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Marketers: Revive Your Sales Funnel With Social Collaboration

Roger Noia

Despite rumors of its death, the sales funnel remains very much alive. However, what has died is marketing’s traditional approach to the funnel. The idea of the sales funnel is no longer about dumping leads generated from a campaign, tradeshow, referral, or any other interaction into a database; determining how “hot” they are as a prospect; and turning them into a customer. Instead, the concept is open-ended – maybe even resembling the shape of a mug rather than a filter.

For marketers, this is quite a challenge. They must now not only take leads through the funnel until there is a clear intent to buy, but also turn new clients into advocates willing to spread the word about the brand to their connections, company, market, and industry. To be successful, this means that marketing must collaborate effectively and in real time across every organization that interacts with customers.

How will your marketing organization keep your sales funnel alive and well in 2016? For some companies, the path to transparent customer intelligence is as simple as the social collaboration tools we use in our daily lives.

Did you know social collaboration brings funnel transparency and 14% greater productivity? 

Customers are more unpredictable than ever before and do not take the same path down the funnel. They enter and emerge the sales funnel at various stages and, at times, disappear for long periods of time before they initiate the final purchase.

For marketers who are trying to keep up, they cannot afford to get lost in e-mail chains and outdated reports and spreadsheets. Without a central location for collaboration, it is very difficult to improve business processes that provide transparency into the latest information on any lead, prospect, and client.

According to the March 2015 commissioned study conducted by Forrester Consulting on behalf of SAP, titled The Total Economic Impact™ of SAP Jam, social collaboration is an incredible vehicle for providing information quickly, accurately, and easily to the right people at the right time. Because social collaboration platforms deliver all relevant information on any potential and existing account 24×7, employees do not have to search for information, wade through reports from different sources, and wait for a response. In fact, in the study, Forrester calculated that social collaboration enabled a composite organization to be 14% more productive.

Did you know social collaboration can move customers through the funnel faster?

According to CEB, the average buyer is 57% done deciding whether they are planning to purchase long before their first interaction with a sales representative or channel. As a result, customers tend to fall through the funnel undetected, appear without warning, and take an undefined journey.

By connecting communications and information with every customer-facing organization, marketers can have a better sense of each customer’s journey. From the initial Google search to a call into customer service, marketers can pinpoint when and where the “next big deal” may happen.

More important, other organizations have an opportunity to help move customers along the funnel. Take customer service, for example. Using social collaboration, customer service can quickly locate the best experts and information across the company to answer any need. They can also access a complete customer view, including service and sales histories, and quickly gather the right team to handle escalations of any degree of difficulty. While this experience builds the customer’s trust and loyalty, Forrester revealed that it also leads to a 10% faster resolution of customer and internal issues with an associated annual financial benefit of approximately $384,600.

The key to the 2016 sales funnel: Real-time transparency, access, and communication

For years, efficient collaboration has been a holy grail that eluded many. However, marketing organizations that have achieved real-time transparency, access to information, and company-wide communication know social collaboration is the secret. By centralizing collaboration to streamline and connect business processes, marketers can accelerate the transformation from lead to customer to brand evangelist.

Are you interested in how social collaboration can help your marketing team? Check out The Total Economic Impact™ Of SAP Jam, a March 2015 commissioned study conducted by Forrester Consulting on behalf of SAP.

 

 

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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.

Level-Up Your Customer Experience: Lessons From The Gaming Industry

Mark de Bruijn

From the first teaser trailer to the final level, the gaming industry demonstrates that it knows exactly how to engage and cultivate the interest (and loyalty) of its customers. And, it’s a goldmine: there are an estimated 1.5 billion gamers, and this year revenue from the global games industry will be around $100 billion.

So, what can other industries learn from this example? Developers and game designers are under huge pressure to create a new experience each time, one that gamers are willing to pay for. Competition in the ceaselessly growing industry is enormous. For every hit, there are countless games no one plays. This constant “survival of the fittest” has a major advantage – many games offer a customer experience that has been perfected down to the finest detail.

Here are five ways gaming takes customer engagement to the next level.

1. Promotion

Popular franchises like Pokémon, Grand Theft Auto, and Battlefield are constantly preoccupied with building a relationship with their customers. Real fans know well in advance that they want to buy a game. They are teased with new features, sneak peeks, trailers, artwork, events, and promotional campaigns. Early birds get discounts and unique content, like new levels and rare weapons.

Games companies understand that customer retention is an ongoing process. And they know that it’s easier and cheaper to sell something to an existing customer than to a new one. Franchises are strong brands with recognizable characters that appeal to the gamer. It’s only a matter of galvanizing the fans into action at the right moment – for example, for the holiday season.

Foster your existing customers, whet their appetites with news of your new products or services, and reward the early birds. And just keep on building a strong brand!

2. First impressions

New mobile games appear daily and can often be downloaded for free. However, research has shown that around a quarter of the apps are opened only once. For that reason, making a good impression is very important for game developers. After all, you don’t get a second chance. That’s why a game is tested exhaustively before it’s launched.

A messy or un-intuitive interface, the lack of a tutorial, long loading times, poor performance, irritating advertising, and intrusive in-app selling can motivate people to delete a game instantly. But factors outside the game also play a role, like the description of its features, general evaluations, and the amount of space needed for installation.

Developing games is a question of testing, optimizing, and testing again. And that’s how companies should also approach their customer experience: only perfect is good enough.

3. Immersion

What actually makes a game good? Tastes differ, just as with films or music. But whether it’s a futuristic shooter, a strategic RPG, on an online word game with friends, a game has to be compelling or “immersive.” There’s no magic wand for creating an immersive experience. But there are certainly elements which contribute to it:

  • Gameplay
    • Good gameplay is crucial. Some games feature deep gameplay mechanics or have a high difficulty level, others opt for addictive elements like puzzles, and still others put the emphasis on the competitive factor (who’s the best?). Whatever they do, the game’s mechanisms must entertain the player.
    • Gameplay elements enrich the customer experience. There are countless examples of gamification. For example, at Starbucks you can earn stars with purchases. The Spanish bank BBVA lets customers perform tasks to promote the use of Internet banking. And the running app Nike+ Run Club challenges sports enthusiasts to measure themselves against others.
  • Graphics and sound
    • A brilliant-looking game that’s enhanced with varied musical and sound effects creates a credible world that gamers want to plunge into. If you constantly encounter visual errors and strange animations, or you’re irritated by poor voice actors and repetitive music, it detracts from the immersion.
    • High visual production values are also a unique selling point for companies, and not only in terms of their products and services. So, for instance, a slow or ugly (mobile) website can upset the customer journey and can motivate potential customers to head to a competitor.
  • Story
    • A huge attraction in many games is the story. Interesting characters, exciting developments, and humorous dialogues ensure that the gamer feels emotionally involved and is curious to discover what will happen. The choices you make, along with the way of playing, leads to a personal experience.
    • Marketing is increasingly concerned with emotion. You persuade the modern consumer not with superlatives, but with storytelling: a good story, which he or she would like to be part of. The interaction between customer and brand is one and the same. Buying stems from that.

Immersion is also very important for the customer experience. The process from orientation to buying and use doesn’t only have to be smooth. It must also be absorbing, personal, and even fun.

4. Customer behavior

Game developers are extremely proficient at analyzing customer behavior. The free-to-play model with in-app purchases has accorded this a completely new dimension. How long does the average gamer play? What type of content and what offers open wallets? What notifications are effective to get you to play again?

Research has shown that just 0.19 percent of mobile gamers account for half of all revenues. They are referred to jokingly as “whales.” Games companies pull out all the stops to land these meaty fish. Sometimes digital items are even developed specially for one whale. You might wonder whether this is ethical, but that gamer is certainly given the royal treatment.

Analyzing customer behavior offers valuable insights with which you can improve the customer experience. And it helps each company determine which customers are really worthwhile.

5. Feedback

Certainly with mobile games, it’s entirely normal to ask the gamer for feedback. This has all sorts of benefits. A positive review can be just enough to persuade people to try an app. But bad reviews with complaints and criticism can also be very valuable. A developer can then see immediately what he has to change.

Even better is if the feedback arrives during the development. That’s why players of previous games are often invited to beta-test a new title – an excellent way to bind gamers at an early stage and get focused feedback from the target group. It’s also an economical way to spot bugs.

Every company benefits from feedback. Take every sign from customers seriously, both positive and negative. And let them test new products, for instance in exchange for a discount.

Business can learn lots from the games industry, but the customer experience is not a game. The biggest difference? Unfortunately your company doesn’t have an endless number of lives. Once your customers walk away, it really is game over.

Here’s another industry to model: Improving The Customer Experience: It’s Time To Look To Fintech.

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Preparing Your E-Commerce Site: 3 Pitfalls To Avoid

Jake Anderson

Using a website instead of a brick-and-mortar retail store to sell products can be a great way to make money while keeping your overhead low. No need to pay rent or utilities on a storefront and hiring people to manage it—with an e-commerce site, you can open a virtual store and begin selling your wares almost immediately.

While it is similar to opening a physical store, the mere act of creating a website won’t provide you with instant sales. Yes, your overhead is much lower and moving product from your pipeline is a more seamless event; however, there are still many things that can go wrong if you aren’t paying attention or thinking about every angle.

Here are three of the most common mistakes people make when building an e-commerce site:

Not knowing where your customers are online

As with traditional marketing, not every channel is right for your business. For example, trying to sell mass-produced plastic items on a DIY website like Etsy may not net you much success. However, if fun, hand-crafted items are your thing, Etsy would be a great place to start.

It is absolutely critical that you do your homework before jumping into e-commerce. Who buys what you’re selling? Where would they go online? Look for websites that carry items similar to the ones you create. Browse their selections and see what their Internet presence is like to get a feel for what you should be doing.

Not maximizing social media

The marketing gods blessed the world of advertisers everywhere when social media came into existence. There are many different platforms that reach different types of people, which makes reaching your target audience much easier. This does take a little bit of awareness, however — for example, methods that appeal to a typical Facebook user might not work as well on Twitter or Instagram, and vice versa.

Social media is where you can build a strong brand voice and interact directly with potential customers. Understand the difference between the platforms and be as active in your community as possible in order to better serve your customers. Many e-commerce website builders integrate the major social media platforms directly on your page.

Getting too far ahead of yourself

In the early stages of any business, it’s important to pace yourself and utilize your time and resources effectively. One of the most common mistakes is purchasing too much inventory before you know what demand is going to be—you don’t want to end up with a garage or storage unit full of product with no one around to buy! To get a sense of how much demand a particular item has, search for it on eBay or other e-tailers and see how many have sold in the last month.

Opening an e-commerce store is very nuanced and comes with many obstacles. Avoiding these three pitfalls will help lead to a successful launch of your e-commerce store.

For more on the future of e-commerce, see How Can IoT Help Retailers?

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Jake Anderson

About Jake Anderson

Awestruck by Star trek as a kid, Jake Anderson has been relentless in his pursuit for covering the big technological innovations which will shape the future. A self-proclaimed gadget freak, he loves getting his hands on every piece of gadget he can afford. Contact Jake on Twitter @_ShoutatJake.

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.

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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.)?

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Jacqueline Prause

About Jacqueline Prause

Jacqueline Prause is the Senior Managing Editor of Media Channels at SAP. She writes, edits, and coordinates journalistic content for SAP.info, SAP's global online news magazine for customers, partners, and business influencers .

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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

Andre Smith

About Andre Smith

An Internet, Marketing and E-Commerce specialist with several years of experience in the industry. He has watched as the world of online business has grown and adapted to new technologies, and he has made it his mission to help keep businesses informed and up to date.

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

Jay Tchakarov

About Jay Tchakarov

Jay Tchakarov is vice president of Product Management and Marketing at HighRadius Corporation. As part of HighRadius’ executive team, he is responsible for defining HighRadius’ Credit and A/R products and for educating the market about the value of automation and advanced technologies. He and his team work closely with sales, consultants, and customers to make sure the products address critical pain points and provide quantifiable, high-value solutions. Jay has more than 15 years of experience in software development, product management, and marketing, and numerous successful product launches. Jay graduated summa cum laude and received a Bachelor of Science in Computer Science from the University of Louisiana at Lafayette, a Master of Science in Computer Science from the University of Illinois at Urbana-Champaign, and an MBA from Rice University.

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

Derek Klobucher

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

Joerg Koesters

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