26 August 2011

Ford Mines Drivers' Minds (Behaviors) To Save Gas

Can your car anticipate your driving patterns and optimize its performance to use fuel more efficiently, or extend your range if you are driving an electric vehicle (EV)? Can it see into the future? Ford is trying to develop the software and systems to enable it to do so.
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Google has been developing technology for cars to drive themselves, but the Ford project has more limited aims. If your car could gather information as you drive, and gradually build a model of your driving habits, plus download information about your driving environment, it could fine-tune its operation to save energy.

Chevy Volt
Ryan McGee, technical expert on vehicle controls architecture and algorithm design at Ford, says, “We have this massive amount of data. The question is what to do with it.”

A recent piece from Greentech Media outlines the concept:

"Code-named Green Zone, the software tries to anticipate where you plan to drive. Say it’s 8 a.m. on Tuesday. Your car knows that this is the second day in a five-day sequence in which you drive 23.5 miles to the same destination. The software crunches data about your driving habits, the topography of the drive, any details about traffic and time-to-destination, and information about how the car performs. It then tries to maximize the power the car draws from the battery pack and minimize the work performed by the gas engine."

This scenario is for an EV with a backup gas engine, like the Chevy Volt. But the same concept could be applied to hybrid vehicles like the Toyota Prius, plug-in hybrids, full battery-electric vehicles like the Nissan Leaf, or even just internal combustion gasoline or diesel vehicles.

The article says the car's systems would connect to cloud-based data resources to manage all the necessary data. In addition to data from the car and driver themselves, such a system would obviously also incorporate data such as the local current and forecasted weather, the local topography and traffic along the anticipated route, the availability of charging points at the likely destination, and so on. Each of these is a complex data model of its own.

Your car would know (probabilistically from historical data, via models, or via real-time data collection along the route) what the traffic was like ahead. In hybrid vehicles the different systems (electric motors, gasoline engine) operate optimally under different conditions. The car could plan its use of these resources to most efficiently deal with different speeds, idling times in stop-and-go traffic or at lights, anticipated episodes of acceleration or braking, and so on. It wouldn't have to wait for you to press the gas or the brake to know what was going on.

Greentech says "The probabilistic principles underlying the experiment are similar to predictive algorithms exploited by search engines. In fact, Ford uses Google’s predictive APIs."

We are all familiar with the computers that have become important parts of automobiles to operate their many high-tech systems. But now we should get ready for cars that have whole IT systems, and communicate moment-by-moment with vast data structures in the cloud.


Reposted from Doc's SCN blog.

The photo is by Mario Roberto Duran Ortiz from Wikimedia Commons, used under his Creative Commons Attribution-Share Alike 3.0 Unported license.

25 August 2011

Sustainability and the CFO

Sustainability, environmental issues and "green" have long since moved from "nice to have" parts of Corporate Social Responsibility, often part of the Corporate Communications (PR) portfolio, toward the center of management of the firm. A sign of this is the increasing involvement of the Chief Financial Officer (CFO) in sustainability issues. Most sustainability and environmental data is like financial data. It is financial data in many cases. (See this previous post for a discussion of the types of green data firms are faced with managing these days.).
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A new report (pdf) from consultants Ernst & Young discusses this trend. It says, among other things:
  • The old "social responsibility" and "corporate citizenship" silos are crumbling.
  • Institutional investors are deciding that "climate change and sustainability issues often bear directly on companies’ risk profiles, their reputations and their financial performance."
  • "These trends are changing the CFO's role in three critical areas: investor relations; external reporting and assurance; and operational controllership and financial risk management." The report discusses each of these three areas.
What does this mean for IT?
Finance, bookkeeping, control, and financial reporting, all managed by the CFO, are leading consumers of IT. Thus the office of the CFO is very experienced and sophisticated about the management of such data, and the products and services that are available. By contrast the Chief Sustainability Officer (CSO) or equivalent manager in charge of sustainability was often connected to PR or communications, corporate health and safety, legal and regulatory, or facilities. These functions don't have the clout and experience that the CFO has in using IT to efficiently manage data, or using data for management (BI).

So my theory is that getting the CFO involved in managing the firm's sustainability will lead to the use of much more sophisticated data management tools and services. Also, mining corporate sustainability data to provide guidance to management will be obvious to the CFO. And the CFO has the clout to get the data management products he or she needs.

External reporting in particular has traditionally been the responsibility of the CFO. The formal quarterly and annual reports, and the auditable data that underlies them, have been his or her job. As companies try to assemble data and submit reports, for instance under the Global Reporting Initiative, they are reinventing approaches that have been mastered by the finance department.

So if you have been involved in designing or implementing financial software, there is a whole new world awaiting your attention.


Reposted from Doc's SCN blog.

Earlier post about Timberland's decision to have the sustainability function report to the CFO.

09 August 2011

The Green Data Firehose: Where Is All This Green Data Coming From?

Companies have many kinds of data that they have to manage, and from which they try to learn how to run their businesses better. "Green" or "sustainability" data is a relatively new category, at least compared to financial data which companies have been dealing with for centuries.

Here are some of the current and future sources of the data filling the Green Data firehose. Companies are at early stages of figuring out how to manage and benefit from many of these data streams. Essentially every company can save 10% or more of costs in many of these areas by more sophisticated collection and use of data.
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Energy Use Data--The main driver for most companies' efforts to become more "green" has been the potential to significantly reduce costs. The place they usually start is on reducing energy costs. This means tracking energy use in order to judge the effectiveness of conservation steps. The degree of sophistication can range from just looking at monthly utility bills to detailed analysis of every energy use, process, light bulb, and server on a minute-by-minute basis.

Emissions Data--Many businesses, non-profits and government entities are trying to compile data on how much CO2 and other greenhouse gases they emit. This may be for regulatory compliance (government requires them to submit the data) or for their own "footprinting" efforts associated with sustainability goals. Of course air quality rules, cap-and-trade schemes, and other demands already require many facilities to measure, log, and report emissions of many pollutants on a minute-by-minute basis from smokestack sensors.

Building Performance Data--Computerized building management systems track building energy consumption and performance factors, to enable fine tuning of building systems. They typically track environmental parameters such as light, temperature and humidity at many points, and measure and adjust the operation of HVAC systems, lighting systems, and the like.

Vehicle Data--Obviously firms with large delivery or transportation fleets, such as FedEx, UPS, The USPS, or Coca-Cola, already track many parameters of their vehicles (including aircraft). These parameters include engine performance and fuel use, driver performance, speed, location and the like. The purpose of collecting this data is to minimize cost by efficient capacity utilization, route planning, and operation, which saves fuel, and thus as a potential secondary benefit reduces GHG emissions. I believe increasingly all companies with corporate vehicle fleets will collect similar data, which will create large data-management requirements. OnStar and SYNC generate lots of data on private vehicles, much of which could be used to help owners reduce their emissions. Battery-electric vehicles will have their own data systems to monitor charge, locate charging points, interact with electric utilities, etc.

Smart Grid--The conversion of electricity meters from traditional "dumb" meters to "smart" meters that communicate wirelessly with the utility every few minutes is generating vast data streams. Several firms are selling utilities software systems use this data to make power generation and dispatching more efficient, manage demand response programs, and identify faults.

Water Use and Discharge Data--The Clean Water Act and similar legislation require most firms to measure and track their water discharges and other releases to assure toxic substances are within acceptable limits. Increasingly, users are finding that reducing water use through increased process efficiency and reuse saves them money, both the cost of water and the cost of treating wastewater. In the future they will manage data on water the same way they manage data on fuel and power to achieve green goals and savings.

Waste Data, Including Electronic Waste Data (WEEE)--Reducing waste reduces cost, since it costs something to dispose of waste. Also, waste reduction efforts often reduce packaging, which cuts manufacturing and shipping costs as well as waste disposal costs. Waste management systems involve measuring and tracking waste, verifying proper recycling and disposal, calculating energy and emissions savings, and so on.

ISO 14000 and ISO 50001 Data--ISO 14000 is an international set of environmental management standards and ISO 50001 is a developing standard for energy management. Both use protocols similar to the ISO 9000 series for quality management, which require significant data assembly, retention, auditing, and data quality systems.

Environmental Health and Safety Data--Most large firms uses sophisticated data tools like SAP's EHS Solutions to track safety, toxic substances, and regulatory compliance, including spills and incidents, accidents and injuries, toxic exposures, required employee training, monitoring and certification, and other measures.

Data From Tracking Toxic Components--Regulations such as the Restriction of Hazardous Substances Directive (RoHS), as well as a healthy concern about liability, drive many organizations to track hazardous substances in their production chains to be sure none end up in jurisdictions where they are forbidden. Lead paint, bisphenol A, or cadmium can only be used in certain products but not in others. Effective management of such components requires reaching back to suppliers--see the next item.

Supplier Quality Requirements--To be sure suppliers are not using unacceptable production or waste disposal practices, that they are using energy efficiently, and that they are complying with packaging and waste reduction rules calls for elaborate systems of questionnaires, monitoring, inspections, reports and so on. All this needs to be imposed across complex international supply chains.

Carbon Footprint Calculations--Thousands of companies, including of course SAP, gather data and calculate their environmental footprints for their sustainability reports. (See recent post on SAP's latest quarterly environmental report.) They use sophisticated protocols such as those of the Greenhouse Gas Protocol Initiative and the Global Reporting Initiative.

Regulatory Compliance Processes and Quality Control--To avoid defects in environmental regulatory compliance many firms use sophisticated software to prepare submissions for and monitor the vast number of rules and regulations to which they are subject.

Product Life Cycle Analysis--Approaches are being developed to analyze the environmental impact, cost, and other parameters across complete product life cycles. This covers everything from the extraction of raw materials through transportation, several manufacturing steps, distribution, sale, use by the consumer, and final disposal or fate. Because suppliers, consumption patterns and designs can change, such analysis is excruciatingly complex.

Strategic Sustainability Goals Development and Tracking--In the executive suite tools are needed to understand the implications of developments in the increasingly competitive sustainability field, and plan and act as seems best for the firm. This applies to every company, not just those that claim to be "going green". Environmental risks and perception issues apply to all organizations. Some will have sophisticated planning tools to address these challenges.

Carbon Emissions Issues in Logistics--Although shipping decisions have traditionally been made on the basis of cost, speed and reliability, these days GHG emissions are often being included as a criterion.

Carbon Assets Tracking and Trading--Companies have to juggle a range of carbon credits, emission allowances, carbon offsets, renewable energy certificates and other valuable assets. These all have specific identities, and many have fluctuating values or expiration dates. They are traded either with specific suppliers or through open markets. Some have associated futures markets. The decisions about acquisition or divestiture of such assets are complex, and sophisticated modeling is needed, in addition to verifiable audit trails for each individual asset.

Risk Management for Climate Change Risks--Climate change is creating many new risks that companies need to model, forecast, and analyze. How will new regulations, heatwaves, sea level rise, or storms affect our operations? Answering these questions requires a lot of data crunching. Environmental risk analysis is a growing field.

Employee Sustainability Training and Motivation Systems--"Green Teams" are increasingly common. Building and managing these communities is one data need. Many cost-saving initiatives require ongoing and effective training, cooperation and monitoring programs. To change behaviors it is not enough to just put up a few signs. Many of these programs involve elaborate reward systems and employee participation.

Social Data on Public Perception of Corporate Sustainability--"Green" perception is one of the topics that some companies are tracking as they analyze the vast streams of comment in social media, news media, and other sources. Such tracking requires sophisticated analytics.

Many of these data streams and databases are or can be connected to other enterprise data systems, such as ERP, Personnel, Financial, and other tools. Some, such as environmental health and safety (EHS) systems or carbon accounting systems come as complete packages.

The availability of this wealth of data presents many opportunities for BI tools to help management reduce costs, reduce or at least anticipate risks, and connect energy and environmental data resources to corporate planning and goals.

I will try to discuss some of these areas in more detail in weeks to come.



This is reposted from David Wheat's post on SCN.