The Power of Stopping

The Power of Stopping

GUEST POST from Mike Shipulski

If when you write your monthly report no one responds with a question of clarification or constructive comment, this may be a sign your organization places little value on your report and the work it stands for.

If someone sends a thank you email and do not mention something specific in your report, this masked disinterest is a half-step above non-interest and is likely also a sign your organization places little value on your report and the work it stands for.

If you want to know for sure what people think of your work, stop writing your report. If no one complains, your work is not valuable to the company. If one person complains, it’s likely still not valuable. And if that single complaint comes from your boss, your report/work is likely not broadly valuable, but you’ll have to keep writing the report.

But don’t blame the organization because they don’t value your work. Instead, ask yourself how your work must change so it’s broadly valuable. And if you can’t figure a way to make your work valuable, stop the work so you can start work that is.

If when you receive someone else’s monthly report and you don’t reply with a question of clarification or constructive comment, it’s because you don’t think their work is all that important. And if this is the case, tell them you want to stop receiving their report and ask them to stop sending them to you.

Hopefully, this will start a discussion about why you want to stop hearing about their work which, hopefully, will lead to a discussion about how their work could be modified to make it more interesting and important.

This dialog will go one of two ways – they will get angry and take you off the distribution list or they will think about your feedback and try to make their work more interesting and important.

In the first case, you’ll receive one fewer report and in the other, there’s a chance their work will blossom into something magical. Either way, it’s a win.

While reports aren’t the work, they do stand for the work. And while reports are sometimes considered overhead, they do perform an inform function – to inform the company of the work that’s being worked. If the work is amazing, the reports will be amazing and you’ll get feedback that’s amazing. And if the work is spectacular, the reports will be spectacular and you’ll get feedback that matches.

But this post isn’t about work or reports, it’s about the power of stopping. When something stops, the stopping is undeniable and it forces a discussion about why the stopping started. With stopping, there can be no illusion that progress is being made because stopping is binary – it’s either stopped or it isn’t. And when everyone knows progress is stopped, everyone also knows the situation is about to get some much-needed attention from above, wanted or not.

Stopping makes a statement. Stopping gets attention. Stopping is serious business.

And here’s a little-known fact: Starting starts with stopping.

Image credit: Pixabay

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Why Data-Based Decisions Will Lead You Straight to Hell

Why Data-Based Decisions Will Lead You Straight to Hell

GUEST POST from Robyn Bolton

Many years ago, Clay Christensen visited his firm where I was a partner and told us a story*.

“I imagine the day I die and present myself at the entrance to Heaven,” he said. “The Lord will show me around, and the beauty and majesty will overcome me. Eventually, I will notice that there are no numbers or data in Heaven, and I will ask the Lord why that is.”

“Data lies,” the Lord will respond. “Nothing that lies can be in Heaven. So, if people want data, I tell them to go to Hell.”

We all chuckled at the punchline and at the strength of the language Clay used (if you ever met him, you know that he was an incredibly gentle and soft-spoken man, so using the phrase “go to Hell” was the equivalent of your parents unleashing a five-minute long expletive-laden rant).

“If you want data, go to Hell.”

Clay’s statement seems absolutely blasphemous, especially in a society that views quantitative data as the ultimate source of truth:

  • “In God we trust. All others bring data.” W. Edward Deming, founding Father of Total Quality Management (TQM)
  •  “Above all else, show the data.” – Edward R. Tufte, a pioneer in the field of data visualization
  • “What gets measured gets managed” – Peter Drucker, father of modern management studies

But it’s not entirely wrong.

Quantitative Data’s blessing: A sense of safety

As humans, we crave certainty and safety. This was true millennia ago when we needed to know whether the rustling in the leaves was the wind or a hungry predator preparing to leap and tear us limb from lime. And it’s true today when we must make billion-dollar decisions about buying companies, launching products, and expanding into new geographies.

We rely on data about company valuation and cash flow, market size and growth, and competitor size and strategy to make big decisions, trusting that it is accurate and will continue to be true for the foreseeable future.

Quantitative Data’s curse: The past does not predict the future

As leaders navigating an increasingly VUCA world, we know we must prepare for multiple scenarios, operate with agility, and be willing to pivot when change happens.

Yet we rely on data that describes the past.

We can extrapolate it, build forecasts, and create models, but the data will never tell us with certainty what will happen in the future. It can’t even tell us the Why (drivers, causal mechanisms) behind the What it describes.

The Answer: And not Or

Quantitative data Is useful. It gives us the sense of safety we need to operate in a world of uncertainty and a starting point from which to imagine the future(s).

But, it is not enough to give the clarity or confidence we need to make decisions leading to future growth and lasting competitive advantage.

To make those decisions, we need quantitative data AND qualitative insights.

We need numbers and humans.

Qualitative Insight’s blessing: A view into the future

Humans are the source of data. Our beliefs, motivations, aspirations, and actions are tracked and measured, and turned into numbers that describe what we believed, wanted, and did in the past.

By understanding human beliefs, motivations, and aspirations (and capturing them as qualitative insights), we gain insight into why we believed, wanted, and did those things and, as a result, how those beliefs, motivations, aspirations, and actions could change and be changed. With these insights, we can develop strategies and plans to change or maintain beliefs and motivations and anticipate and prepare for events that could accelerate or hinder our goals. And yes, these insights can be quantified.

Qualitative Insight’s curse: We must be brave

When discussing the merit of pursuing or applying qualitative research, it’s not uncommon for someone to trot out the saying (erroneously attributed to Henry Ford), “If I asked people what they wanted, they would have said a horse that goes twice as fast and eats half as much.”

Pushing against that assertion requires you to be brave. To let go of your desire for certainty and safety, take a risk, and be intellectually brave.

Being brave is hard. Staying safe is easy. It’s rational. It’s what any reasonable person would do. But safe, rational, and reasonable people rarely change the world.

One more story

In 1980, McKinsey predicted that the worldwide market for cell phones would max out at 900,000 subscribers. They based this prediction on solid data, analyzed by some of the most intelligent people in business. The data and resulting recommendations made sense when presented to AT&T, McKinsey’s client.

Five years later, there were 340,213 subscribers, and McKinsey looked pretty smart. In 1990, there were 5.3 million subscribers, almost 6x McKinsey’s prediction.   In 1994, there were 24.1M subscribers in the US alone (27x McKinsey’s global forecast), and AT&T was forced to pay $12.6B to acquire McCaw Cellular.

Should AT&T have told McKinsey to “go to Hell?”  No.

Should AT&T have thanked McKinsey for going to (and through) Hell to get the data, then asked whether they swung by earth to talk to humans and understand their Jobs to be Done around communication? Yes.

Because, as Box founder Aaron Levie reminds us,

“Sizing the market for a disruptor based on an incumbent’s market is like sizing a car industry off how many horses there were in 1910.”

* Except for the last line, these probably (definitely) weren’t his exact words, but they are an accurate representation of what I remember him saying

Image Credit: Pixabay

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This 9-Box Grid Can Help Grow Your Best Future Talent

This 9-Box Grid Can Help Grow Your Best Future Talent

GUEST POST from Soren Kaplan

Hiring good people is tough. Retaining your best talent can be equally challenging. In today’s disruptive world, competitive advantage relies as much on people as it does technology.

So, how do you objectively know which people are your all-stars, especially in a bigger organization? And not just the best talent today, but the best for the future?

I originally wrote this article for my Inc. Magazine column. My team at Praxie.com created an online 9-Box app and I was stunned at how much interest there was from across industries for this solution.

Keeping & Growing Talent is Today’s Name of the Game

Just as it’s easier and cheaper to retain customers than to acquire new ones, the same goes for employees. Knowing who your current and future all-stars are helps you keep them and gives you the opportunity to help them grow into more strategic roles.

The 9-box talent grid categorizes your people into nine categories. The grid contains two axes, performance and potential, each of which includes three levels each: low, moderate, and high. When you match up the categories on the axes, you get nine boxes that become classifications.

Categorizing people helps reveal who’s contributing the most now, and who will likely contribute the most in the future:

  1. Stars (High Potential, High Performance): Consistently high performance with high potential. Will likely become part of the future leadership team.
  2. High Potentials (High Potential, Moderate Performance): Solid performance overall with high potential to grow. Will most likely advance in current or future roles and may become part of the future leadership team.
  3. Enigmas (High Potential, Low Performance): While high potential, challenges exist in performance that may require additional support or training and development.
  4. High Performer (Moderate Potential, High Performance): Consistently high performance with solid potential to advance in current role and future positions with the right opportunity.
  5. Key Player (Moderate Potential, Moderate Performance): Overall good performance and potential with additional support and opportunities to grow.
  6. Inconsistent Player (Moderate Potential, Low Performance): Low performance and moderate potential require additional support and training to validate growth opportunity.
  7. Workhorses (Low Potential, High Performance): Highly effective performance yet may have peaked in terms of potential so coaching or training may help elevate potential.
  8. Backups (Low Potential, Moderate Performance): Decent performance and an asset but may not become a more significant contributor.
  9. Bad Hires (Low Potential, Low Performance): Low performance coupled with low potential means re-evaluating overall role in organization.

The team at Praxie.com has made the 9-Box application available to try to free.

9 Box Example

Shoot for the Stars

The easiest way is to assign people to the categories is based on your experience working with them. Or, if you’re in a larger organization, collect inputs from managers and aggregate the results.

Here’s how it works: The CEO of an organization works with their HR director to collect inputs from managers within the sales department. Twenty-five sales representatives are mapped into the nine boxes. The results are used to provide additional incentives, identify people for leadership development programs, and promote individual reps to managers for new territories.

The 9-box grid provides a snapshot in time. Use the tool to continually assess and reassess your talent. You’ll see some people move up and to the right while others may stay stagnant. Use these trends to help people grow. It won’t improve just your organizational culture. It will also improve your business.

Image credits: Praxie.com

This article was originally published on Inc.com and has been syndicated for this blog.

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How Consensus Kills Innovation

How Consensus Kills Innovation

GUEST POST from Greg Satell

“I hate consensus,” legendary Silicon Valley coach Bill Campbell used to growl. The problem, as the authors explain in the book, Trillion Dollar Coach, wasn’t that he didn’t want people to get along, but that an easy consensus often leads to groupthink and inferior decisions. It’s often just easier to fall in line than to engage in vigorous debate.

Research bears this out. In one study where college students were asked to solve a murder mystery, homogenous groups that formed an easy consensus felt more successful, but actually performed worse than more diverse teams that argued and voiced different viewpoints. When everybody agrees, nobody questions.

Make no mistake. If an idea is big enough, some people aren’t going to like it. Some will argue against it passionately and others may even try and actively undermine it. Yet rather than working to silence those voices, we need to learn to bring them to the fore. That’s how we can test our assumptions, consider other alternatives and, ultimately, come up with better ideas.

The Dangers of Consensus

Whenever the Harlem Globetrotters play the Washington Generals, there’s no doubt what the outcome will be, because the point isn’t to have a genuine contest. The games are essentially theatre set up to entertain the audience. All too often, we set up meetings in very much the same way — designed to reach a particular conclusion for the sake of expediency.

Unfortunately, leaders have strong incentives to drive quickly toward a consensus. Listening to dissenting views takes time and energy and we want to get things done quickly and move forward. So, it’s tempting to stock the room with people who are already on board and present the idea as a fait accompli.

Even if a leader isn’t consciously designing meetings for consensus, dissenting views can get squelched. In a famous series of conformity studies done in the 1950s, it was shown that we have a strong tendency to agree with the majority opinion even if it is obviously wrong. Subsequent research has generally confirmed the findings.

The truth is that majorities don’t just rule, they also influence. We can’t count on one or two lone voices having the courage to speak up. That’s why it’s not enough to simply listen to dissenting views, we must actively seek them out.

Uncovering Dissent

The biggest mistake a leader can make is to assume that they have somehow built a culture that is so unique, and that people feel so secure that they will voice their true views. We have to design for debate—it won’t just happen on its own—and there are several techniques that can help us do that.

The first is changing meeting structure. If the most senior person in the meeting voices an opinion, others will tend to fall in line. So, starting with the most junior person and then working up will encourage more debate. Another option is to require everyone to voice an opinion, either through a document or a conversation with a senior leader, before the meeting starts.

Another strategy that is often effective is called a pre-mortem analysis. Similar to a post-mortem analysis in which you try to figure out what went wrong, in a pre-mortem you assume a project has failed in the future and try to guess what killed it. It’s a great way to surface stuff you might have missed.

A third option is to set up a red team. This is an independent group whose sole purpose is to poke holes in a plan or a project. For example, while planning the Osama bin Laden Raid, a red team was set up to look at the same evidence and try to come up with different conclusions. They were able to identify a few key weaknesses in the plan that were then corrected.

Overcoming Opposition

While opening up a healthy discussion around dissenting views helps drive innovation forward, ignoring opposition can lead to its demise. Every significant innovation represents change, which creates winners and losers. There will always be some who will be so vehemently opposed that they will try to undermine an innovation moving forward.

Since my book Cascades was published, I’ve had the opportunity to work with a number of organizations working to drive transformation and have been amazed how reticent many are to identify entrenched opposition and build a strategy to overcome it. Often, they aren’t willing to admit that opposition is relevant or even that it exists at all.

Unlike those who merely have dissenting views, but share objectives and values with the transformation team, entrenched opposition wants to stop change in its tracks. For example, as I have previously noted, it was internal opposition, chiefly from franchisees and shareholders, not a lack of strategy or imagination, that killed Blockbuster Video.

That’s why, much like dissenting views, it’s important to bring opposition to the fore. In Blockbuster’s case, there were various actions that management could have taken to mollify the opposition and address some of the concerns. That wouldn’t have guaranteed success, but it would have made it far more likely.

Innovation Must Be Led

Steve Jobs was, by all accounts, a mediocre engineer. It was his passion and vision that made Apple the most valuable company on the planet. In a similar vein, there were plenty of electric car companies before Tesla, but Elon Musk was the first who showed that the technology can succeed in the marketplace.

Can you imagine what would have happened if Jobs had the iPhone designed by a committee? Or if Musk had put Tesla’s business plan to a vote? It’s hard to see either having had much success. What we would have ended up with is a watered-down version of the initial idea.

Yet all too often, managers seek out consensus because it’s easy and comfortable. It’s much harder to build a culture of trust that can handle vigorous debate, where people are willing to voice their opinions and listen to those of others without it getting personal. That, however, is what innovative cultures do.

Big ideas are never easy. Almost by definition, they are unlikely, fraught with risk and often counterintuitive. They need champions to inspire and empower beliefs around them. That’s why leadership drives innovation and consensus often kills it.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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Land Mines of Intrapreneurship

Land Mines of Intrapreneurship

GUEST POST from Arlen Meyers, M.D.

Entrepreneurship is the pursuit of opportunity under VUCA (volatile, uncertain, complex and ambiguous) conditions with the goal of creating user/stakeholder defined value through the deployment of innovation using a VAST business model.

Intrapreneurs are employees trying to act like entrepreneurs within their organizations or non-profits. Here is the textbook of physician intrapreneurship.

Here is how to get your ideas noticed:

If you are trying to develop and deploy an AI solution in your sickcare organization, have you answered these questions?

Here are some reasons why your initiative will fail.

Do you have a VAST edupreneur business model?

Studies show that around 60 to 80% of new products fail. The same is probably true for programs and new educational offerings. It is difficult to determine the exact number of unreported cases, because who would like to talk about his innovation flops? The odds are against you.

So, what are the landmines to detect and avoid?

  1. You did not do your homework because you where unwilling, unable to do so ,or ,you do not have an entrepreneurial mindset and think because you already have 2 people who said they were interested that you could forge ahead.
  2. You did not have an exit strategy.
  3. You did not read the field manual.
  4. You don’t have the right sponsor with staying power.
  5. You tried to bite off more than your stakeholders are willing or able to chew.
  6. You are a bad rebel and chalk it up to “being authentic.”
  7. You do not have the right clinical champions on board.
  8. You have empty seats on the bus or the wrong people sitting in them.
  9. You are making these rookie intrapreneur mindset mistakes.
  10. You are not addressing the dysfunction of teams.
  11. You are not aligned with your organization’s strategy or vision.
  12. You are working in the wrong place with a toxic or fixed culture or for the wrong person.
  13. You don’t have an innovation strategy
  14. You don’t get sales and marketing
  15. You didn’t ask and answer these four questions before you started
  16.  If you’ve got a major change on the horizon, here’s how to avoid three of the most common saboteurs of company transformation. First, understand that significant change will be harder than you think it will be to achieve. Next, be realistic about your organization’s capacity to implement changes. Finally, make sure your organization understands how and why the transformation is important to you.
  17. You have not learned how to win at Survivor  1) Don’t expect friendship. Invest in relationships outside your company to meet your emotional needs; 2) Manage sideways. Your reputation with your peers becomes an important factor as you’re being considered for senior ranks; and 3) Hone your political skills.

If you get too far ahead of your troops, it is hard to tell the difference between you and the enemy. De-risk yourself. Be careful out there.

Image credit: Pixabay

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Now is the Time to Design Cost Out of Our Products

Now is the Time to Design Cost Out of Our Products

GUEST POST from Mike Shipulski

With inflation on the rise and sales on the decline, the time to reduce costs is now.

But before you can design out the cost you’ve got to know where it is. And the best way to do that is to create a Pareto chart that defines product cost for each subassembly, with the highest cost subassemblies on the left and the lowest cost on the right. Here’s a pro tip – Ignore the subassemblies on the right.

Use your costed Bill of Materials (BOMs) to create the Paretos. You’ll be told that the BOMs are wrong (and they are), but they are right enough to learn where the cost is.

For each of the highest-cost subassemblies, create a lower-level Pareto chat that sorts the cost of each piece-part from highest to lowest. The pro tip applies here, too – Ignore the parts on the right.

Because the design community designed in the cost, they are the ones who must design it out. And to help them prioritize the work, they should be the ones who create the Pareto charts from the BOMs. They won’t like this idea, but tell them they are the only ones who can secure the company’s future profits and buy them lots of pizza.

And when someone demands you reduce labor costs, don’t fall for it. Labor cost is about 5% of the product cost, so reducing it by half doesn’t get you much. Instead, make a Pareto chart of part count by subassembly. Focus the design effort on reducing the part count of subassemblies on the left. Pro tip – Ignore the subassemblies on the right. The labor time to assemble parts that you design out is zero, so when demand returns, you’ll be able to pump out more products without growing the footprint of the factory. But, more importantly, the cost of the parts you design out is also zero. Designing out the parts is the best way to reduce product costs.

Pro tip – Set a cost reduction goal of 35%. And when they complain, increase it to 40%.

In parallel to the design work to reduce part count and costs, design the test fixtures and test protocols you’ll use to make sure the new, lower-cost design outperforms the existing design. Certainly, with fewer parts, the new one will be more reliable. Pro tip – As soon as you can, test the existing design using the new protocols because the only way to know if the new one is better is to measure it against the test results of the old one.

And here’s the last pro tip – Start now.

Image credit — aisletwentytwo

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7 Tips for Creating a Great Content Experience

7 Tips for Creating a Great Content Experience

GUEST POST from Shep Hyken

Content marketing is a sound strategy. Using email, texting, and social media, companies, and brands are taking advantage of an effective way to connect with customers. Most companies use content to deliver value-added information that gets customers excited about what they sell. That makes sense, but it’s limiting. Think beyond marketing and sales. You don’t just want people to buy your products and services. You want them to experience your company. Beyond what you sell, you want customers to know who you are, what you stand for, and more. A good content strategy helps make that happen.

Perhaps a better way to describe content marketing in this context is to rename it content experience. So, with that in mind, here are seven ways to create an experience that uses content beyond a sales pitch:

1. Get Customers Excited

This is ultimately what you want your customers to experience—excitement for your brand. Share the latest and greatest, and maybe even a sneak preview of what’s to come. Make them feel like they made the right decision to give you their contact information. Get them excited about you—and motivated to want to buy from you and evangelize your brand.

2. Educate the Customer

You might think this is about teaching the customer about your products and services, but there is more. For example, let’s say you sell sports shoes. Look beyond shoes and educate your customers about anything related to your industry. An intelligent customer makes better—and often easier—buying decisions.

3. Highlight Success Stories

Customers want a successful experience with your products, so why not share how other customers have experienced success? Showcase these examples. Turn them into case studies that customers can use to duplicate success. Let your customers tell their stories.

4. Let Customers Showcase the Best Way to Use Your Products

If you’re going to highlight success stories, consider letting your customers do the talking. In effect, these are third-party testimonials and endorsements that are worth far more than traditional paid advertising.

5. Create a Customer Support Forum Run by Customers

Create a place where customers can answer questions posed by other customers. Consumers who have problems or questions love to learn from their peers. By the way, you will want to moderate the responses and be there to comment, add information, and thank customers for their help.

6. Create Meaningful Conversations That Go Beyond What You Sell

Your content experience strategy shouldn’t be one-way. Don’t just post something (a short article, video, white paper, etc.) and walk away. Start a conversation. Ask questions that get your customers to respond and share their opinions, which will ideally lead to other customers chiming in with their thoughts. Then respond to these answers. This type of engagement can bond you with your customers.

7. Stand for Something That Creates a Bond with Your People

There are companies that are admired for their “give-back” strategies. These companies are often charitable. Or they have such a strong belief in a cause that they make it part of their publicly stated mission. It could be sustainability, diversity, and inclusion, or any other cause, charity, or important issue that might excite customers and resonate with them so much that it takes the relationship to something beyond a typical transaction of trading money for a product or service.

Content marketing becomes an experience when you go beyond sales and marketing and make it about the customer. If the content you share creates value for your customers, makes customers feel connected to you and your brand, or makes your customers smarter, you’ve crossed over from sales and marketing to the level of experience. Make your content strategy an experience.

This article originally appeared on Forbes

Image Credit: Shep Hyken

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Why Are Transformations So Hard to Manage?

Why Are Transformations So Hard to Manage?

GUEST POST from Drs. Dean Anderson and Linda Ackerman Anderson

Knowing which type of change your organization is undergoing is critical to your success. Three types exist, and each requires different change strategies, plans and degrees of employee engagement. A very common reason for failure in transformational change is leaders inadvertently using approaches that do not fit the type of change they are leading. Is this happening in your organization?

The three types of change occurring in organizations today are:

  1. Developmental
  2. Transitional
  3. Transformational

Traditional project management and change management effectively support developmental and transitional change, but they are woefully insufficient for transformational change. You will need to understand the type of change you are in to know whether typical project or change management approaches can work for you.

Developmental Change

Developmental change is the simplest type of change: it improves what you are currently doing rather than creates something new. Improving existing skills, processes, methods, performance standards, or conditions can all be developmental changes. Specific examples include increasing sales or quality, interpersonal communication training, simple work process improvements, team development, and problem-solving efforts.

Transitional Change

Transitional change replaces “what is” with something completely new. This requires designing and implementing a “new state.” The organization simultaneously must dismantle and emotionally let go of the old way of operating while the new state is being put into place. This “transitional” phase can be project managed and effectively supported with traditional change management tools. Examples include reorganizations, simple mergers or acquisitions, creation of new products or services that replace old ones, and IT implementations that do not radically impact people’s work or require a significant shift in culture or behavior to be effective.

Two variables define transitional change: (1) you can determine your destination in detail before you begin, and can, therefore, “manage” your transition, and (2) people are largely impacted only at the levels of skills and actions, not the more personal levels of mindset, behavior and culture.

Transformational Change

Transformation, however, is far more challenging for two distinct reasons. First, the future state is unknown when you begin, and is determined through trial and error as new information is gathered. This makes it impossible to “manage” transformation with pre-determined, time-bound and linear project plans. You can have an over-arching change strategy, but the actual change process literally must “emerge” as you go. This means that your executives, managers and frontline workers alike must operate in the unknown—that scary, unpredictable place where stress skyrockets and emotions run high.

Second, the future state is so radically different than the current state that the people and culture must change to implement it successfully. New mindsets and behaviors are required. In fact, often leaders and workers must shift their worldviews to even invent the required new future, let alone operate it effectively.

Without these “inner” shifts of mindset and culture, the “external” implementation of new structures, systems, processes or technology do not produce their intended ROI. For example, many large IT implementations fail because they require a mindset and culture change that does not occur, i.e., the new systems require people to share information across strongly held boundaries or put the needs of the enterprise over their own turf agendas. Without these radical changes in attitude and behavior, people do not use the technology as designed and the change fails to deliver its ROI.

Implications for the Workforce

Because transformation impacts people so personally, you must get them involved in it to garner their support; and the earlier in the process of formulating your transformation strategy the better! Employee resistance is always in direct proportion to the degree to which people are kept in the dark and out of the change process. Here are some options for employee engagement.

Get staff engaged in building your case for change and determining the vision for the new state. Consider using large group meeting technologies, which can involve hundreds of people simultaneously in short periods of time.

Consider putting a wider representation of people on your change leadership team. Provide mindset, behavior, and change skill development to all employees. Use employee groups to identify your customers’ requirements for your transformation, and to benchmark what “best-in-class” organizations are doing in your industry. Ask employee groups to input to enterprise-wide changes that impact them, and give them the authority to design the local changes for improving their work (they know it best.) Then before implementation, get them involved in doing an impact analysis of your design to ensure that it is feasible and won’t overwhelm your organization beyond what it can handle.

When you engage your employees in these ways before implementation, you minimize resistance. Use such strategies to support your change efforts, especially if they are transformational.

Image credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of July 2022

Top 10 Human-Centered Change & Innovation Articles of July 2022Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. We also publish a weekly Top 5 as part of our FREE email newsletter. Did your favorite make the cut?

But enough delay, here are July’s ten most popular innovation posts:

  1. What Latest Research Reveals About Innovation Management Software — by Jesse Nieminen
  2. Top Five Reasons Customers Don’t Return — by Shep Hyken
  3. Five Myths That Kill Change and Transformation — by Greg Satell
  4. How the Customer in 9C Saved Continental Airlines from Bankruptcy — by Howard Tiersky
  5. Changing Your Innovator’s DNA — by Arlen Meyers, M.D.
  6. Why Stupid Questions Are Important to Innovation — by Greg Satell
  7. We Must Rethink the Future of Technology — by Greg Satell
  8. Creating Employee Connection Innovations in the HR, People & Culture Space — by Chris Rollins
  9. Sickcare AI Field Notes — by Arlen Meyers, M.D.
  10. Cultivate Innovation by Managing with Empathy — by Douglas Ferguson

BONUS – Here are five more strong articles published in June that continue to resonate with people:

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America Needs to Innovate Its Innovation Ecosystem

America Needs to Innovate Its Innovation Ecosystem

GUEST POST from Greg Satell

The world today just seems to move faster and faster all the time. From artificial intelligence and self-driving cars to gene editing and blockchain, it seems like every time you turn around, there’s some newfangled thing that promises to transform our lives and disrupt our businesses.

Yet a paper published by a team of researchers in Harvard Business Review argues that things aren’t as they appear. They point out that total factor productivity growth has been depressed since 1970 and that recent innovations, despite all the hype surrounding them, haven’t produced nearly the impact of those earlier in the 20th century.

The truth is that the digital revolution has been a big disappointment and, more broadly, technology and globalization have failed us. However, the answer won’t be found in snazzier gadgets or some fabulous “Golden Era” of innovation of years long past. Rather we need to continually innovate how we innovate to solve problems that are relevant to our future.

The Productivity Paradox, Then and Now

In the 1970s and 80s, business investment in computer technology was increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so bizarre that they called it the “productivity paradox” to underline their confusion.

Yet by the late 1990s, increased computing power combined with the Internet to create a new productivity boom. Many economists hailed the digital age as a “new economy” of increasing returns, in which the old rules no longer applied and a small initial advantage, a first mover advantage, would lead to market dominance. The mystery of the productivity paradox, it seemed, had been solved. We just needed to wait for technology to hit critical mass.

Yet by 2004 productivity growth fell once again and has not recovered since. Today, more than a decade later, we’re in the midst of a second productivity paradox, just as mysterious as the first one. New technologies like mobile computing and artificial intelligence are there for everyone to see, but they have done little, if anything, to boost productivity.

Considering the rhetoric of many of the techno-enthusiasts, this is fairly shocking. Compare the meager eight years of elevated productivity that digital technology produced with the 50-year boom in productivity created in the wake of electricity and internal combustion and it’s clear that the digital economy, for all the hype, hasn’t achieved as much as many would like to think.

Are Corporations to Blame?

One explanation that the researchers give for the low productivity growth is that large firms are cutting back on investment in science. They explain that since the 1980s, a “combination shareholder pressure, heightened competition, and public failures led firms to cut back investments in science” and point to the decline of Bell Labs and Xerox PARC as key examples.

Yet a broader analysis tells a different story. Yes, while Bell Labs and Xerox PARC still exist, they are but a shadow of their former selves, but others, such as IBM Research, have expanded their efforts. Microsoft Research, established in 1991, does cutting edge science. Google runs a highly innovative science program that partners with researchers in the academic world.

So anecdotally speaking, the idea that corporations haven’t been investing in science seems off base. However, the numbers tell an even stronger story. Data from the National Science Foundation shows that corporate research has increased from roughly 40% of total investment in the 1950s and 60s to more than 60% today. Overall R&D spending has risen over time.

Also, even where corporations have cut back, new initiatives often emerge. Consider DuPont Experimental Station which, in an earlier era, gave birth to innovations such as nylon, teflon and neoprene. In recent years, DuPont has cut back on its own research but the facility, which still employs 2000 researchers, is also home to the Delaware Incubation Space, which incubates new entrepreneurial businesses.

The Rise of Physical Technologies

One theory about the productivity paradox is that investment in digital technology, while significant, is simply not big enough to move the needle. Even today, at the height of the digital revolution, information and communication technologies only make up about 6% of GDP in advanced economies.

The truth is that we still live in a world largely made up of atoms, not bits and we continue to spend most of our money on what we live in, ride in, eat and wear. If we expect to improve productivity growth significantly, we will have to do it in the physical world. Fortunately, there are two technologies that have the potential to seriously move the needle.

The first is synthetic biology, driven largely by advances in gene editing such as CRISPR, which have dramatically lowered costs while improving accuracy. In fact, over the last decade efficiency in gene sequencing has far outpaced Moore’s Law. These advances have the potential to drive important productivity gains in healthcare, agriculture and, to a lesser extent, manufacturing.

The second nascent technology is a revolution in materials science. Traditionally a slow-moving field, over the past decade improved simulation techniques and machine learning have improved the efficiencies of materials discovery dramatically, which may have a tremendous impact in manufacturing, construction and renewable energy.

Yet none of these gains are assured. To finally break free of the productivity paradox, we need to look to the future, not the past.

Collaboration is the New Competitive Advantage

In 1900, General Electric established the first corporate research facility in Schenectady, New York. Later came similar facilities at leading firms such as Kodak, AT&T and IBM. At the time, these were some of the premier scientific institutions in the world, but they would not remain so.

In the 1920s new academic institutions, such as the Institute for Advanced Study, as well as the increasing quality of American universities, became an important driver of innovation. Later, in the 1940s, 50s and 60s, federal government agencies, such as DARPA, NIH and the national labs became hotbeds of research. More recently, the Silicon Valley model of venture funded entrepreneurship has risen to prominence.

Each of these did not replace, but added to what came before. As noted above, we still have excellent corporate research programs, academic labs and public scientific institutions as well as an entrepreneurial investment ecosystem that is the envy of the world. Yet none of these will be sufficient for the challenges ahead.

The model that seems to be taking hold now is that of consortia, such as JCESR in energy storage, Partnership on AI for cognitive technologies and the Manufacturing USA Institutes, that bring together diverse stakeholders to drive advancement in key areas. Perhaps most conspicuously, unprecedented collaboration sparked by the Covid-19 crisis has allowed us to develop therapies and vaccines faster than previously thought possible.

Most of all, we need to come to terms with the fact that the answers to the challenges of the future will not be found in the past. The truth is that we need to continually innovate how we innovate if we expect to ever return to an era of renewed productivity growth.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

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