Check out this great infographic, thanks to CustomMade – quantifying the carbon costs of email, search and cloud storage – 2 percent of global CO2 emissions, comparable to air travel…
In my last post, I wrote about poor Brian. When we left him he was sitting in quiet desperation, driven to the edge of his sanity by the need to make sense of the data he collected in a pile of spreadsheets (in this case for the purpose of generating his company’s CDP report). In this post, I’ll talk about the kind of application that is making the Brians of the world so much more productive.
Many of the problems described are rooted in the fact that Brian is managing multiple copies of the same spreadsheet. Each time one of his 200 facility managers makes a change to ‘their’ copy, Brian needs to merge that change into a common copy of the spreadsheet.
In recent years, solutions such as Dropbox, Google Drive and SharePoint have emerged, enabling multiple users to work on a single shared copy of the data. These have certainly made life easier – at the very least, spreadsheets aren’t being emailed back and forth as much. But underlying these applications are still flat documents, whether spreadsheets or text files.
The right kind of cloud-based application greatly simplifies efforts like Brian’s CDP reporting, saving valuable time and democratizing data to save money and make for a more productive organization.
The right application improves on the basic spreadsheet in many ways, including:
- Enabling multiple users to work on a coherent data set.
- Automating unit conversion.
- Warning of outliers and missing or duplicate data.
- Providing an audit trail.
But it goes further to:
- Support dynamic and unanticipated data relationships
- Facilitate in-depth and flexible analysis of the data.
- Make it easy to generate many different charts and reports
- Enable data extension and customization through the definition of new datasets and new calculations
- Automate data collection
- Engage employees
Let’s take a deeper look at the benefits that this kind of application brings.
Sending spreadsheets back and forth and then trying to combine many into one, is time-consuming. Managers often report spending hundreds of hours just collecting and organizing data
With a cloud-based application, there’s no need to email spreadsheets around. Each ‘data provider’ logs in to the application and enters their data. Because a single database underlies the application, the data is always up to date and coherent.
Maintaining multiple spreadsheets with multiple users and multiple data sources is error prone. Data must be copied and pasted. Units must be converted. Duplicates must be identified. The right application incorporates error checking and warns of outlying, missing or duplicate data. Unit conversion is built in, enabling each user to provide data in the units most convenient. The application quantifies the quality of the data so that the user can decide whether he or she can be confident in the data.
The application provides an audit trail. Since each user logs in under his or her credentials, the application ‘knows’ just who created or updated each data record and when. An audit trail should also allow users to upload files or images with each record to substantiate the data.
Conventional spreadsheets do lend a degree of structure to the data collection task. However – too often, data providers modify parts of the spreadsheet to meet their specific data format. This makes it difficult to combine multiple spreadsheets. Managers can lock parts or all of the spreadsheet to prevent the data provider from tampering with the proscribed format. In this case, the data provider may simply omit that part of the data that doesn’t ‘fit’.
A cloud-based application can be designed to both give the data provider flexibility in data entry (such as by offering a drop-down with a broad choice of units) while simultaneously restricting them to a common format (such as requiring monthly data rather than annual). The application might allow the data provider to define new fields or column names while keeping the basic structure and data relationships intact.
Charting, Reporting, and Analyzing
Data is often collected with one purpose or report in mind. Spreadsheets will typically be structured to suit that purpose specifically.
But the collected data is a potential treasure trove of insight. The value of the data beyond its initial intended purpose might not be realized for months. In spreadsheets, the data remains static and perishable. When the data is resident in a relational database and accessible through a quality application, the data ‘comes to life’. Users with different needs and interests can chart one variable as a function of another. They can segment the data in ways never intended, revealing insights that lead to operational improvements.
For his CDP report, Brian’s only interested in GHG emissions. But the data includes electricity and fuel use for each facility. In the cloud-based application, a user might decide to chart their facility’s usage relative to other facilities. If the application stores the area of each facility, that user can chart energy per square foot for each facility. Such a chart reveals facilities that are using much more energy per square foot than the average (or much less). This leads to energy and cost savings.
Flexibility and Customization
Since spreadsheet solutions are often designed for a specific purpose in mind, they collect a specific set of data. When a new type of data is required, a new spreadsheet must be designed and re-circulated. For example – a new project is launched to collect water and waste use at the same facilities from which energy use was previously collected. This requires the creation of a new spreadsheet, doubling the number of spreadsheets in circulation.
In our cloud-based application, the administrator of the application can add categories of data and can configure the detailed parameters around each category in a manner that supports specific business processes. This exercise should not require a team of experts to customize the application at significant cost but should be doable with a few clicks, by any authorized user. The application remains alive, readily updated by those collecting and using the data.
Automated Data Collection
The cloud-based application can automate the otherwise tedious process of data collection. In many cases, data can be periodically retrieved electronically from other data stores, such as online utility accounts or other systems that are already part of an organization’s infrastructure. As such, data remains current without requiring manual effort. In cases in which the data is not available electronically, data can be imported from third-party spreadsheets in varying formats.
Finally, one of the benefits of the cloud-based application lies in the democratization of the data. In the old spreadsheet world, data providers often feel like cogs in a machine. They’re asked for data, they provide the data and that’s the last they hear of it. They wonder what part their data played in the whole – how their data compares to the data provided by peers. It’s fundamentally a many (the data providers) to one (the data collector), unidirectional exercise.
A cloud-based application engages its users. At the administrator’s discretion, they can be allowed access to their division’s data, their region’s data, or the whole dataset. They see the part their data plays in the whole, leading
to engaged users and to creative and unexpected insights. Of course, the application must support the appropriate level of segmentation among users who should not be seeing each other’s data.
To fully realize the value of engaged users, the application must be at a minimum, easy to use, and ideally fun and interesting to use.
Many companies (53% in 2014) are still using MS Excel spreadsheets for their sustainability reporting. Spreadsheets make the work of tracking and reporting such data tedious and error prone. Cloud-based applications are emerging to make this kind of work far easier. In addition to saving time and money, these applications increase the quality of the data and can lead to surprising insights. They promote greater transparency and deeper stakeholder engagement.
At Scope 5, we’re excited to be providing such an application and seeing our customers and partners through yet another CDP reporting season.
A post I recently read was titled simply “It’s CDP Submission Time Again”. Reading it reminded me of Scope 5’s very earliest days. In its development and deployment, we spoke with a handful of people, ranging from passionate tree huggers to seasoned EHS managers. All worked for large organizations and had one thing in common -responsibility for their organization’s CDP (Carbon Disclosure Project) reporting.
Our conversations gave us a view into the real challenges of data management, but they certainly weren’t unique to the CDP, Greenhouse Gas Reporting or to sustainability reporting in general (though these specific exercises exemplify the challenges). As we serve an increasing variety of customers, we see the same challenges emerging again and again, in many different contexts and subject areas.
In order to perhaps make you, dear reader, feel less alone at this CDP time of year, I thought I’d share the story of Brian at XYZ Corp. Neither Brian nor XYZ Corp are real names, but their stories are real stories, composed based on several customer interviews. We used Brian’s story to guide our work on the Scope 5 application.
Brian is a manager at XYZ Corp. His organization operates some 200 facilities around the world. He is responsible for reporting XYZ Corp’s greenhouse gas emissions each year to the CDP. For this, he needs to find XYZ Corp’s usage of electricity and various fuels at each facility and then multiply those numbers by some emissions factor, which may be location specific. Brian composes a spreadsheet, posts it on a shared server and sends an email to all of his facility managers. In that email, he sends a pointer to the spreadsheet and asks the managers to please fill out the data for their facility in the cells indicated. For extra credit, Brian asks for cost data too.
Brian eagerly anticipates the return of his spreadsheets. As they start to trickle in, he tries to combine the numbers. A few weeks and many hours of Excel column copying later, Brian is struggling. Here’s what’s been happening:
- Several respondents have sent revised spreadsheets after the first, with highlighted cells that contain corrected (or previously missing) data.
- Many of the respondents have written comments into cells – Brian needs to go through these and delete the text.
- Some are reporting back in units that Brian hadn’t anticipated.
- Some of the responses are so out of range that Brian feels there must have been a mistake.
- Brian finds duplicate entries. He’s sure one of them is correct and one erroneous. But – which one?
- Some respondents provide cost data, some don’t. Some provide it in USD, others in various foreign currencies.
In short, the blending of the spreadsheets is turning out to be a nightmare, requiring endless version management and email correspondence. Several weeks later, Brian has in his hands a pile of spreadsheets, corrected spreadsheets and comments, and the prize – the single blended spreadsheet with the final results, almost ready for that CDP report.
Brian meets with his boss, Jane, to share his results. Jane is pleased that Brian has finally completed his data collection exercise. She has some questions for him:
- That seems like a lot of money spent on fuel. How is the cost distributed across the facilities? Is it evenly distributed?
- Are there facilities at which the cost per unit fuel is very high or very low?
- Is there an audit trail? We can get this verified by an auditor but we’ll need the data behind the numbers.
- How reliable is this data? Did everyone provide the numbers requested? Or were some missing?
Back in his office, Brian sits in quiet desperation. He digs through his pile of spreadsheets, trying to combine subsets and to chart the results. He’s keeping lots of notes in lots of margins and he feels his sanity beginning to slip away.
Whether in CDP reporting or other data collection exercises, we see this general pattern and frustration frequently: far too many hours invested to produce one specific report. While the final report (probably) answers the specific question asked, there’s little ability to glean further insights – to ask the next set of questions that beg to be asked. And – too many repeat this tedious exercise year after year, with little ability to compare the results over time or to analyze the wealth of data collected.
We at Scope 5 feel your pain!
In a future post, we’ll talk about solutions that address these challenges and how Brian’s life is now so much easier.
I wrote about Full Sail Ale’s sustainability leadership not long ago. Since then, we’ve been fortunate enough to work with New Season’s Market – another sustainability leader in the food industry and also a B-Corp. Here’s another post I’d like to draw your attention to on sustainability in the brewery and winery industries. It’s written by Abby Quillen.
I encourage you to read the full post. Here are a few excerpts:
Americans consume 9.4 billion gallons of alcoholic beverages a year: 87 percent beer, 8 percent wine, and the rest spirits. The environmental impact of producing, packaging, and selling all those beverages could make an environmentalist reach for a drink. Breweries and wineries consume large quantities of water, raw materials, and other natural resources.
But there’s good news: Green beer is no longer something people drink just on Saint Patrick’s Day. With the rise of the craft beer movement and growing consumer interest in local and sustainable food, more breweries and wineries are working to reduce the beverage industry’s environmental footprint. As a result, it’s easier to stock the home bar with sustainable, organic brews.
A gallon of beer requires five to 10 gallons of water to produce. Craft brewers are leading a movement to reduce that ratio (Oregon’s Full Sail Brewery boasts a 2.5 to 1 ratio) and even the world’s largest brewers, including Anheuser Busch, MillerCoors, and Heineken, are cutting water usage.
“Our job is to “first do no harm,’ so addressing climate change as part of keeping people healthy and safe could be interpreted as being in the Hippocratic Oath” That was one of the first points Brenna Davis, Virginia Mason Health System’s Director of Sustainability made clear when we spoke recently. So, it should be no surprise that her rigorous, data-driven approach is leading an empathy-focused business, if not the entire healthcare industry, to major change.
War on Waste
This focus on sustainability actually got a head start over a decade ago when they incorporated the Toyota Production Methods in their own organizational “War on Waste.” Studying nursing procedures or waiting room waits or…you name it, brought the attention of Virginia Mason’s leadership back then to the combined business and patient case for rooting out the most efficient ways of keeping people healthy. So, when Davis, an environmental scientist by education, joined the organization in 2012, the foundation and support for her evidence-based approach to making sustainability decisions was solid.
And, by switching the medical center from spreadsheet tracking to the customizable Scope 5 data management tool for analysis and monitoring, Davis soon realized the power of that approach. Among other “wastes” that emerged after Virginia Mason started monitoring, the data showed that steam – yes, steam – was the most expensive utility for typical adjusted patient day (a typical hospital performance measure here). Along similar lines, her deeper attention to medical center’s food purchases has also uncovered waste worth battling.
With even more complex data and decisions to make than your average business, healthcare organizations have layers upon layers of information they “could” monitor and analyze. But having the right leader of that charge will mean starting with the best questions, designing the most productive parameters, finding the right tools and digging in most effectively. Virginia Mason has Davis to thank for understanding which data points are worth measuring and how to best go about making decisions from there. Virginia Mason’s already embedded war on waste has been a powerful framing metaphor for the task.
Adding Value by Removing
Some may assume that considering sustainability in business could only add internal hoops and processes, though Davis has found incredible value by leveraging data to discover what might be removed to bring more value to human life and improve the business of VMCC. In the big picture, this means striving to take away the toxins or waste that harm the environment, all to improve the health of humans on earth. At the level of running a facility, this might be as obvious as sorting through operating room waste to recycle as much as possible and lower landfill costs, or as seemingly obscure as thinking about whether it makes sense to decrease use of meat in hospital meals as a way to both improve patient health and lessen carbon emissions of food supply chain.
Discovering where the value lies in developing business sustainability starts with measuring what matters. Since medical centers are such a unique environment, Davis decided that the best way for VMMC to develop their metrics would be to carefully select elements from the GRI, SASB and Practice GreenHealth standards. As Davis put it, “Our data management tool allowed us to customize, and combine those standards into something that made sense and met the majority of the materiality essential to our business. This was new wisdom for us. There really had not been a lot out there in terms of what is material to healthcare specifically.” Accounting for the use of reprocessed single-use medical devices is just one industry example of something GRI and SASB were not including. Yet, Virginia Mason works with a vendor that reprocesses them to such a high quality that their re-use saves them up to a million dollars every year. That is certainly worth measuring.
Head Supports Heart
The concept of battling waste also reflects the “head” (aka business case) that tends to guide the sustainability decisions of most organizations. But, as Davis emphasized in our conversation, the business case that continues to be built through use of Virginia Mason’s data really supports and enhances the “heart” of the business, or empathy for human health and wellbeing, which is core to the medical center’s purpose and the Hippocratic Oath.
As a scientist with long-established focus on analytic rigor, Davis sees all sorts of data to support the smart decisions and possible changes her organization is exploring. Her own personal passion for the cause has also been part of the reason her scientific approach has been so successful. In fact, her position as Virginia Mason’s Sustainability Director has helped increase the profile of the Seattle-based health system in the national healthcare industry and policy circles.
Among the ways she is expanding the reach of Virginia Mason’s learnings, Davis, who lauds and contributes to the work of industry groups like Practice GreenHealth, is currently heading up the Washington Business for Climate Declaration group of over 100 businesses (including Microsoft and REI) and is moderating a panel, which includes Ross McFarlane of Climate Solutions and Derek Eisel of Scope 5, for the 2015 CLEANMED conference on “How Smaller Health Care Organizations Can Have a Big Impact on Climate Change”
The Data Prescription
Without being able to measure data the way they can now, Virginia Mason would not have switched out showerheads in their two campus hotels, which resulted in saving 45% of the water used. The combined impact of heart-driven, but mind and data measurement-based decisions like that, and the others already mentioned and unmentioned here, has been incredible for Virginia Mason as a business and human care giver. The benefits of having access to meaningful data has created new opportunities in every department, from building and facilities to employee engagement, patient service, and beyond. Davis is sharing those stories with industry folk who visit her organization to learn, as well as with the Seattle community of businesses, the national healthcare industry and policy makers in Washington, DC.
With Davis’ guiding focus on data, Virginia Mason is leading the way in sustainable healthcare, and elevating best practices that decision-makers from all walks of business and institutional management are already learning from. What drives her rigorous, scientific approach to the work, however, starts deep in her heart: a desire to contribute to local and global human health and wellbeing.
In both the individual and the medical institution, that unusual combination of evidence and empathy is an excellent prescription for healthcare sustainability leadership.
This post first published January 9, 2015, in CSRWire: http://www.csrwire.com/blog/posts/1494-head-and-heart-a-data-prescription-for-healthcare-sustainability-leadership
Andrea Learned writes about sustainability and social engagement. Read about Andrea at: learnedon.com
— The interesting topic isn’t big data but rather, just data —
The term ‘big data’ is thrown around an awful lot lately to describe a set of problems and solutions. Often though, the term is used in connection with an interesting set of trending issues that actually have little to do with the size of a particular data set.
- The increasing availability of data
- The emergence of software tools to process this data in contextually useful ways
- The increasing availability of tools to share this data and the resulting democratization of the data
It seems that the interesting topic isn’t big data but rather, just data. I’m making this suggestion not to be nitpicky or even controversial (though I’ve been know at times to be both). To be sure, there are specific cases in which the sheer size of the data poses interesting challenges in processing or storage but I’m concerned that the focus on the size of the data is a distraction.
Generally, the trends are around data becoming available to organizations with the promise that it can help them be more productive and more efficient in their operations. Datasets might be huge but they might not. The interesting challenge is in handling all the new data that’s becoming available, in a manner that benefits the organization.
At Scope 5 for example, the datasets that we handle aren’t huge – we might be tracking a few dozen data points, sampled monthly, across a few hundred facilities. That’s on the order of 100,000 data points per year, a far cry from the billions of data points typically associated with big data.
The challenges that we’re seeing are not in the technical processing – that’s easy. We see the challenges falling into two general categories – one is an organizational behavior challenge, the other is in imparting to our customers domain specific knowledge (in Scope 5’s case, sustainability knowledge) related to using the data. My impression is that most of the organizations that are part of the new data trends are grappling with a similar set of challenges.
Our leading customers have the notion of data tracking and analysis deeply embedded but many organizations are only just realizing the potential benefits of putting data to use. We’re finding that these organizations benefit from handholding or consulting through the process. Let’s take a look at the two areas in which we’ve started to provide additional functionality and consulting support.
Organizational Behavior Around Data
For many organizations, the flood of data is new. Nobody has been assigned the task of looking at the data and acting on it. They’re asking questions such as: Whose job is it to identify the relevant data sources. Whose job is it to analyze the data? What is the goal in analyzing the data? How are those individuals empowered to act on their findings? We often help customers decide which data sources should be automated and which are better done manually. We help them to assign responsibilities and establish a workflow.
Domain Specific Opportunities
The next set of challenges is domain specific. For example, in the case of a customer that has many facilities, they can use data to identify over-performing facilities and to apply lessons learned from these to under-performing facilities. Here again, we serve in a consulting role, recommending to our customers that they plot energy, carbon and cost across multiple facilities, normalized to square footage or units produced (or whatever normalizing factors make sense for them).
In other cases we may help customers select libraries of greenhouse gas conversion factors to use or we may help them decide which metrics should be tracked at a fine grain and which can be tracked more coarsely. We may work with customers to help them use the data to present their sustainability story more clearly.
That’s just the data analysis part. When you begin to look at the data you have and how it can be sorted, a whole world of unrealized transparency benefits emerge. As just one example, our customers have found that making data more available to rank and file employees can help develop and retain talent through a whole new level of engagement and empowerment.
It’s not the size of the data that our customers are grappling with – it’s how to use the data. Helping customers navigate through this conundrum, both with our tool and through our consulting, has shown us just how quickly rewarding our collaborations can be.