifies key variables and relationships that should be examined to make macro and micro level project evaluation decisions regarding the ORS initiative Options Based Methodology An Experimentation Plan reduces uncertainty by gathering data/evidence as project matures Campaign of Experiments

Business Case Conceptual Model: 

Business Case Conceptual Model Options-Based Methodology purports to allow managers to determine the value of agility in an uncertain environment. It is based on the concept, borrowed from financial literature, of real options. Real options are opportunities to invest in, or liquidate a business’s ‘real’ operating assets. They result from the management’s ability to change and optimize operations over time as new information becomes available or as uncertainties are resolved.[1] In applying the concept to ORS PS and PMs have the option to invest in real assets, such as launch vehicles, sensors, networks, etc. [1] “Shareholder Value Added: Making Real Decisions with Real Options.” L.E.K. Consulting, Vol. XVI, p. 2

Options Available to Project Managers and Sponsors: 

Options Available to Project Managers and Sponsors Abandon – stop funding the project Alter/Modify – continue funding but change the focus of funding Hold – continue to fund project as originally planned Expand – increase the level of funding and scope of project

Key Variables for Options-Based Analysis: 

Key Variables for Options-Based Analysis In order to make such decisions, sponsors and project managers must first gather certain information: The intrinsic value of the project The price/cost of the investment necessary to continue to fund the project Payments, such as dividends, which investors/sponsors are obligated to pay The interest rate, which measures the opportunity cost of investing money in the project The time until investors/sponsors need to make a decision (or chose an ‘option’) The volatility of asset’s value – a measure of how much the value of the asset changes in a period of time


In order to make decisions about investing (or not investing) in an option, uncertainties associated with each of these factors must be considered. Uncertainty is defined as “the lack of information or knowledge.”[1] When project sponsors and investors must make decisions in conditions of uncertainty, i.e., when they lack the information needed to make informed decisions, they face certain risks. Risk is defined as “the expected value of a loss function.”[1] Understanding risk requires that we have some information regarding what could go wrong, what the consequences or loss would be if this happens, and what is the likelihood or probability that this will happen. [1] Saha, Pallah, “A Real Options Perspective to Enterprise Architecture as an Investment Activity.” http://www.opengroup.org/architecture/wp/saha-2/ROA_and_Enterprise_Architecture.pdf Uncertainty, Risk, and Decision Making

Types of Uncertainty (1): 

Types of Uncertainty (1) Market uncertainty arises if we are unsure of the current and/or future demand for and supply of an ORS Mission Capability Package (MCP). There are many factors that determine demand uncertainty: price of the MCP to the user, alternative sources of the capability, operational need for the capability, etc. Supply uncertainties arise from unknowns regarding input costs and resource availability. Market uncertainty is typically higher when innovative capabilities are being introduced and when investors are attempting to ‘grow markets’ for new products. The risk resulting from this uncertainty is that project sponsors may over or under estimate the demand for or supply of the MCP, resulting in loss of potential value.

Types of Uncertainty (2): 

Technical uncertainty arises if we are unsure of the functionality of the underlying technology needed to provide the MCP. Technological uncertainty is typically high when innovative technologies are being introduced which have not been thoroughly tested. The risk resulting from this uncertainty is that the technology will under perform or fail, resulting in reductions in demand for the MCP.[1] [1] Greden, Lara, Richard de Neufville, and Leon Glicksman, “Management of Technology Investment Risk with Real Options-Based Design: A Case Study of an Innovative Building Technology.” 9th Annual Real Options Conference – Draft Submission February 21, 2005. Types of Uncertainty (2)

Types of Uncertainty (3): 

Organizational uncertainty arises if we are unsure if the MCP will have the appropriate organizational support necessary to fully take advantage of the new capabilities. Often organizational structures and processes were created in response to technologies that may be obsolete. These structures and processes can be difficult to change. The risk in this situation is that the benefits of the MCP will be less than expected due to rigid and inflexible organizational structures and processes.[2] [2] Lint, Onno. “The Primary Assessment Tool at Philips Electronics: Capturing Real Options and Organizational Risk in Technology Portfolio Management.” Eindhoven Centre for Innovative Studies, The Netherlands, Working Paper, 00.01, January 2000. Types of Uncertainty (3)

Types of Risk: 

Types of Risk Market/Public risk – which can be estimated or modeled by market data Non-market/Private risk – which must be estimated or modeled using the subjective judgments of managers Exogenous risk – which managers cannot mitigate directly Endogenous risk- which managers can mitigate with proactive policies

Options-Based Approaches to Uncertainty and Risk: 

Options-Based Approaches to Uncertainty and Risk Classic Real Options Analysis (ROA) Subjective ROA Marketed Asset Disclaimer (MAD) Revised Classic Integrated ROA[1] [1] Adapted from Borison, Adam, “Real Options Analysis: Where are the Emperor’s Clothes?” Presented at Real Options Conference, Washington, DC, July 2003.

Classic ROA: 

Classic ROA The basic idea behind the classical approach is that the value of the option can be determined if we consider the option as part of a risk less portfolio. Such a portfolio can be constructed by holding shares of a stock as well as holding an option on that stock’s derivative (the stock option). This logic is the foundation for the Black-Scholes option pricing model (BS-OPM).

Logic of BS-OPM: 

Logic of BS-OPM Since both [stock and derivative] positions are affected by the same source of uncertainty (the stock price), the capital gains associated with one investment are exactly offset by the losses associated with the other. The rate of return on the portfolio is thus risk less and should therefore equal the risk-free rate. The building block of the Black-Scholes method is a differential equation that relates the expected future value of the derivative security to the price of the underlying security and the risk less rate. This differential equation can be solved to obtain the option’s current value. In addition, it yields an optimal rule for exercising the option.[1] [1] Slade, Margaret, “Valuing Managerial Flexibility: An Application of Real-Option Theory to Mining Investments.” Journal of Environmental Economics and Management, 41, 193-233 (2001).

Black-Scholes : 

Black-Scholes In 1973, Black and Scholes showed that you can manufacture an IBM option by mixing together some shares of IBM stock and cash, much as you can create a fruit salad by mixing together apples and oranges. Of course, options synthesis is somewhat more complex than making a fruit salad, otherwise someone would have discovered it earlier. Whereas a fruit salad's proportions stay fixed over time (50 percent oranges and 50 percent apples, for example), an option's proportions must continually change. [...] The exact recipe you need to follow is generated by the Black-Scholes equation. Its solution, the Black-Scholes formula, tells you the cost of following the recipe. Before Black and Scholes, no one ever guessed that you could manufacture an option out of simpler ingredients, and so there was no way to figure out its fair price. [1] [1] Derman, My Life as a Quant, John Wiley & Sons, 2004

Black-Scholes Model (1): 

C = SN(d1) – Ke(-rt) N (d2) C = Value of the call option S = Current stock price N = Cumulative standard normal distribution d1 = ln (S/K) + (r + s2 / 2) t s√t K = Option striking price e = Exponential term r = Risk-free interest rate t = Time until option expiration d2 = d1 - s√t s = Standard deviation of stock returns ln = Natural logarithm Black.F., and Scholes M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81, pg 673-654. [Original work.] Black-Scholes Model (1)


Key assumptions of the model: Price of the underlying instrument is a geometric Brownian motion (i.e., the change in price is random) Possible to short sell the underlying stock No risk-less arbitrage opportunities Continuous trading in the stock No transaction costs or taxes All securities are perfectly divisible Risk-free interest rates and maturity dates are constant Not all of these assumptions are applicable to Real Assets Black-Scholes Model (2)

Integrated ROA Approach: 

Integrated ROA Approach Explicitly acknowledges that most investments in real assets involve both market and private risk. Steps in ROA approach: 1) Build a decision tree representing the investment alternatives 2) Identify each risk as either public or private 3) For public risks, identify the replicating portfolio and assign ‘risk-neutral’ probabilities 4) For private risks, assign subjective risks 5) Apply a spreadsheet cash-flow model at each tree endpoint, and calculate NPV using the risk-free rate 6) “Roll back” the tree to determine the optimal strategy and its associated value

Market Uncertainty: 

Market Uncertainty Market Uncertainties Demand for ORS capabilities from core users and stake-holders Demand for ORS capabilities from alternative markets Competitiveness of alternative suppliers of ORS capabilities Cost of inputs Strategies to Mitigate Risks (inputs to ROA) Identify and explore existing and potential new markets Knowledge solicitation (find out what users want and need) Operational Experiments (co-evolve ORS capabilities to meet evolving demand) Identify potential competitors Conduct market analysis of input costs and volatility


Anticipating Potential Future Markets

Potential Competitors for ORS : 

Potential Competitors for ORS Cost – Satellite development only; does not include launch or operational costs

Technology and Organization Uncertainty: 

Technology and Organization Uncertainty Technological Uncertainties Launch vehicles (cost and availability) Communications networks Sensor components VMOC Organizational Uncertainties VMOC (creating a market of users) DoD and DHS (acceptance and integration) Strategies to Mitigate Risks (inputs to ROA) Identify and explore existing and potential new launch options, communications networks and sensors Conduct market analysis of costs and availability volatility Limited Objective Experiments to test technology (co-evolve ORS capabilities) Limited Objective Experiments to explore community of users and DoD/ DHS acceptance

Applying ROA to ORS (1): 

Applying ROA to ORS (1) Step 1: Build an Investment Decision Tree In order to apply the ROA to ORS, the first step is to build a decision tree representing investment alternatives. The investment options available to ORS sponsors deal with how to allocate resources across the following key ORS project elements: Launch vehicles Satellite - Bus Satellite – Sensors (payload) Access – i.e., communications networks, VMOC, etc.


Start Phase I Phase I Do nothing Cont. Do nothing Cont. Stop Cont. Stop Cont. Stop Cont. Cont. Stop Notional Decision Tree for ROA Decision/ Option Points Strategy B Strategy A


Start Phase I Phase I Do nothing Cont. Do nothing Cont. Stop Cont. Stop Cont. Stop Cont. Cont. Stop Notional Decision Tree for ROA for ORS Is the Program Delivering as Expected? Limited Objective Experiments, DoD/ DHS Exercises Strategy B: Increase Spending on Sensor Capabilities Strategy A: Increase Spending on Launch Vehicles

Applying ROA to ORS (2): 

Step 2: Identify Risks as Public or Private and Assign Probabilities Recall from above that the fundamental variables of concern to ROA are the following: The intrinsic value of the project The price of the investment necessary to fund (or continue to fund) the project Payments, such as dividends, which investors/sponsors are obligated to pay The interest rate, which measures the opportunity cost of investing money in the project The time until investors/sponsors need to make a decision (or chose an ‘option’) The volatility of asset’s value – a measure of how much the value of the asset changes in a period of time Applying ROA to ORS (2)

Estimating the Intrinsic Value of ORS: 

Estimating the Intrinsic Value of ORS The value of any particular ORS mission capability package (MCP) cannot be estimated or modeled by assets traded in a market. Value is determined by a combination of the following: Subjective and objective value to individual users (experimentation is a key input here) Subjective and objective value to stakeholders Subjective and objective value to sponsors and project managers Estimates for these values will be based upon data collected in experiments, questionnaires and surveys. The value of an ORS MCP is also a function of alternative suppliers of space capabilities. Subjective and objective estimates of the value of potential competitors to ORS (i.e., governmental and non-governmental suppliers of low earth orbit space capabilities). Estimated values based on market analysis and subject matter expert evaluations.

Estimating Remaining Information Needs : 

The price of the investment to continue to fund or to expand funding for ORS is a function of cost of inputs to develop launch vehicles, satellites, sensors, communication networks, and the VMOC. Estimates will be based upon current and expected costs, which to some extent can be based on market indicators. It is assumed that there will be no dividend like expenditures entailed in ORS. The cost of investing money is determined by the risk free rate of return. The time needed to make a decision can be determined by the DoD/ DHS funding schedule which dictates to some extent investment timing decisions. The volatility of the value of an ORS MCP will need to be estimated by the same process identified above for measuring the value of the project. Estimating Remaining Information Needs

Experimentation as a Way to Reduce Uncertainty: 

Experimentation as a Way to Reduce Uncertainty Market Uncertainty Technological Uncertainty Organizational Uncertainty Campaign of Experiments Market Uncertainty Technological Uncertainty Organizational Uncertainty

Campaign of Experiments: 

Campaign of Experiments Objectives Increased transaction rates Shortened feedback loops Improved tactical and organizational learning Institute critical investment decision points along development path Completed and Pending DoD Exercises Terminal Fury 04 Trident Resolve II Talisman Saber Trident Resolve III Terminal Fury 05

Types of Experiments: 

Types of Experiments Large Scale DoD (or DHS) Exercises have potential to: Reduce demand uncertainty (value estimates from users) ‘Create’ market demand (by exposure to new users) Reduce organizational uncertainty (obtain ‘buy in’ of influential users) Small Scale Limited Objective Experiments have potential to: Reduce technical uncertainty (co-evolution of technology) Reduce organizational uncertainty (co-evolve TTPs, doctrine, etc.) Reduce demand uncertainty (co-evolve mission capability packages, i.e., different mixes of launch, sensor, communications and collaboration capabilities)

Linking Experimentation Schedule to ROA: 

LOE1 LOEn LOE2 Exp1 Exp2 Expn Initial Investment Expand Hold Quit Linking Experimentation Schedule to ROA Decision/ Option Points Performance Metrics

Applying ROA to ORS (3): 

Step 3: Apply a spreadsheet cash-flow model at each tree endpoint, and calculate NPV using the risk-free rate and “Roll back” the tree to determine the optimal strategy and its associated value Applying ROA to ORS (3) NOTIONAL


Applying ROA to ORS (4) NOTIONAL


Agenda Traditional Space Transforming Space Operationally Responsive Space (ORS) TacSat-1 Transforming Acquisition Real Options Analysis (ROA) Applying ROA to ORS Conclusions and Discussion


Conclusions Real Options Analysis is a feasible method to evaluate the Operationally Responsive Space Initiative. Applying ROA methods to DoD and DHS initiatives requires that we integrate market and non-market information types. Market information can be obtained and analyzed using standard ROA methods. Non-market information can be obtained from experimentation and knowledge solicitation and can be analyzed using decision tree methods. Challenges: Obtaining credible and accurate objective and subjective estimates Communicating process and results from a complicated evaluation process to larger audience Obtaining DoD and DHS acceptance of non-traditional evaluation method


BACKUP SLIDES Questions, Thoughts, Puzzles?


Back-up Slides

Black-Scholes Model: 

Black-Scholes Model Often referred to as: Black-Scholes Model of the varying price over time of financial instruments and in particular stocks The Black-Scholes formula: Mathematical formula for the theoretical value of European put and call stock options derived from the assumptions of the model *Wikipedia. (2005). Black-Scholes. From: http://en.wikipedia.org/wiki/Black-Scholes, accessed 13 October 2005.

Black – Scholes Model: 

Black – Scholes Model Parameters for Pricing Options and Warrants *QuickMBA. (2004). Black-Scholes Option Pricing Formula. From: http://quickmba.com/finance/black-scholes, Accessed 13 October 2005.


Heteroskedasticity Asset returns in the capital, commodity and energy markets often exhibit heteroskedasticity. Risk Glossary. (2005). Heteroskedasticity. From: http://www.riskglossary.com/link/heteroskedasticity.htm, accessed 24 October 2005. In econometrics terms, heteroskedasticity refers to when standard error is not spread evenly among values of x – when standard error varies per independent variable(s), and level of independent variable(s) Wabash University. (2005). Chapter 19: Heteroskedasticity. Introductory Econometrics. From: http://www.wabash.edu/econometrics/EconometricsBook/chap19.htm, accessed 24 October 2005. The Nature of Heteroskedasticity: Systematic pattern in errors in which the variances of the errors are not constant Wright University. Ec609 Syllabus. Information from: (1997) Chapter 15: Heteroskedasticity; John Wiley & Sons, Inc.. From: www.wright.edu/~rudy.fichtenbaum/syllabi/ec609/ec609ppt/chap15/chap15.PPT, accessed 27 October 2005.


Heteroskedasticity Example of homoskedasticity, visually represented


Heteroskedasticity Examples of heteroskedasticity, visually represented

Potential Competitors – Cost of Satellites: 

Potential Competitors – Cost of Satellites Typically, cost is positively correlated with: Reliability Marsh, T. (2005). Operationally Responsive Space. Presentation at SMC Industry Days: Supporting the Joint Warfighter Through Responsive Space Operations. Long Beach, CA. Type of sensor system and resolution on board TacSat-1 - which boasts of many capabilities - cost approximately $17 M Office of Force Transformation. Operationally Responsive Space Experiment: TacSat-1. Not to be distributed.

authorStream Live Help