Sections

This New Digital Divide Is Leaving Most Companies Behind

Michael Brenner

What digital divide? Among one of the world’s most innovative nations, the United States is globally known for its cutting-edge digital capabilities.

Yet according to a recent McKinsey report, the U.S. economy is realizing only 18% of its digital potential. The productivity gains digital technologies should be enabling are not being seen in the economy due to a new digital divide in the U.S.

The birth of “have-mores”

Almost all individuals, companies, and sectors in the U.S. today have access to digital technologies. There are hardly any “have-nots” when it comes to all things digital. But increasingly there is a wide and persistent gap between the “haves” and a group of “have-mores” – companies and sectors that are leveraging and using their digital capabilities more than their peers to transform and innovate their operations.

The 18% figure is determined by how the U.S. economy as a whole performs against the have-mores, through an analysis of where and how companies are building their digital capabilities, increasing usage and developing a more digital workforce. At the sector level, McKinsey Global Institute found that the have-mores have increased their level of investment in technology-enabled initiatives four-fold since 1997, with greatest gains realized in the past decade. Other sectors are barely keeping up with the have-mores.

The technology sector as well as media, professional and financial services sectors rank themselves with the have-mores, and are leading on the digital front compared to other sectors of the U.S. economy. However, this does not mean every technology or media company is leading. There are many companies within those sectors that are falling behind as well.

The laggard sectors are generally government, health care, construction, local services and hospitality, but again, there are exceptions within each sector that are innovating and disrupting on the digital front.

Economic implications of the new digital divide

This digital gap has broader economic implications. The digitally advanced have boosted their productivity and profit margins by two to three times the average rate of their peers in the last twenty years. The laggard sectors also reported lower productivity and performance.

Since many of the laggard sectors contribute and represent a significant portion of U.S. GDP and employment, this inevitably slows down the broader economy. It is estimated that, if the U.S. operates at its full digital potential, this could add at least $2 trillion to the economy.

Digital usage drives business growth

It should be noted that this digital divide is not a result of reluctance to invest in digital technologies, as most companies now spend heavily on IT regardless of their sectors. This gap is created by the degree of digital usage. For leading sectors, the level of digital engagement with customers and suppliers is five times larger than others – digital engagement includes everything from digital payments to advertising and interactions on social media.

The gap is even more substantial when it comes to developing digital workforces. For leading sectors, digital and mobile increase worker efficiency and automate routine tasks, while creating new digital jobs.

On the company level, the have-mores are disrupting their sectors (and others) and are leading on the product/service, business model innovation and revenue growth front. Digitally enabled innovations tend to have network effects associated with them, leading to “winner-take-most” outcomes. Top-performing companies experience much higher profit margins and are leaving everyone else behind.

McKinsey research of 150 large companies found that many firms are struggling to keep up with digitization to deliver products and services more quickly and cost-efficiently. However, not all of the digital leaders were born digital. Companies like Nike and GE have successfully transformed their strategies and operations to become top digital leaders.

Since digitization is closely connected to innovation, productivity, and growth, closing this digital disparity between the haves and have-mores should be a top agenda item for both public and private-sector leaders. The digital growth and productivity advances of the haves could be an important stimulant for the U.S. and global economy.

What do you think? Do you agree with McKinsey that this digital catch-up growth will lead into a broader economic transformation? Please share your thoughts below!

Are you interested in engaging and converting new customer for your business? Contact me here and let’s talk about how we can help. Follow me on LinkedInTwitterFacebook, and subscribe here for regular updates.

The post This New Digital Divide Is Leaving Most Companies Behind appeared first on Marketing Insider Group.

Comments

About Michael Brenner

Michael Brenner is the CEO of Marketing Insider Group, former Head of Strategy at NewsCred, and the former VP of Global Content Marketing here at SAP. Michael is also the co-author of the book The Content Formula, a contributor to leading publications like The Economist, Inc Magazine, The Guardian, and Forbes and a frequent speaker at industry events covering topics such as marketing strategy, social business, content marketing, digital marketing, social media and personal branding.  Follow Michael on Twitter (@BrennerMichael)LinkedInFacebook and Google+ and Subscribe to the Marketing Insider.

Amazing Digital Marketing Trends And Tips To Expand Your Business In 2015

Sunny Popali

Amazing Digital Marketing Trends & Tips To Expand Your Business In 2015The fast-paced world of digital marketing is changing too quickly for most companies to adapt. But staying up to date with the latest industry trends is imperative for anyone involved with expanding a business.

Here are five trends that have shaped the industry this year and that will become more important as we move forward:

  1. Email marketing will need to become smarter

Whether you like it or not, email is the most ubiquitous tool online. Everyone has it, and utilizing it properly can push your marketing ahead of your rivals. Because business use of email is still very widespread, you need to get smarter about email marketing in order to fully realize your business’s marketing strategy. Luckily, there are a number of tools that can help you market more effectively, such as Mailchimp.

  1. Content marketing will become integrated and more valuable

Content is king, and it seems to be getting more important every day. Google and other search engines are focusing more on the content you create as the potential of the online world as marketing tool becomes apparent. Now there seems to be a push for current, relevant content that you can use for your services and promote your business.

Staying fresh with the content you provide is almost as important as ensuring high-quality content. Customers will pay more attention if your content is relevant and timely.

  1. Mobile assets and paid social media are more important than ever

It’s no secret that mobile is key to your marketing efforts. More mobile devices are sold and more people are reading content on mobile screens than ever before, so it is crucial to your overall strategy to have mobile marketing expertise on your team. London-based Abacus Marketing agrees that mobile marketing could overtake desktop website marketing in just a few years.

  1. Big Data for personalization plays a key role

Marketers are increasingly using Big Data to get their brand message out to the public in a more personalized format. One obvious example is Google Trend analysis, a highly useful tool that marketing experts use to obtain the latest on what is trending around the world. You can — and should — use it in your business marketing efforts. Big Data will also let you offer specific content to buyers who are more likely to look for certain items, for example, and offer personalized deals to specific groups of within your customer base. Other tools, which until recently were the stuff of science fiction, are also available that let you do things like use predictive analysis to score leads.

  1. Visual media matters

A picture really is worth a thousand words, as the saying goes, and nobody can deny the effectiveness of a well-designed infographic. In fact, some studies suggest that Millennials are particularly attracted to content with great visuals. Animated gifs and colorful bar graphs have even found their way into heavy-duty financial reports, so why not give them a try in your business marketing efforts?

A few more tips:

  • Always keep your content relevant and current to attract the attention of your target audience.
  • Always keep all your social media and public accounts fresh. Don’t use old content or outdated pictures in any public forum.
  • Your reviews are a proxy for your online reputation, so pay careful attention to them.
  • Much online content is being consumed on mobile now, so focus specifically on the design and usability of your mobile apps.
  • Online marketing is essentially geared towards getting more traffic onto your site. The more people visit, the better your chances of increasing sales.

Want more insight on how digital marketing is evolving? See Shutterstock Report: The Face Of Marketing Is Changing — And It Doesn’t Include Vince Vaughn.

Comments

About Sunny Popali

Sunny Popali is SEO Director at www.tempocreative.com. Tempo Creative is a Phoenix inbound marketing company that has served over 700 clients since 2001. Tempos team specializes in digital and internet marketing services including web design, SEO, social media and strategy.

Social Media Matters: 6 Content And Social Media Trend Predictions For 2016 [INFOGRAPHIC]

Julie Ellis

As 2015 winds down, it’s time to look forward to 2016 and explore the social media and content marketing trends that will impact marketing strategies over the next 15 months or so.

Some of the upcoming trends simply indicate an intensification of current trends, however others indicate that there are new things that will have a big impact in 2016.

Take a look at a few trends that should definitely factor in your planning for 2016.

1. SEO will focus more on social media platforms and less on search engines

Clearly Google is going nowhere. In fact, in 2016 Google’s word will still essentially be law when it comes to search engine optimization.

However, in 2016 there will be some changes in SEO. Many of these changes will be due to the fact that users are increasingly searching for products and services directly from websites such as Facebook, Pinterest, and YouTube.

There are two reasons for this shift in customer habits:

  • Customers are relying more and more on customer comments, feedback, and reviews before making purchasing decisions. This means that they are most likely to search directly on platforms where they can find that information.
  • Customers who are seeking information about products and services feel that video- and image-based content is more trustworthy.

2. The need to optimize for mobile and touchscreens will intensify

Consumers are using their mobile devices and tablets for the following tasks at a sharply increasing rate:

  • Sending and receiving emails and messages
  • Making purchases
  • Researching products and services
  • Watching videos
  • Reading or writing reviews and comments
  • Obtaining driving directions and using navigation apps
  • Visiting news and entertainment websites
  • Using social media

Most marketers would be hard-pressed to look at this list and see any case for continuing to avoid mobile and touchscreen optimization. Yet, for some reason many companies still see mobile optimization as something that is nice to do, but not urgent.

This lack of a sense of urgency seemingly ignores the fact that more than 80% of the highest growing group of consumers indicate that it is highly important that retailers provide mobile apps that work well. According to the same study, nearly 90% of Millennials believe that there are a large number of websites that have not done a very good job of optimizing for mobile.

3. Content marketing will move to edgier social media platforms

Platforms such as Instagram and Snapchat weren’t considered to be valid targets for mainstream content marketing efforts until now.

This is because they were considered to be too unproven and too “on the fringe” to warrant the time and marketing budget investments, when platforms such as Facebook and YouTube were so popular and had proven track records when it came to content marketing opportunity and success.

However, now that Instagram is enjoying such tremendous growth, and is opening up advertising opportunities to businesses beyond its brand partners, it (along with other platforms) will be seen as more and more viable in 2016.

4. Facebook will remain a strong player, but the demographic of the average user will age

In 2016, Facebook will likely remain the flagship social media website when it comes to sharing and promoting content, engaging with customers, and increasing Internet recognition.

However, it will become less and less possible to ignore the fact that younger consumers are moving away from the platform as their primary source of online social interaction and content consumption. Some companies may be able to maintain status quo for 2016 without feeling any negative impacts.

However, others may need to rethink their content marketing strategies for 2016 to take these shifts into account. Depending on their branding and the products or services that they offer, some companies may be able to profit from these changes by customizing the content that they promote on Facebook for an older demographic.

5. Content production must reflect quality and variety

  • Both B2B and B2C buyers value video based content over text based content.
  • While some curated content is a good thing, consumers believe that custom content is an indication that a company wishes to create a relationship with them.
  • The great majority of these same consumers report that customized content is useful for them.
  • B2B customers prefer learning about products and services through content as opposed to paid advertising.
  • Consumers believe that videos are more trustworthy forms of content than text.

Here is a great infographic depicting the importance of video in content marketing efforts:
Small Business Video infographic

A final, very important thing to note when considering content trends for 2016 is the decreasing value of the keyword as a way of optimizing content. In fact, in an effort to crack down on keyword stuffing, Google’s optimization rules have been updated to to kick offending sites out of prime SERP positions.

6. Oculus Rift will create significant changes in customer engagement

Oculus Rift is not likely to offer much to marketers in 2016. After all, it isn’t expected to ship to consumers until the first quarter. However, what Oculus Rift will do is influence the decisions that marketers make when it comes to creating customer interaction.

For example, companies that have not yet embraced storytelling may want to make 2016 the year that they do just that, because later in 2016 Oculus Rift may be the platform that their competitors will be using to tell stories while giving consumers a 360-degree vantage point.

For a deeper dive on engaging with customers through storytelling, see Brand Storytelling: Where Humanity Takes Center Stage.

Comments

About Julie Ellis

Julie Ellis – marketer and professional blogger, writes about social media, education, self-improvement, marketing and psychology. To contact Julie follow her on Twitter or LinkedIn.

How AI Can End Bias

Yvonne Baur, Brenda Reid, Steve Hunt, and Fawn Fitter

We humans make sense of the world by looking for patterns, filtering them through what we think we already know, and making decisions accordingly. When we talk about handing decisions off to artificial intelligence (AI), we expect it to do the same, only better.

Machine learning does, in fact, have the potential to be a tremendous force for good. Humans are hindered by both their unconscious assumptions and their simple inability to process huge amounts of information. AI, on the other hand, can be taught to filter irrelevancies out of the decision-making process, pluck the most suitable candidates from a haystack of résumés, and guide us based on what it calculates is objectively best rather than simply what we’ve done in the past.

In other words, AI has the potential to help us avoid bias in hiring, operations, customer service, and the broader business and social communities—and doing so makes good business sense. For one thing, even the most unintentional discrimination can cost a company significantly, in both money and brand equity. The mere fact of having to defend against an accusation of bias can linger long after the issue itself is settled.

Beyond managing risk related to legal and regulatory issues, though, there’s a broader argument for tackling bias: in a relentlessly competitive and global economy, no organization can afford to shut itself off from broader input, more varied experiences, a wider range of talent, and larger potential markets.

That said, the algorithms that drive AI don’t reveal pure, objective truth just because they’re mathematical. Humans must tell AI what they consider suitable, teach it which information is relevant, and indicate that the outcomes they consider best—ethically, legally, and, of course, financially—are those that are free from bias, conscious or otherwise. That’s the only way AI can help us create systems that are fair, more productive, and ultimately better for both business and the broader society.

Bias: Bad for Business

When people talk about AI and machine learning, they usually mean algorithms that learn over time as they process large data sets. Organizations that have gathered vast amounts of data can use these algorithms to apply sophisticated mathematical modeling techniques to see if the results can predict future outcomes, such as fluctuations in the price of materials or traffic flows around a port facility. Computers are ideally suited to processing these massive data volumes to reveal patterns and interactions that might help organizations get ahead of their competitors. As we gather more types and sources of data with which to train increasingly complex algorithms, interest in AI will become even more intense.

Using AI for automated decision making is becoming more common, at least for simple tasks, such as recommending additional products at the point of sale based on a customer’s current and past purchases. The hope is that AI will be able to take on the process of making increasingly sophisticated decisions, such as suggesting entirely new markets where a company could be profitable, or finding the most qualified candidates for jobs by helping HR look beyond the expected demographics.

As AI takes on these increasingly complex decisions, it can help reduce bias, conscious or otherwise. By exposing a bias, algorithms allow us to lessen the impact of that bias on our decisions and actions. They enable us to make decisions that reflect objective data instead of untested assumptions; they reveal imbalances; and they alert people to their cognitive blind spots so they can make more accurate, unbiased decisions.

Imagine, for example, a major company that realizes that its past hiring practices were biased against women and that would benefit from having more women in its management pipeline. AI can help the company analyze its past job postings for gender-biased language, which might have discouraged some applicants. Future postings could be more gender neutral, increasing the number of female applicants who get past the initial screenings.

AI can also support people in making less-biased decisions. For example, a company is considering two candidates for an influential management position: one man and one woman. The final hiring decision lies with a hiring manager who, when they learn that the female candidate has a small child at home, assumes that she would prefer a part-time schedule.

That assumption may be well intentioned, but it runs counter to the outcome the company is looking for. An AI could apply corrective pressure by reminding the hiring manager that all qualifications being equal, the female candidate is an objectively good choice who meets the company’s criteria. The hope is that the hiring manager will realize their unfounded assumption and remove it from their decision-making process.

At the same time, by tracking the pattern of hiring decisions this manager makes, the AI could alert them—and other people in HR—that the company still has some remaining hidden biases against female candidates to address.

Look for Where Bias Already Exists

In other words, if we want AI to counter the effects of a biased world, we have to begin by acknowledging that the world is biased. And that starts in a surprisingly low-tech spot: identifying any biases baked into your own organization’s current processes. From there, you can determine how to address those biases and improve outcomes.

There are many scenarios where humans can collaborate with AI to prevent or even reverse bias, says Jason Baldridge, a former associate professor of computational linguistics at the University of Texas at Austin and now co-founder of People Pattern, a startup for predictive demographics using social media analytics. In the highly regulated financial services industry, for example, Baldridge says banks are required to ensure that their algorithmic choices are not based on input variables that correlate with protected demographic variables (like race and gender). The banks also have to prove to regulators that their mathematical models don’t focus on patterns that disfavor specific demographic groups, he says. What’s more, they have to allow outside data scientists to assess their models for code or data that might have a discriminatory effect. As a result, banks are more evenhanded in their lending.

Code Is Only Human

The reason for these checks and balances is clear: the algorithms that drive AI are built by humans, and humans choose the data with which to shape and train the resulting models. Because humans are prone to bias, we have to be careful that we are neither simply confirming existing biases nor introducing new ones when we develop AI models and feed them data.

“From the perspective of a business leader who wants to do the right thing, it’s a design question,” says Cathy O’Neil, whose best-selling book Weapons of Math Destruction was long-listed for the 2016 National Book Award. “You wouldn’t let your company design a car and send it out in the world without knowing whether it’s safe. You have to design it with safety standards in mind,” she says. “By the same token, algorithms have to be designed with fairness and legality in mind, with standards that are understandable to everyone, from the business leader to the people being scored.” (To learn more from O’Neil about transparency in algorithms, read Thinkers in this issue.)

Don’t Do What You’ve Always Done

To eliminate bias, you must first make sure that the data you’re using to train the algorithm is itself free of bias, or, rather, that the algorithm can recognize bias in that data and bring the bias to a human’s attention.

SAP has been working on an initiative that tackles this issue directly by spotting and categorizing gendered terminology in old job postings. Nothing as overt as No women need apply, which everyone knows is discriminatory, but phrases like outspoken and aggressively pursuing opportunities, which are proven to attract male job applicants and repel female applicants, and words like caring and flexible, which do the opposite.

Once humans categorize this language and feed it into an algorithm, the AI can learn to flag words that imply bias and suggest gender-neutral alternatives. Unfortunately, this de-biasing process currently requires too much human intervention to scale easily, but as the amount of available de-biased data grows, this will become far less of a limitation in developing AI for HR.

Similarly, companies should look for specificity in how their algorithms search for new talent. According to O’Neil, there’s no one-size-fits-all definition of the best engineer; there’s only the best engineer for a particular role or project at a particular time. That’s the needle in the haystack that AI is well suited to find.

Look Beyond the Obvious

AI could be invaluable in radically reducing deliberate and unconscious discrimination in the workplace. However, the more data your company analyzes, the more likely it is that you will deal with stereotypes, O’Neil says. If you’re looking for math professors, for example, and you load your hiring algorithm with all the data you can find about math professors, your algorithm may give a lower score to a black female candidate living in Harlem simply because there are fewer black female mathematicians in your data set. But if that candidate has a PhD in math from Cornell, and if you’ve trained your AI to prioritize that criterion, the algorithm will bump her up the list of candidates rather than summarily ruling out a potentially high-value hire on the spurious basis of race and gender.

To further improve the odds that AI will be useful, companies have to go beyond spotting relationships between data and the outcomes they care about. It doesn’t take sophisticated predictive modeling to determine, for example, that women are disproportionately likely to jump off the corporate ladder at the halfway point because they’re struggling with work/life balance.

Many companies find it all too easy to conclude that women simply aren’t qualified for middle management. However, a company committed to smart talent management will instead ask what it is about these positions that makes them incompatible with women’s lives. It will then explore what it can change so that it doesn’t lose talent and institutional knowledge that will cost the company far more to replace than to retain.

That company may even apply a second layer of machine learning that looks at its own suggestions and makes further recommendations: “It looks like you’re trying to do X, so consider doing Y,” where X might be promoting more women, making the workforce more ethnically diverse, or improving retention statistics, and Y is redefining job responsibilities with greater flexibility, hosting recruiting events in communities of color, or redesigning benefits packages based on what similar companies offer.

Context Matters—and Context Changes

Even though AI learns—and maybe because it learns—it can never be considered “set it and forget it” technology. To remain both accurate and relevant, it has to be continually trained to account for changes in the market, your company’s needs, and the data itself.

Sources for language analysis, for example, tend to be biased toward standard American English, so if you’re building models to analyze social media posts or conversational language input, Baldridge says, you have to make a deliberate effort to include and correct for slang and nonstandard dialects. Standard English applies the word sick to someone having health problems, but it’s also a popular slang term for something good or impressive, which could lead to an awkward experience if someone confuses the two meanings, to say the least. Correcting for that, or adding more rules to the algorithm, such as “The word sick appears in proximity to positive emoji,” takes human oversight.

Moving Forward with AI

Today, AI excels at making biased data obvious, but that isn’t the same as eliminating it. It’s up to human beings to pay attention to the existence of bias and enlist AI to help avoid it. That goes beyond simply implementing AI to insisting that it meet benchmarks for positive impact. The business benefits of taking this step are—or soon will be—obvious.

In IDC FutureScapes’ webcast “Worldwide Big Data, Business Analytics, and Cognitive Software 2017 Predictions,” research director David Schubmehl predicted that by 2020 perceived bias and lack of evidentiary transparency in cognitive/AI solutions will create an activist backlash movement, with up to 10% of users backing away from the technology. However, Schubmehl also speculated that consumer and enterprise users of machine learning will be far more likely to trust AI’s recommendations and decisions if they understand how those recommendations and decisions are made. That means knowing what goes into the algorithms, how they arrive at their conclusions, and whether they deliver desired outcomes that are also legally and ethically fair.

Clearly, organizations that can address this concern explicitly will have a competitive advantage, but simply stating their commitment to using AI for good may not be enough. They also may wish to support academic efforts to research AI and bias, such as the annual Fairness, Accountability, and Transparency in Machine Learning (FATML) workshop, which was held for the third time in November 2016.

O’Neil, who blogs about data science and founded the Lede Program for Data Journalism, an intensive certification program at Columbia University, is going one step further. She is attempting to create an entirely new industry dedicated to auditing and monitoring algorithms to ensure that they not only reveal bias but actively eliminate it. She proposes the formation of groups of data scientists that evaluate supply chains for signs of forced labor, connect children at risk of abuse with resources to support their families, or alert people through a smartphone app when their credit scores are used to evaluate eligibility for something other than a loan.

As we begin to entrust AI with more complex and consequential decisions, organizations may also want to be proactive about ensuring that their algorithms do good—so that their companies can use AI to do well. D!

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


About the Authors:

Yvonne Baur is Head of Predictive Analytics for Sap SuccessFactors solutions.

Brenda Reid is Vice President of Product Management for Sap SuccessFactors solutions.

Steve Hunt is Senior Vice President of Human Capital Management Research for Sap SuccessFactors solutions.

Fawn Fitter is a freelance writer specializing in business and technology.

Comments

Tags:

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 Derek Klobucher

Derek Klobucher is a Brand Journalist, Content Marketer and Master Digital Storyteller at SAP. His responsibilities include conceiving, developing and conducting global, company-wide employee brand journalism training; managing content, promotion and strategy for social networks and online media; and mentoring SAP employees, contractors and interns to optimize blogging and social media efforts.

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

Tiffany Rowe

About Tiffany Rowe

Tiffany Rowe is a marketing administrator who assists in contributing resourceful content. Tiffany prides herself in her ability to provide high-quality content that readers will find valuable.

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

Andreas Heckmann

About Andreas Heckmann

Andreas Heckmann is head of Product Support at SAP. You can follow him on Twitter, LinkedIn, and WeChat at AndHeckmann.

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 Joerg Koesters

Joerg Koesters is the Head of Retail Marketing and Communication at SAP. He is a Technology Marketing executive with 20 years of experience in Marketing, Sales and Consulting, Joerg has deep knowledge in retail and consumer products having worked both in the industry and in the technology sector.

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

Henry Albrecht

About Henry Albrecht

Henry Albrecht is the CEO of Limeade, the corporate wellness technology company that measurably improves employee health, well-being and performance. Connect with Henry and the Limeade team on Twitter, Facebook and LinkedIn.

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

About Timo Elliott

Timo Elliott is the VP of Global Innovation Evangelist at SAP. Over the last 25 years, I've presented to Business and IT audiences in over 50 different countries around the world, on themes such as Digital Transformation, Big Data and Analytics, the Internet of Things, the future of Digital Marketing, and the challenges of technology culture change in organizations.

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

Bruce McCuaig

About Bruce McCuaig

Bruce McCuaig is the director of Solution Marketing, Governance Risk and Compliance at SAP. His specialties include Enterprise Risk Management, Governance, Management Consulting and Strategy.

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 Bob Caswell

Bob Caswell is Senior Product Manager of the Internet of Things at SAP.

Tags:

awareness