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The Super Materials Revolution

Dan Wellers

Thousands of years ago, humans discovered they could heat rocks to get metal, and it defined an epoch. Later, we refined iron into steel, and it changed the course of civilization. More recently, we turned petroleum into plastic, with all that implies. Whenever we create new materials that push the limits of what’s possible, we send the world down an entirely new path.

Today, we’re on the verge of a revolution in materials science that will transform the world yet again. Scientists have developed tools that make it possible to design, build, and shape new “super materials” that will eclipse what we once believed were physical limits, create previously unimaginable opportunities, and expand the capabilities of what we already think of as exponential technologies in ways limited only by our imaginations.

Super strength in a pencil

The materials of the future are already being made in the present. One astonishing example is graphene, derived from the same graphite that’s in the pencil on your desk. A sheet just one atom thick, graphene is essentially two-dimensional. It weighs next to nothing, yet is up to 300 times stronger than steel. It conducts electricity more efficiently and faster than any other material. It dissipates heat faster than any other known material. It’s the only substance on earth that is completely impermeable by gas.

Excitement about graphene’s potential was high from the first, and it’s not ebbing. At least 13 conferences focusing on graphene, 2D substances, and nanotechnology are scheduled for 2016. The European Commission has created Graphene Flagship, Europe’s largest-ever research initiative, to bring graphene into the mainstream by 2026. And researchers have already developed an array of fascinating uses for graphene: new types of sensors, high-performance transistors, composites that are both super-light and super-strong, even a graphene-based gel for spinal cord injuries that can help nerve cells communicate by conducting electricity between them.

In 2015, IBM achieved a breakthrough in carbon nanotubes — graphene rolled into a tubular shape — that opens the door to faster transistors that will pack exponentially more computing power onto a single silicon chip. In fact, taken to its logical conclusion, the ability to shrink transistors to nanoscale could lead to processors that combine vast power and tiny size in a way that could be called “smart dust” (good news for those of us who don’t prioritize good housekeeping).

But that’s not all we’ll be doing with graphene. Here are just a few examples of what researchers say this single super material is likely to bring us in the not-too-distant future:

Transparent future mobile phone in hands. Concept.
  • batteries that last twice as long as they do now and could offer electric cars a 500-mile range on a single charge.
  • solar cells that are up to 1,000 times more efficient
  • clothing that conducts electricity and has wireless connectivity
  • bendable, highly conductive display screens
  • water desalinization using 15 to 50 percent less energy
  • coatings that can be applied to almost any surface that needs protection from water and air
  • meteor-resistant spacecraft and lightweight bulletproof armor, both enabled by graphene’s ability to dissipate energy from incoming projectiles

Marveling at the possibilities

Amazingly, graphene barely scratches the surface. Consider these advanced materials, all of them currently in development, and let yourself marvel at how we might put them to work:

Nanomaterials artificially engineered at molecular scale are giving rise to cotton-blend fabric that kills bacteria or conducts electricity, a coating that makes objects so frictionless they give no tactile feedback, and ceramics that bounce back from extreme pressure.

Recyclable carbon fiber composites that can be turned back into liquid form and remolded will replace the current versions that can only go into landfills when they’re broken.

Ultra-thin silicon circuits will lead to high-performance medical instruments that can be not just worn, but implanted or swallowed.

Flexible solar cells will replace large, unwieldy solar panels with thin film that can go almost anywhere and be incorporated into almost anything, from windows to tents to clothing.

Rechargeable metal-air batteries that can store electricity in grid-scale amounts will bring plentiful low-cost, reliable energy to places that currently have unreliable or no access to the traditional power grid.

Biomaterials will allow us to build robotic structures out of engineered materials that mimic organic ones. Soft materials that can be activated by an electric field will give us a whole new take on the human/machine interface. The next generation of prosthetics, for example, will be more comfortable, more functional, and harder to distinguish from living flesh.

Metamaterials, synthetic composites designed at the inter-atomic level, will have properties not found in nature. Those of you who love Star Trek and/or Harry Potter will be thrilled at this example: Scientists have already created a thin skin of metamaterial that makes whatever it covers undetectable. That’s right—an actual invisibility cloak. (Unfortunately, non-Romulans and Muggles will probably have to wait quite a while for the retail version.)

Designing the future, one molecule at a time

More mind-boggling developments in material science are on their way. The Materials Genome Initiative (MGI) is a multi-agency U.S. government project designed to help American institutions discover, develop, and deploy advanced materials at lower cost and bring them to market in less time. One central part of the initiative is a database attempting to map the hundreds of millions of different combinations of elements on the periodic table so that scientists can use artificial intelligence to predict what properties those combinations will have. As the database grows, scientists can draw on that data to determine how best to combine elements to create new super materials that have specific desired properties.

Of course, no technological advance is without its challenges, and the rise of the super materials is no exception. One technical hurdle that’s already pressing is the need to find ways to integrate graphene into a high-tech world in which industry and academia have already invested trillions of dollars in silicon. That sum is impossible to walk away from, so unless (until?) graphene supplants silicon entirely, factories, production lines, and research centers will have to be retooled so that both materials can co-exist in the same projects.

That said, advanced materials are a fundamental building block for change, so keep your eye on them as they develop. As super materials become exponentially easier to produce, we’ll start to see them in common use — imagine 3D printers that can create new objects with high-performance computing and battery power literally baked in. As they become more common, expect to see them weaving exponential technologies tightly into the fabric of daily life, both literally and figuratively, and bringing us ever-closer to a world of ambient intelligence. And as these foundation-shaking new materials become ubiquitous, it’s likely that they’ll make today’s technological marvels seem like a preschooler’s playthings.

Download the executive brief Super Materials: Building the Impossible

super-materials-thumbnail

To learn more about how exponential technology will affect business and life, see Digital Futures in the Digitalist Magazine.

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About Dan Wellers

Dan Wellers is the Global Lead of Digital Futures at SAP, which explores how organizations can anticipate the future impact of exponential technologies. Dan has extensive experience in technology marketing and business strategy, plus management, consulting, and sales.

Machine Learning: The Real Business Intelligence

Kai Goerlich

Business intelligence (BI) tools first appeared on the enterprise technology scene several decades ago, at birth clumsy and difficult to use but ultimately improving the flow of data through organizations from their operational systems to decision support. Data warehousing cut the time it took to access data, but even at their full maturity, BI systems could do little more than produce data and reports in a traditional organized way. The rules-driven software wasn’t actually providing intelligence at all.

But with the advancement of artificial intelligence and—more importantly—machine learning, true business intelligence is actually on its way to the enterprise. Such self-learning software will run on servers, be built into bots, drive decision-making systems, be embedded into cars or aircraft, and become the beating heart of mobile devices.

Increased data-processing power, the availability of big data, the Internet of Things, and improvements in algorithms are converging to power this actual business intelligence. To be clear, this will be an evolution rather than a revolution. There are a number of factors that could limit the progress of machine learning and its integration into business, from quality of data and human programming to cultural resistance. However, the question is when, not if, the BI tools of today become a quaint relic of earlier times and real business intelligence emerges.

Beyond sci-fi AI

Artificial intelligence (AI), a term dating back to the 1960s, is tossed about quite a bit these days. It’s an umbrella descriptor that refers to computers capable of doing things that a human typically would. It’s often inaccurately used interchangeably with machine learning. Machine learning, however, is a specific subset of AI that uses statistical methods to improve the performance of a system over time. Any programmer can write code to develop a program that more or less acts like a human. But it’s not machine learning unless the systems is learning to how to behave based on data. Machine learning comes in several flavors, sometimes referred to as supervised learning (the algorithm is trained using examples where the input data and the correct output are known), unsupervised learning (the algorithm must discover patterns in the data on its own), and reinforced learning (the algorithm is rewarded for penalized for the actions it takes based on trial and error). In each case, the machine is able to learn from data—structured and increasingly unstructured in the future —without explicitly being programmed to do so, absorbing new behaviors and functions over time.

Gartner recently placed machine learning at the height of “inflated expectations” in its report, noting that this emerging capability is two to five years from mainstream adoption. But those immersed in machine learning development are grounded in reality. And the reality is that they are making significant strides. Machine learning mimics human learning; it takes time.

The big advantage machines have over us is that they can handle massive amounts of data, take advantage of ever-faster processing power, and run (and thereby) improve 24 hours a day. Over just the last four years, the error rate in machine learning-driven image recognition, for example, has fallen dramatically to near zero—practically to human performance levels.

Still, every instance of machine learning is different. Just as, for us, learning to play piano is different from learning how to crawl, each instance of machine learning is different. It may take longer for a computer to learn to analyze text than it takes it to recognize the meaning of a furrowed brow.

Machine learning for the rest of us

Digital giants are leading the way in machine learning development. Google has more than 1,000 machine learning projects underway, including its Google Brain project. IBM continues to make headlines with Watson. Microsoft uses neural networks to powers its search rankings, photo search, and translation systems while Facebook translates 2 billion user posts in more than 40 languages each day in the same manner. In the last year alone, venture capital firms have poured approximately $5 billion into machine intelligence startups.

At this early stage, there are no concrete baselines for machine learning adoption rates in the rest of industry. Consumer adoption of machine-learning technologies has taken off with the success of Amazon’s Echo and Apple’s Siri. It’s an important component in fraud detection and surveillance, image and voice recognition, and product recommendations. But, as a recent report from 451 Research pointed out, but enterprise adoption is less pervasive. To broaden the enterprise use of machine learning, some of the biggest tech players in the field, such as Google, Microsoft, Intel, and Facebook make their older machine learning systems and designs available to the open source community.

Machine learning could bring significant value to the business: improving the core functionality of existing software and analytics, uncovering previously inaccessible insights hidden in large data sets unstructured data formats, and taking over tasks like image recognition, text analysis, and repetitive knowledge work. The potential use cases are seemingly endless, from supply chain and risk detection to logistics and technical support to behavioral analysis and customer support.

Limiting factors

Machine learning is not a silver bullet and there are a number of issues that companies must address. Because it is based on algorithms that learn from data rather than relying on rules-based programming, effective machine learning is dependent on relevant and reliable data—and lots of it. Business leaders must take a hard look at available data (the quality of it, the gaps in it, the silos around it) to extract the value of self-learning capabilities.

What’s more, machine learning is ultimately guided by human decision making. Humans will decide what problems the technology will be used to solve. Humans will develop the algorithms to employ. And humans don’t necessarily operate on logic.

Perhaps most importantly, the adoption of machine learning is going to be determined more by organizational and cultural forces than by technical factors. Humans are yet not machine ready. Machine learning will need to be designed with the man-machine interaction in mind. Fear, uncertainty, and doubt about how these self-learning systems will impact our roles and our livelihoods must be addressed, and significant investment must be made in change management as business processes and models are reworked to integrate self-learning systems.

The rise of the machines in business—and beyond

Business leaders have been talking about the importance of context-sensitive systems to the enterprise for several years. Machine learning could finally bring that concept to life—from smart software to smart vehicles to intelligent machines and robots to machine learning-enabled digital assistants and to smart grids that can learn to understand their environment and adapt on their own.

Smart machines will become an integral part of business—and daily life—creating insight from data in ways that humans on their own never could. That will lead to new levels of automation, cost savings, and process change. Gartner predicts that in 2018, 45 percent of the fastest-growing companies will have fewer employees than instances of smart machines and customer-facing digital assistants will recognize individuals by face and voice across channels and partners. Self-learning algorithms will introduce unprecedented levels of efficiency in business systems taking over highly repetitive work. On a personal level, smart assistant technology could turn our mobile devices—already capable of voice response, into interactive learning assistants tasked with helping us navigate our daily lives. Machine learning could uncover new efficiencies in our complex and overstressed infrastructure systems including energy, logistics, healthcare, IT, and even education.

The value that machine learning can deliver will be dependent on the degree to which these systems can deal with structured and unstructured data (which remains a challenge) as well as the availability of useful data and quality algorithms. Taking over the mundane and repetitive tasks within business systems and for consumers is all but guaranteed. Organizations are starting to collect unstructured und unprocessed data in so-called data lakes. If companies open up more of their self-learning data and designs, that shared insight will result in ever better algorithms and more accurate and effective machine learning capabilities.

If machine learning matures to the point that it can handle unstructured data, organizations openly share data, and algorithms begin to interact with each other more freely, machine learning will be embedded in all systems, devices, machines and software. That will enable highly context-sensitive insight at both the large scale and individual level. We can only guess about the level of automation and support that will result, but the impact on business—and society—will be significant.

However this evolution plays out, it will take time. But business leaders can prepare now for the rise of machine learning, taking a hard look at data structures and availability, freeing up information from siloed systems, identifying the richest areas for machine-fueled insight and improvement, and addressing the cultural and change management challenges that will be required to take advantage of this real business intelligence.

Download the executive brief Rise of the Smart Machines

To learn more about how exponential technology will affect business and life, see Digital Futures in the Digitalist Magazine.

For more on next-generation business intelligence in the enterprise, see An AI Shares My Office.

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Kai Görlich

About Kai Görlich

Kai Goerlich is the Idea Director of Thought Leadership at SAP. His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation. Share your thoughts with Kai on Twitter @KaiGoe.

Perception vs Reality: The Next Wave of Computing

Dan Wellers

01Perception:
We have to accept the limitations of silicon chips.

Reality:

Graphene molecule, credit: Getty Images

Current manufacturing methods may not be able to shrink silicon transistors much smaller than they’ve already become without compromising chip performance, but our appetite for ever-increasing computing power doesn’t seem to have an end. Emerging alternatives show promise as materials to build the next generation of computing hardware. Graphene, one molecule thick and more conductive than any other known material, can move electrons faster in less space than even the tiniest bit of silicon.

A biocomputer made of the molecular “motors” that perform tasks in living cells can also perform parallel calculations faster, cheaper, and with far more energy efficiency than conventional electrical computers. And for long-term storage, synthetic DNA packs so much data into so little space—think of how little DNA it takes to make one person—that every bit of information humans have ever generated could fit in a spoonful of lab-grown goo with room to spare.

02Perception:
Computers are binary.

Reality:

Quantum computer chip, credit: D-Wave

Conventional computers execute instructions using sequences of electrical pulses: zero (off) and one (on). New computing technologies fracture this binary approach. Qubits, the bits used in quantum computing, operate through fluctuating electrical fields, which can represent a zero, a one, both at once, or some point in between—all at the same time. Theoretically, these computers will be able to solve highly complex problems millions of times faster than the ones we have today.

Neuromorphic technology, meanwhile, is modeled on the human brain, with thousands of electronic neurons connected to many other neurons, all exchanging electrical signals at the same time. While still binary, they can perform calculations faster because they work in parallel, not sequentially.

03Perception:
New kinds of computers are a long way off.

Reality:

Synthetic DNA chip, credit: Wikipedia

While quantum computers, neuromorphic chips, and other advances may sound like science fiction, they are on their way to becoming commercial products. General Vision has created a neuromorphic chip that can recognize patterns in microseconds and learn in real time; it’s already being used for data and visual pattern recognition applications. Google researchers announced in 2015 that they had developed a new way to protect the quantum entanglement—or stability—of qubits, a feat necessary for quantum computing to work without errors and outperform conventional computers. IBM’s 2015 breakthrough in creating graphene nanotubes is the first step toward building processors that will squeeze enormous computing power onto chips the size of dust particles. And researchers at Sweden’s Lund University have already built an experimental biocomputer, though it’s still only capable of doing simple calculations. As for storage, Microsoft is investigating synthetic DNA for secure long-term storage and has already successfully encoded and recovered 100% of its initial test data. D!

 

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

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About Dan Wellers

Dan Wellers is the Global Lead of Digital Futures at SAP, which explores how organizations can anticipate the future impact of exponential technologies. Dan has extensive experience in technology marketing and business strategy, plus management, consulting, and sales.

Is Personalization Killing Your Relationships With Customers?

Christopher Koch

 

Customers Want Personalization…

 

Customers expect a coordinated, personalized response across all channels. For example, 91% expect to pick up where they left off when they switch channels.

Source: “Omni-Channel Service Doesn’t Measure Up; Customers Are Tired of Playing Games” (Aspect Blog, January 29, 2014)

laptop_phone

 


 

… And they Want it Now

 

Customers also want their interactions to be live – or in the moment they choose. For example, nearly 60% of consumers want real-time promotions and 48% like online reminders to order items that they might have run out of.

realtime

That means companies need to become a Live Business – a business that can coordinate multiple functions in order to respond to and even anticipate customer demand at any moment.

Source: “U.S. Consumers Want More Personalized Retail Experience and Control Over Personal Information, Accenture Survey Shows” (Accenture, March 9, 2015)

 


 

But There’s a Catch: Trust

 

73percent

Customers are demanding more intimacy, but there’s only so far companies can go before they cross over the line to creepy. For example, facial-recognition technology that identifies age and gender to target advertisements on digital screens is considered creepy by 73% of people surveyed.

Source: “In-Store Personalization: Creepy or Cool?” (RichRelevance, 2015)

 


 

How to Earn Their Trust and Keep It

 

Here are some ways to improve trust while moving forward with omnichannel personalization.

trustfall

1-01

Customers Want Value for Their Data

An Accenture study found that the majority of consumers in the United States and the United Kingdom are willing to allow trusted retailers to use some of their personal data in order to present personalized and targeted products, services, recommendations, and offers.

Source: “U.S. Consumers Want More Personalized Retail Experience and Control Over Personal Information, Accenture Survey Shows” (Accenture, March 9, 2015)

 

2-01

Don’t Take Data, Let Customers Offer It

Customers who voluntarily provide data are less likely to be annoyed by personalization that’s built around it. Mobile apps are a great way to invite customers to share more data in a relationship that they control.

 

3-01

Be Clear About How You Will Use Data

Companies should think about the customer data transaction – such as what information the customer is giving them, how it’s being used, and what the result will be – and describe it as simply as possible.

 


 

download arrowTo learn more about how to personalize without destroying trust, read the in-depth report Live Businesses Deliver a Personal Customer Experience Without Losing Trust.

 

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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Nic Smith

About Nic Smith

Nic Smith leads the global product marketing organization for business intelligence and cloud analytics at SAP. As a data-driven marketing leader, his experience in enterprise and business consumer marketing strategies supports customer innovation and consistently drives growth targets. Nic brings a unique blend of experience in product marketing, field marketing, product management, digital marketing, and customer experience with a proven record of leading great teams and initiatives for companies such as SAP, Microsoft, and Business Objects.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Jayne Landry

About Jayne Landry

Jayne Landry is the global vice president and general manager for Business Intelligence at SAP. Ms. Landry joined Crystal Decisions in 2002 and came into SAP through the Business Objects acquisition in 2007. A seasoned executive with 20+ years of experience in the technology sector, Jayne has held leadership roles in high-tech companies in the CRM, mobility, and cloud applications space. Ms. Landry holds a Bachelor of Commerce degree from the University of Auckland, and has continued executive development with Queen’s University, Ontario, and through work with the Sauder School of Business at the University of British Columbia.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Roger Noia

About Roger Noia

Roger Noia is the director of Solution Marketing, SAP Jam Collaboration, at SAP. He is responsible for product marketing and sales enablement for our dedicated sales team as well as the broader SAP sales force selling SAP Jam.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Stephen Cloughley

About Stephen Cloughley

As part of the global Life Sciences Business Unit at SAP, Stephen Cloughley drives supply chain solutions with a special focus on serialization in the wholesales, consumer, and pharmaceutical industries. Stephen is a chemical engineer from University College Dublin and has over 20 years experience in the software industry in Europe, South Africa, and the United States.   

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awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Dr. Ravi Prakash Mathur

About Dr. Ravi Prakash Mathur

Dr. Ravi Prakash Mathur is Senior Director of Supply Chain Management (SCM) and Head of Logistics and Central Planning at Dr. Reddy’s Laboratories Ltd. He heads the global logistics, central planning, and central sourcing for the pharmaceutical organization. Winner of the 2015 Top 25 Digitalist Thought Leaders of India award from SAP, Dr. Mathur is an author, coach, and supply chain professional with 23 years of experience and is based in Hyderabad. He is also actively involved in academic activities and is an internal trainer for DRL for negotiation skills and SCM. In 2014, he co-authored the book “Quality Assurance in Pharmaceuticals & Operations Management and Industrial Safety” for Dr. B. R. Ambedkar University, Hyderabad. He is also member of The Departmental Visiting Committee (DVC) for Department of Biotechnology, Motilal Nehru National Institute of Technology (MNNIT) Allahabad. Professional recognitions include a citation from World Bank and International Finance Corporation for his contribution to their publication “Doing Business in 2006” and the winner of the Logistics-Week Young Achiever in Supply Chain Award for 2012.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

About Michael Brenner

Michael Brenner is a globally-recognized keynote speaker, author of  The Content Formula and the CEO of Marketing Insider GroupHe has worked in leadership positions in sales and marketing for global brands like SAP and Nielsen, as well as for thriving startups. Today, Michael shares his passion on leadership and marketing strategies that deliver customer value and business impact. He is recognized by the Huffington Post as a Top Business Keynote Speaker and   a top  CMO influencer by Forbes.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

About Meghan M. Biro

Meghan Biro is talent management and HR tech brand strategist, analyst, digital catalyst, author and speaker. I am the founder and CEO of TalentCulture and host of the #WorkTrends live podcast and Twitter Chat. Over my career, I have worked with early-stage ventures and global brands like Microsoft, IBM and Google, helping them recruit and empower stellar talent. I have been a guest on numerous radio shows and online forums, and has been a featured speaker at global conferences. I am the co-author of The Character-Based Leader: Instigating a Revolution of Leadership One Person at a Time, and a regular contributor at Forbes, Huffington Post, Entrepreneur and several other media outlets. I also serve on advisory boards for leading HR and technology brands.

Tags:

awareness

Donuts, Content Management and Information Governance

Ina Felsheim

I was on vacation for two weeks, which was awesome, and my girls mainly wanted to do two things:

I had my own list of projects, too. The big one was installing glass tile on the kitchen backsplash. (Grout everywhere. That’s all I’m saying.)

After two weeks of glorious holiday, I sat down to take stock. The old technical writer in me came creeping out, and I began to count how many sets of instructions we followed over the course of the two weeks—more than 15, definitely. And the amazing thing? They were all right. Every. Last. One. From proper application of fabric paint to proper frying temperature for homemade donuts, to putting together a shoe rack that came in 20 pieces.

I’m pretty sure this wouldn’t have happened five years ago. The difference comes from an increased awareness in the importance of great user assistance. Without successful “use,” who’s going to evangelize your product?

Information Governance: Part of a Larger Food Pyramid

In EIM, we have a well-seasoned group of information developers. They apply information governance principles every day:

  • Create a single source of master information (in this case, product step-by-step instructions)
  • Manage versioning of master information (as product updates happen)
  • Survey end-users of the information to gauge quality, freshness, and applicability of master information
  • Establish master information Responsible, Accountable, Consulted, or Informed (RACI) models for owners, reviewers, and informed stakeholders.

Sometimes, we group this knowledge management work into other categories, like content management. However, information governance needs to also be inclusive of these activities; otherwise, how can we be successful? No one can live on donuts alone!

Does your information governance program include content management? Do you have comments about the quality of EIM user assistance (online help, PDFs, printed documentation, etc.)?

Comments

Tags:

awareness