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Data Management Concepts for Sustainability, Pt. 4

The SSC Team August 20, 2015 Tags: , , , , , , , , , , , , Strategic Sustainability Consulting No comments
This article was written as an expansion of our white paper “Choosing Sustainability Management Software for your Business” published in July 2011.  If you’re looking for information on how to make your software selection, check out the full article.  If you just want to make sense of this particular topic, keep reading.  Whether you like this article or not, we want to hear from YOU so that we can continue to provide the best insight for YOU, our readers…  Our series on Sustainability Software continues with “Data Management Concepts for Sustainability”.  In this article (Part 4 of 4), we’ll complete the introduction and definition of key Data Management terms (read Part 3 here).  Our end goal with this series is to enable YOU, as the Business Leader, to feel more comfortable in a technical discussion related to the various areas of Data Management, especially as related to the care and feeding of Sustainability Software packages. Being able to “talk the talk” is the best defense in the technology wilderness.  Just remember, at the basis of any technical term is a common sense business notion, and staying grounded to this notion will help keep your conversations from drifting astray.

Data Integration

Data Integration is one of the most difficult of the activities covered in this series because it involves most of the different activities working in concert with each other.  For example, it is implicit in Data Movement between systems where the Data models are different.  Suppose we have data in our Accounting system that will be used in a cost calculation algorithm (method) in our Sustainability Software.  To do this, we need to copy the Accounting data, then reshape it to conform to the load utilities for our package and proceed with the load.  This setup entails numerous subtleties including the cross referencing of the source data model in the Accounting System with the format of the import utility.  This is called Field Mapping and it’s not just an easy matching question where you can get the first few right and guess the rest.  Examples will help us here.
  • Suppose we need to deal with quantity shipment data and the target model is asking for unit prices and volumes.  We might need to deduce the carbon content per gallon from the available carbon content per fifty five gallon barrel, or just divide by 55.
  • A more complex example involves translation from the English System to the Metric System (raise your hand if you can do this without a calculator).
  • Another example would be the rules concerning the potential for rounding errors for large quantities.
  • A final classic example is how to deal with Asian names (commonly listed with the surname first) being transferred into a system with a European paradigm (where the surname is listed last).
Data Integration is expensive to build and more expensive to operate.  SaaS is a way to avoid the Integration Tax to the extent possible since it has already been built into many of the downstream systems you’ll be using.

Data Mining

Data Mining is the last major topic to be introduced.  It also involves smatterings of the others, but has a unique ad-hoc character at its essence. Suppose we have a database that describes product production events in a manufacturing setting.  Suppose also that we wish to learn more about root causes of some recurring problem that has escaped previous attempts to solve it and choose to “look at all the occurrences at once”.  Someone who is expert in the data itself, as well as all the business processes it describes could attempt to construct queries that will reveal common conditions that led to the problem occurrences.  For example, he might notice they all tend to fall in the first half hour of their respective production runs.  Further drill down might reveal they all involve late shipments from the same raw material vendor, while production runs with timely shipments from the same vendor seem to go without mishap.  This would lead us to suspect potential spoilage or lack of maturity in the late arriving material.  Data Mining is a spiral learning discipline.  One spirals in to a common cause, or spirals out to learn the nature of the Cosmos.

Conclusion

We hope that as a result of this information, albeit somewhat high-level, you’ll find a greater degree of ease in approaching Data Management problems and their solutions with any Sustainability Software package that you may be considering.   As with the rest of this series, our goal is to guide you through each of these complex topics and bring them safely toward a solution that will provide you with robust and accurate data and data management practices that will last for years to come. Now that you’ve read this article, tell us what you think!  And be sure to check out the full white paper.

Data Management Concepts for Sustainability, Pt. 3

The SSC Team August 18, 2015 Tags: , , , , , , , , , , , Strategic Sustainability Consulting No comments
This article was written as an expansion of our white paper “Choosing Sustainability Management Software for your Business” published in July 2011.  If you’re looking for information on how to make your software selection, check out the full article.  If you just want to make sense of this particular topic, keep reading.  Whether you like this article or not, we want to hear from YOU so that we can continue to provide the best insight for YOU, our readers…   Our series on Sustainability Software continues with “Data Management Concepts for Sustainability”.  In this article (Part 3 of 4), we’ll continue introducing and defining key Data Management terms (read Part 2 here).  Our end goal with this series is to enable YOU, as the Business Leader, to feel more comfortable in a technical discussion related to the various areas of Data Management, especially as related to the care and feeding of Sustainability Software packages. Being able to “talk the talk” is the best defense in the technology wilderness.  Just remember, at the basis of any technical term is a common sense business notion, and staying grounded to this notion will help keep your conversations from drifting astray.

Data Movement

Data Movement is one of the silent cost areas of Data Management.  This entails the replication of data into a system and then out of it on to another system.  For example, suppose you have selected the ideal Sustainability Software offered in a SaaS-based contract by a reputable vendor.  A qualified consultant is hired to mastermind the installation and the ideal algorithms are determined, tested and approved.  All we need now is to move the company transaction data into it and let it do its work to produce the outputs we desire.  What can be so hard about that? Strong vendors of Sustainability Software will provide robust utilities to import data into their system and to export data from it.  These must receive special attention from your Consultant and from your IT staff who will need to know how they work, at least for diagnostic scenarios. We list some additional considerations below.

Data In

Suppose your consultant determines your current operational control systems can supply the data your new Sustainability Software needs and a prototype has proven this to everyone’s satisfaction.  It seems like all we need to do is to rerun the prototype code every day and everything will work. Axiom of Design:  Everything needs to be designed at least three times: Once to see if we even really want what we had in mind, once more to learn how to build the ongoing system, and once more to really build what we imagined.  Then Continuous Improvement kicks in. You are in the process of building what is called a Data Movement Application.  Any process that is repeated will fail often in new ways not anticipated.  Yes, computers can break and humans make mistakes frequently, but tornadoes and blizzards happen too. We want repeating processes to repeat as planned, and this is why the first design of any software will be replaced.  Moreover, you are probably required to prove to an auditor that all your data is being transmitted and received with very few errors that are themselves being analyzed and accounted for.  This is motivation for an Automated Balance and Control system that manages your Data Movement and assures its accuracy and timeliness.  If you intend all the work to be “outsourced”, be sure to consider these factors in your negotiations.  At minimum, be prepared to self-ensure for these events—they will happen.

Data Out

There are two main reasons to move data out of your Sustainability Software.
  1. To provide a report for approved readers
  2. To supply calculated data to another system
Reporting is technically “easy” now with all the Business Intelligence platforms that are available.  Vendors include Microsoft, Oracle, IBM and many others.  These tools are expensive but would be cost effective for SaaS providers because they can scale to serve many end users.  They are being enhanced daily to also support information display on tablets and smart phones, so you can digest this information over the Internet from nearly any place in the world. Data transfer to another system, however can be a different story.  This will be a Data Movement Application and all the considerations we’ve raised above apply here as well, except your system is now the supplier of data and another system is the recipient.  The complexities arise not only from engineering for repeatability, but from the likely need to translate source data so the target system can receive and interpret it appropriately. (TO BE CONTINUED…)  Now that you’ve read this article, tell us what you think!  And be sure to check out the full white paper.

Data Management Concepts for Sustainability, Pt. 2

The SSC Team August 13, 2015 Tags: , , , , , , , , , , , , , Strategic Sustainability Consulting No comments
This article was written as an expansion of our white paper “Choosing Sustainability Management Software for your Business” published in July 2011.  If you’re looking for information on how to make your software selection, check out the full article.  If you just want to make sense of this particular topic, keep reading.  Whether you like this article or not, we want to hear from YOU so that we can continue to provide the best insight for YOU, our readers…   Our series on Sustainability Software continues with “Data Management Concepts for Sustainability”.  In this article (Part 2 of 4), we’ll continue introducing and defining key Data Management terms (read Part 1 here).  Our end goal with this series is to enable YOU, as the Business Leader, to feel more comfortable in a technical discussion related to the various areas of Data Management, especially as related to the care and feeding of Sustainability Software packages. Being able to “talk the talk” is the best defense in the technology wilderness.  Just remember, at the basis of any technical term is a common sense business notion, and staying grounded to this notion will help keep your conversations from drifting astray.

Data Modeling

This term is most commonly associated with Data Warehouse design, but is relevant to the construction of any database.  If you elect to design and build your own Sustainability Software you will find the design of its underlying database (Data Modeling) to be one of the most labor intensive steps in the process, and because Sustainability is a rapidly evolving concept, it will seem that the database changes are boundless. Data Modelers are not only IT-savvy, but are required to be subject matter experts in the business functions of the company.  Data Modeling usually starts with vocabulary lists which are organized by a discipline called Taxonomy.  These lists are then translated into abstractions called Logical Data Models which ideally constitute the rigorous definitions of, and relationships among all the data elements required for the enterprise to function.  Then magic happens and database administrators interpret the Logical Data Models into real databases in software products such as Oracle, DB2 or SQL Server.  There are software tools like ERWin and ERStudio that assist both the modelers and DBA’s in doing this. These are lofty goals indeed and can be expensive to implement especially if you purchase expensive tools.  Additionally, in a rapidly changing environment it can be difficult for the Modelers to keep pace with the Entrepreneurs, but if your Business requires databases to function, their models (designs) must either be purchased from vendors or created by the home team. Since Analysis Paralysis can be costly, we encourage you to “buy” vs. “build” the database for your Sustainability Software, especially given the wide variety of SaaS solutions available in the market today.  For small to midsized companies, this is by far the most cost effective option.  If you elect a SaaS approach, all these issues will be completely hidden from view and their expenses will be shared among all the system’s users as part of the overall licensing cost.

Data Storage & Archiving

This is where the ongoing cost kicks in.  Hardware for data storage is at an all time low and trending downward, but the software licenses required are costly to buy and to maintain going forward.  Both must be periodically patched and upgraded which requires a sophisticated IT Infrastructure team.  These costs and hassles furnish more strong arguments for SaaS. There are also potential standards clashes with bringing in special purpose software.  For example, SQL Server is an excellent database platform for a small to midsized company, but the Sustainability package you love most might be based on DB2 and Cognos.  The benefits of the new system could easily be outrun by the cost of this big company software alone.  Remember the notion of Total Cost of Ownership, wherein it often turns out that ongoing costs exceed the installation costs dramatically. This is the area of Data Management concerned with backups, disaster recovery, test environments, complex operational change control, etc.  Bear in mind that Sustainability is an emerging venture and that commercial and governmental influences are afoot to undermine your investment, no matter which way you start out.  It’s best to adopt the conservative approach unless your industry has specific special needs that package software has not yet addressed. If you feel you must support your own Sustainability Software on your own premises with your own team, then make platform compatibility one of your highly loaded criteria.  If you have a SQL Server shop, try to adapt to a SQL Server-based package if possible. One final significant consideration: regardless of who maintains the data storage servers, you will be at least partly responsible to assure all data privacy and audit best practices are followed.  If these are not contemplated in the initial setup, it is possible you will enjoy fines and audits that will eventually motivate the re-design of the storage systems (or migration to a SaaS solution!) (TO BE CONTINUED…)  Now that you’ve read this article, tell us what you think!  And be sure to check out the full white paper.

Data Management Concepts for Sustainability, Pt. 1

The SSC Team August 11, 2015 Tags: , , , , , , , , , , Strategic Sustainability Consulting No comments
This article was written as an expansion of our white paper “Choosing Sustainability Management Software for your Business” published in July 2011.  If you’re looking for information on how to make your software selection, check out the full article.  If you just want to make sense of this particular topic, keep reading.  Whether you like this article or not, we want to hear from YOU so that we can continue to provide the best insight for YOU, our readers…  Our series on Sustainability Software continues with “Data Management Concepts for Sustainability”.  In this article (Part 1 of 4), we’ll begin introducing and defining key Data Management terms.  Our end goal with this series is to enable YOU, as the Business Leader, to feel more comfortable in a technical discussion related to the various areas of Data Management, especially as related to the care and feeding of Sustainability Software packages. Being able to “talk the talk” is the best defense in the technology wilderness.  Just remember, at the basis of any technical term is a common sense business notion, and staying grounded to this notion will help keep your conversations from drifting astray.

Data Management

The definition provided in the Data Management Association (DAMA) Data Management Body of Knowledge (DAMA-DMBOK) is: "Data Management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets."  This term is the most general description of the collection of activities involved with data and broadly includes all the areas that we’ll introduce in this article.  If you’re really interested in more detail, check out the DAMA site at http://www.dama.org.

Data Processing

This is another very broad term representing the collection of plans, processes, people and technology tasked with the collection of transactional data (e.g. item sales in a company's retail outlets) and the subsequent calculation of summary data that has meaning to your business such as periodic sales reports.  This includes the routine computational work performed by your company's people and computers that generate output like your monthly customer invoices or accounting reports, for example. Your Sustainability Software, in the ongoing state, would be supplied with data such as rigorous measurements of weights and volumes of raw materials and products (Collected Data) and the software installation will calculate the various indicators and reports for their respective uses (Calculated Data).  When discussing Data Processing, it is always a good grounding exercise to distinguish the Collected Data vs. Calculated Data being considered.  The two have different types of rules around them, which brings us to the next category of Data Management.

Data Governance

Data Governance is the management aspect of Data Management and has to do with identification and life cycle management of Business Rules connected with Data Management.  These rules might be driven by law, profit motivation, social norms or a myriad of other factors, but the establishment of definitions of terms and their existence in your company's soft assets is the foundation of Data Governance.  Examples of such rules include the following:
  • Meta-data Management is the collection of rules and definitions of the data elements used in your company.  It could be stored in a rigorous set of spreadsheets, or in an exotic, purpose-built system like Rochade from ASG Software.  Meta-data should have a dedicated team devoted to its maintenance and secure distribution to interested parties.  This team should include representation from both the technical side and the business side of your firm.
  • Business and technical ownership of data quality standards for things like customer mailing addresses and formulae used in reporting.
  • The clear specification of things like sales transactions and revenue classifications in the company's data streams.
  • The identification and lifecycle management of your company's master lists such as store locations, product names and their reporting rollups, and a consolidated customer contact list across all lines of business.  This activity is referred to as "Master Data Management" and has taken on a life of its own by numerous software companies and consultancies but it is based on the common sense notion to "Keep your lists straight."
Data Governance is like going to church, in that it is often postponed until there is enough confusion in the Business to make people desperate enough to try it.  It is definitely an endeavor that can start small, but requires the organization’s highest level of support.  Unlike some of the other topics presented here. Data Governance must be practiced within the confines of your corporate headquarters by your employees, perhaps augmented by technical consultants from time to time. (TO BE CONTINUED…) Now that you’ve read this article, tell us what you think!  And be sure to check out the full white paper.

Reducing and Managing Food Waste presented by ITP’s Green Hotelier

Tara Hughes July 31, 2015 Tags: , , , , , , , , , , , , , Industry News No comments
FOOD WASTE

Reducing and Managing Food Waste in Hotels presented by Green Hotelier

Join us for a complimentary webinar about Reducing and Managing Food Waste presented by AGPOM’s Partner International Tourism Partnership on September 24th.

Register heregreen hotelier

 

 

 

 

 

 

 

 

Every bit of food you throw away costs you and the environment.

According to UNEP, roughly one third of the food produced in the world for human consumption every year – approximately 1.3 billion tonnes – gets lost or wasted. Additionally, according to the Food Waste Alliance, 68m tonnes of food waste are produced each year in the US, with around 39.7m tonnes going to landfill or incineration. One third of this is from full and quick service (QSR) restaurants. The saddest part is 842 million people in the world do not have enough to eat.

What’s the environmental issues cased by food waste?

  • When food rots it creates methane (CH4) which has 21 times the global warming potential of carbon dioxide
  • Every time food is wasted, the water, energy, time, manpower, land, fertilizer, fuel, packaging and MONEY put into growing, preparing, storing, transporting, cooking the food is wasted.
  • If food waste was a country, it would be the world’s 3rd largest emitter of CO2

Reduced Waste = Reduced Expenses

By taking a few simple steps to waste less and recycle more, and by working out the cost of food waste to the business, hotels can reap financial as well as environmental benefits. Read more

Deciding on a Measurement Process: Calculating Your Company’s Carbon Footprint

The SSC Team July 28, 2015 Tags: , , , , , , , , , , , , , Strategic Sustainability Consulting No comments
9pcmmdc4crw-dominik-schroder.jpg Enjoy this blog post from the SSC archives: You can't manage what you don't measure -- but deciding what to measure, how to measure it, when to measure it, and where to capture and store the data can be one of the most challenging pieces of a carbon management strategy. If you're stuck at this stage (or getting ready to tackle it), here are some questions to guide your decision:

Which carbon calculation standard do you want to use?

There are several carbon calculation standards out there, but 99% of companies will end up choosing the GHG Protocol. Why?
The Greenhouse Gas Protocol (GHG Protocol) is the most widely used international accounting tool for government and business leaders to understand, quantify, and manage greenhouse gas emissions. The GHG Protocol, a decade-long partnership between the World Resources Institute and the World Business Council for Sustainable Development, is working with businesses, governments, and environmental groups around the world to build a new generation of credible and effective programs for tackling climate change. It provides the accounting framework for nearly every GHG standard and program in the world - from the International Standards Organization to The Climate Registry - as well as hundreds of GHG inventories prepared by individual companies.
Our advice: whatever standard you choose (e.g. an industry specific standard), make sure that it's built on (and in compliance with) the GHG Protocol. It makes life so much simpler.

Which emissions categories are most relevant to your organization?

In sustainability jargon, this is a question about materiality -- which activities within your operations and value chain generate material emissions? The GHG protocol outlines more than a dozen different categories (like "purchased electricity" and "employee commuting") to choose from. In most cases, you want to calculate emissions from Scope 1 (direct emissions) and Scope 2 (indirect emissions), along with a handful of Scope 3 (indirect emissions) categories that make the most sense given your size and industry.

Which carbon footprint tool makes the most sense?

There are a wide variety of options to measure your company's carbon emissions. There are excel spreadsheet models, and dozens of software programs -- both SaaS and enterprise-level options. Some companies even choose to develop their own internal calculators that integrate directly with their internal systems (like ERP, timesheets, business travel reimbursement, etc.). To dive deeper into this process, check out our free white paper on Choosing Sustainability Management Software. It's a vendor-neutral look at how companies can choose the most effective software option, including the pros and cons of some of the most popular software features.

How will we manage the process?

How many facilities are we going to include? Where is the raw data now, and how will we get it into our carbon calculator? Where are we missing data, and how can we best fill in the blanks? What is our timeline? All of these questions should be answered -- at least tentatively -- at this stage of the process. Are simple mistakes holding back your sustainability? Find out how to correct those mistakes here!

Sustainable Supply Chains in Chinese Factories

The SSC Team May 19, 2015 Tags: , , , , , , , , , Strategic Sustainability Consulting No comments
Enjoy this 2013 interview from the SSC archives: An increasing number of companies are implementing sustainable supply chain programs. These programs usually include requests to suppliers to fill out long surveys, track and report data, and develop internal management systems to improve factory-level sustainability performance. At Strategic Sustainability Consulting, we believe that effective supply chain engagement on sustainability is critical to manage risk and leverage opportunities, but we also know that suppliers are often overwhelmed at the requests they are getting from their customers. To get some insight into the challenges facing suppliers, we recently interviewed Nate Sullivan of Efficiency Exchange (EEx). We've worked with EEx, a provider of sustainability software and services to Chinese factories, for many years, and believe they have their finger on the pulse of the Chinese supply chain. SSC: You specialize in working with Chinese factories. What are you seeing in these factories with regard to supplier questionnaires? Nate Sullivan: Supplier questionnaires and worksheets are not a new thing -- factories have seen them for decades.  They've always had to fill out spreadsheets and word documents with tons of information about their facility -- from general company information, to detailed labor practices and customized quote sheets.  However, they complain that the only ones that seem to have a real impact are the quote sheets, because they're about price, and that's ultimately what customers care about in practice.  Now they are being asked to fill out sustainability questionnaires full of data, which requires a full time job to compile and document (around 40 hours a month).  Most of the time they don't even know why the customer is asking for the data, and they say that they rarely hear much back after submitting the information.  So basically it's another hoop to jump through that doesn't appear to influence purchasing decisions, and keeps factories from focusing on what they do well -- which is making stuff. SSC: What are the biggest obstacles to effectively measuring and managing sustainability impacts (like energy, waste, and water) at the supplier factory level? NS: The biggest problem, by far, is accuracy. People really need to realize that there's a tremendous amount of bad, inaccurate data out there that is useless no matter how you look at it, because it simply doesn't reflect reality. That's almost entirely due to how and why it's collected, which is usually through required self-reporting, without any incentive for suppliers that what they provide is true. Unless you're going to sit there in every facility, forever, and actively track what's happening -- which isn't practical for any retailer we've met, no matter how big -- you simply have to find a better reason for suppliers to track and truthfully report what's going on than "because I say so." And that doesn't even address the fact that suppliers have lots of customers who all have their own elaborate set of disclosure requirements, or that factories have no idea how to measure many of the things they're asked to report. SSC: Your company, Efficiency Exchange, has developed software and services that aim to overcome these challenges. Can you explain the 3-4 most important elements that supplier factories should be looking for in sustainability programs and tools? NS: The number one thing factories should be looking for is something that helps their business. Manufacturing is a tough gig; it's not like these guys have huge margins they can afford to cut into an order to look good for potential customers. So the most important characteristic of any kind of factory facing tool is that it provides direct business value to that factory. Any investment that is going to provide that kind of value to a factory needs to be easy to use, and inexpensive not only to buy, but to operate, understand, implement, etc. In our experience, what's missing from every tool we've looked at is simplicity and clarity. There are lots of systems that are really powerful and complex, but they're usually designed to be all things to all people -- utilities, retailers, manufacturers- and anybody who could conceivably buy it, really. With any kind of typical enterprise software, you end up buying this incredibly expensive, super-capable system, and then a bunch of consulting services, training, and support on top of that.  (Then you have to) whittle it down and customize it into something that's actually useful to you. Factories don't have the time or money or expertise to deal with any of that. So any tool that's going to make sense at the factory level has to strip away all of that extra nonsense, and focus on being something that's lightweight, useful, and solves a problem right out of the box. That means it can't necessarily be all things to all people -- it has to be built specifically for factories that need help with this kind of stuff, and it has to provide that help in a really direct way. If you're a factory looking at any kind of sustainability or operational improvement tool, just stop and think about how the tool is going to affect what you do all day. Are you going to get a dashboard or a weekly report? What are you actually going to do with that? Are you going to print it out once a month and put it in a file cabinet? If so, that tool doesn't make sense for you. Anything that's going to be useful needs to go from login, all the way to the part where you're saving money, or getting new business, or removing some obstacle that slows down your growth. Everyone talks about intelligence versus just data, but "actionable intelligence" versus just intelligence is just as important of a distinction, especially for factories. Whatever tool you're investing in needs to take you from software to actually doing something inside your facility that helps your business. How is sustainability saving Chinese textile mills money? Read about it here!