Archive for July, 2018

15 Change Management Mistakes You’re Probably Making

July 30th, 2018

It’s often been said that change is the only constant in life. Trite though it may be, this adage rings true, especially in the business world. Markets, technologies and customer preferences are always shifting and evolving, and these factors can have a significant impact on internal operations.

As a leader, it’s your job to not only clearly communicate big changes, but help your team navigate through them. However, this is easier said than done, which is why we asked the experts at Forbes Coaches Council for their advice. Below, they discuss the biggest mistakes leaders make in change management, and how to avoid those errors in your own organization.


  1. Not Developing A Clear Communication Plan For Before, During And After Change

Insufficient communication is the leading problem when it comes to moving employees through change. Organizations that practice transparency and provide information before, during and after the change process will have a more accepting workforce. A communication plan should be developed including different forms of communication taking place at different times. – Karin Naslund, Naslund Consulting Group Inc.

  1. Ignoring The Root Causes Of Employee Resistance

People don’t buy into seemingly bad ideas. Leaders make the mistake of assuming that resistance to change is due to disengaged or difficult employees. In the majority of cases, employees resist change because the information they have tells them this initiative is unwise, ill-founded or unlikely to stick. Leaders need to get curious about the true sources of resistance and take action on those. – Maureen Cunningham, Up Until Now Inc.

  1. Not Asking For Or Incorporating Team Feedback

When instituting change, leaders need to constantly seek feedback on the real-time effects of the changes and be open to adjusting their plan to achieve the desired results. Leaders should be constantly measuring the effects of change and seeking feedback from the affected team members. You then have the data to make adjustments to the plan in order to get the best possible results. – David Galowich, Terra Firma Leadership LLC

  1. Dictating Change, Rather Than Educating People About It

Instituting change from the top down may be your prerogative as a leader but the tendency is to bring this on as a demand and not an education. Companies that bring change on gently find that people adapt and accept it. Education encourages. Harsh decisions will be accepted but often come in more harshly. Training, teaching and peer-to-peer education are the best ways to create positive change. – John M. O’Connor, Career Pro Inc.

  1.  Inconsistent Leadership Involvement

One of the biggest reasons change initiatives fail to materialize is inconsistent executive sponsorship. Change leaders tend to be very vocal and active in the beginning, but with time become inactive. This lack of visibility fuels more resistance to change and runs counter to a successful initiative. Leaders need to stay active and visible throughout the change cycle, not just the beginning. – Ali Merchant, Ali Merchant

  1. Oversimplifying The Change

In my experience, leaders often address change management from an overly simplistic perspective. That perspective is often rooted in their own level of development. Since much of the workforce comes from what’s known as an Expert or Achiever point of view, it’s easy to miss the complexity of change. Such complexity calls for the ability to see the impact of change across multiple systems. – Sharon Spano, Spano & Company, Inc.

  1. Expecting Immediate Acceptance Of Change

People react to a major change in phases, similar to the stages of grief. Understand that buy-in is gradual, and support your team at each phase. Are they in denial? Give them proof with a project timeline. Are you seeing resistance? Comfort them about what they may be losing. Are they exploring with lots of questions? Support them with answers. – Loren Margolis, Training & Leadership Success LLC

  1. Downplaying The Impact Of The Change

Leaders often minimize the change or, more specifically, the impact of the change on engagement and productivity. Leaders have had much more time with the change and have rationalized the impact of the change for themselves. They may also lack the courage to face the change and therefore downplay it to the team. – Michael Brainard, Brainard Strategy

  1. Assuming Employees Know What to Do

Sometimes leaders of change lay out what needs to happen, yet employees don’t know how to move forward. Likely feeling threatened, many employees won’t say anything and become frustrated and fearful for their jobs. Training programs can provide the skills development necessary for success. Coaching programs can help employees identify their emotions and beliefs that might be holding them back. – Barbara OMalley, Exec Advance LLC

  1. Failing To Actively Participate In The Change

There is only so much your change management team can do to prepare, train and reinforce within the organization. The real impact comes from the C-level and executive teams championing the change and leading by example. Leaders can’t expect teams to adopt if they are not actively and publicly participating. – Leanne Wong, Leanne Wong

  1. Neglecting To Involve Those Impacted By The Change

Leaders should decide the “what” of the change and engage others in the “how.” People resist change when it is done to them. When they are a part it, they can see how they’re impacted and how to influence it. One of the first things leaders need to do is identify key stakeholders — both individuals and groups — and identify ways to engage with them early and often. – Edith Onderick-Harvey, NextBridge Consulting, LLC

  1. Not Communicating The Change In A Way That Speaks To Your Team’s Different Personalities

Stabilizers love predictability in their day and aren’t a big fan of change. Organizers want the stats to back up your reasoning. Fixers will step in and help everyone deal with the changes as painlessly as possible. Independents love change and will be pushing you for more. Use “Culture Types” to develop your strategy around roll-out, and you’ll be delighted at its effective implementation. – Dr. Rachel MK Headley, Rose Group, Intl

  1. Trying To Make A Big Change All At Once

Change happens frequently and can be complex. Break change down into manageable steps. Take the most immediate small step that can bring the greatest value. Mastering change comes from being present and seeing opportunities that exist now. Similar to the concept of time to market, be the first to manage the change, no matter how small. – Alan Trivedi, Trivedi Coaching & Consulting Group

  1. Not Helping Others Envision The Possibilities

When changes come, they create uncertainty, doubt and concern among staff. Good leadership requires walking through the upcoming or ongoing change together and casting a vision of the new possibilities that will come about as a result of the change. Help your employees and teammates see the future that you see, and empathize with their potential concerns as you journey together. – Billy Williams, Archegos

  1. Not Outlining And Supporting The Internal Transitional Steps

Change is situational, transition is psychological. Strong change management incorporates both processes. Guide the situational change with clarity of purpose, training and resources, and offer space and time for individuals to digest and process the associated internal transition. Making the steps of transitions known ensures the people will drive the change rather than the change driving them. – Tonyalynne Wildhaber, The Courage Practice


Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Forbes Coaches Council.

Empowering Marketers: When Customer Acquisition Could Go Wrong Without Data Science

July 23rd, 2018

In this fast-paced, fast-food world, advertising is only as good as the science behind it. Customer acquisition is a complex machine requiring attention to all the details and one small slip in the process could cost you millions in revenue. Fancy advertising just doesn’t cut it anymore — you need top-shelf scientific data to get the results you want.

Obtaining quality data is critical especially for startups with limited budgets. Analysts believe (registration required) that companies that use data-driven marketing are six times as likely to be profitable every year and 75% of companies that use it have an advantage over their competition.

Data science allows you to gain valuable insights into who your customers are before spending even one dollar of marketing on them. Demanding consumers are littering the internet with more information than ever. Using this information, you can identify intent and use predictive analysis to hook them in at the right time when they are ready to buy.

Improved Consumer Segmentation — Dig Deeper

It’s not enough to just collect demographic information on your customers. You need to dig deep and know all about who they are, where their interests lie and what kinds of things they buy, why they buy them and when.

According to Google, a person’s online life tells a story, and they call this “I want to moments.” What they do online, where they go and what they click on indicates valuable intent signals. These signals are the gold in the data that you can use to segment and target your audience.

  1. Combine Signals For A Deeper Dive

Capturing one segment of data is not adequate, by combining multiple signals you get a clearer picture and can better pinpoint your marketing strategies. For example, if you gather data on customer search history, this is great information. However, when you combine it with articles they read and videos they watch online, it becomes much more powerful in fleshing out your customer profile. You get to see the whole person come to life in the data.

To finish painting a complete picture of your segment audience, you must collect data from multiple channels. Technology can help with this piece, and programmatic tools will work towards creating a richer, more effective customer profile.

The last thing you want to do as a marketer is to spend money advertising to customers who are not ready to buy your product. Using purchase intent signals and developing predictive models, your team can learn to identify customers who are ready to buy and encourage a purchase.

  1. Fine Tune Your Target Audience With Personalized Marketing

Using a deep dive into customer data will help you identify your target audience to figure out which consumers will be more profitable long-term. Those customers that are more likely to be repeat customers are worth the investment, whereas one-off sales might not be. It’s about lifetime value, not selling to the masses.

One great example of this is a lawn company in Nashville Texas. They started by running a simple Adwords campaign that earned a click-through rate of 1% and a conversion of about 10%. Their CEO Bryan Clayton thought they could do better.

They accessed public records for marketing to find median income levels and property values. They found that East Nashville was populated with a price-sensitive demographic. They then ran a new ad targeted specified to those zip codes which touted “The Cheapest Lawn Mowing in Nashville. Lawn mowing from $20.” This fine-tuning paid off. The new ad generated a 300% click-through rate with a conversion of more than 30%.

The better you know your customer, the easier it is to engage with them and create lasting relationships. It’s not just about selling one item to a lot of customers anymore. These days the marketing game is about customer loyalty, satisfaction and retention.

  1. Email — Still Your Strongest Marketing Tool

Email remains the strongest form of marketing tools with the highest return on investment. Digital strategist Jennie Holmes recommends combining your email campaigns with social media. Instead of following up with the segment that didn’t open your email, target those that clicked on a link and set up a tailored Facebook ad that ties in with the same subject. Social media ads allow you to segment your audience with helpful tools such as customer lists, website traffic data and app activities. Instead of chasing those elusive customers, focus on the ones that are already interested.

Collect The Right Big Data For Your Business

Big data plays a huge role in effective marketing and better decision making. The use of big data makes it possible for you to pinpoint your perfect customer, target a specific set of consumers and fine-tune your marketing techniques and content.

Quality data is a crucial component to marketing success. Without the use of data science and analysis, these efforts would be nearly impossible. All data is not created equal, and you must obtain the most useful and effective data for your marketing strategies through channels that make sense.

The Bottom Line

Without data science, customer acquisition is a guessing game and sales a hit or miss. Integrating technology with quality data allows you to market more successfully with relevant, engaging customer experiences that equals a recipe for success.

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Waije Coler.

Preparing Your Business For The Artificial Intelligence Revolution

July 16th, 2018

Today, when asked about artificial intelligence (AI), many people start painting science fiction inspired images of machine-ruled futures and robots completing manual tasks for human beings. To them, AI is only a concept, something that’s going to happen tomorrow.

In reality, artificial intelligence is already part of our lives. We use AI every day. It’s not only on your smartphones, laptops and cars, it’s everywhere.

Is 2018 The Year That The AI Revolution Goes Mainstream?

For the last few years, AI has entered the consciousness of every industry. It has become part of mainstream conversations. Businesses of all shapes and sizes are considering artificial intelligence to solve real business problems.

In the past, only the largest corporations could afford to invest in AI technology, but things are changing fast. In fact, the high-speed growth of AI makes it more likely that startups and younger businesses will be able to embrace the technology earlier than their corporate colleagues.

According to a PricewaterhouseCoopers (PwC) report, the global economy can see a potential contribution of $15.7 trillion from AI by the year 2030. China and North America will receive almost 70% of this potential global GDP growth.

Opportunities For AI Across Industries

Artificial intelligence can be used to solve problems across the board. AI can help businesses increase sales, detect fraud, improve customer experience, automate work processes and provide predictive analysis.

Industries like health care, automotive, financial services and logistics have a lot to gain from AI implementations. Artificial intelligence can help health care service providers with better tools for early diagnostics. The autonomous cars are a direct result of improvements in AI.

Financial services can benefit from AI-based process automation and fraud detection. Logistics companies can use AI for better inventory and delivery management. The retail business can map consumer behavior using AI. Utilities can use smart meters and smart grids to decrease power consumption.

The rise of chatbots and virtual assistants are also a result of artificial intelligence. Amazon’s Alexa, Google’s Home, Apple’s Siri and Microsoft’s Cortana are all using AI-based algorithms to make life better. These technologies will take more prominent roles in dictating future consumer behavior. Most of your future transactions will be completed with the help of an AI-based chatbot or virtual assistant.

Organizations Are Realizing The Potential Of AI

Implementing machine learning and AI is going to have a major impact on your organization’s efficiency. Intelligent systems can automate a great amount of your work and help reduce the risk of human errors. As time goes by, your systems will learn and get smarter. It will result in better outcomes.

Many businesses are starting to recognize the significant benefits and the potential competitive edge they can gain from using AI. There’s a growing interest from every industry about exploring the possibilities.

Organizations are already using artificial intelligence to make practical decisions. For example, Coca-Cola released Cherry Sprite based on their AI product analysis. Furthermore, the soft drink company is planning to create its own virtual assistant to incorporate into its vending machines.

Implementing AI In Your Organization

With so much conversation about AI, there is a real fear of losing out. Remember that it’s only the beginning of the AI revolution. According to Gartner 2018 CIO survey (registration required), only 4% of surveyed companies have invested and deployed an AI-based solution. The rest of the companies are at various planning stages. So if you don’t have an AI-based solution yet, don’t panic. It’s important to start looking at possible tools for your business. Here are a few strategies:

Figure Out Your Business Needs

Take a good look at your business and determine what strategic pain points can be eliminated using AI-based solutions. AI can provide predictive analytics for your business. It can help you automate tasks. Through examination, you can determine the right objectives for your business.

Understand The Risks

Any new technology comes with risks, but the only way to master the technology is through using it and learning from your mistakes. You can take initiatives with smaller scopes and critically evaluate every failure. It will help you understand your risk factors and give you data to make better decisions in the future.

Find Valuable AI Services

To implement AI solutions in the real world, you need AI developers. Due to the fast-growing AI market, developers are a scarce resource. Furthermore, in order to train and deploy the AI applications, developers need access to scalable and affordable computational infrastructure that can support the necessary AI processing. Also, they need raw data and specialists for data labeling, model output validation and more. Building this AI infrastructure is time-consuming and costly. Most companies simply can’t afford to hire 100 data mappers in-house and implement the infrastructure to support them, but there are services available that make AI app development accessible and affordable for businesses. So you don’t have to build the infrastructure and the human capital from scratch. You can use these services to fast-track your AI efforts.

Build The Right Background

To win in any technology war, you need the right people and the right culture. Hiring employees takes time. Building a good culture takes time. You need to invest resources to improve your chances. While it’s expensive to invest in new technology and new talent, it’s worth it. It can transform your business.

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Dmitry Matskevich.


Do You Fear Artificial Intelligence Will Take Your Job?

July 10th, 2018

Artificial intelligence (AI) has been around longer than most people realize. The intent behind much of AI is to free us from mundane repetitive tasks, giving us more time to grow our intellects and businesses, with more interesting, evolving actions. We want what we want when we want it. AI offers us that access with speed and accuracy when we need it.

In London, self-driving robots deliver food. In Pasadena, California, a robot named Flippy can cook it. Last fall, an autonomous train made its way across the Australian outback for the first time, and Zhuzhou, China, began testing a trackless and driverless train that navigates city streets by means of lines painted on the road. From writing articles for The Washington Post to creating music, artificial intelligence is everywhere. And its adoption is rapidly becoming necessary for businesses to stay competitive.

How does this affect human employees? As co-founder of a company that utilizes artificial intelligence to provide customer support solutions, I believe that low-skilled jobs are most likely to be affected and most chances of being automated. White collar jobs are also at risk though with AI taking a bigger role in the financial industry.

But despite all this, the future for human employees may be much brighter than many recent predictions. While AI destroys jobs, it also creates them. And according to a report from the research firm Gartner, artificial intelligence is currently creating more jobs than it destroys, with a net increase of over two million jobs by 2025. This includes not only the obvious jobs such as software engineers but also low-level jobs such as training AI to recognize objects or human activity and many others.

AI may destroy jobs and it may create them, but it’s not always about man versus machine. AI can be at its best when it helps humans to perform jobs. For example, last year, Walmart announced it was beginning tests of shelf scanning robots at 50 locations. These robots are not intended to replace human workers but to make them more efficient. The robots free employees from the tedious task of walking the aisles looking for out of stock products and allow them to focus their time on filling the shelves, replacing items left in the wrong place and fixing problems that the robots notify them of. The goal here is to reduce the number of times a customer looks for an item only to discover an empty shelf.

In the pharmaceutical industry, artificial intelligence can take on tasks that human minds simply can’t do. According to a study from Tufts University, it can take over a decade and cost over $2.5 billion to develop a drug from start to approval and market. However, most drugs don’t make it to market, some failing early, but others failing close to the end when years and millions or billions of dollars have already been spent. AI can leverage the vast amounts of data regarding medicine and health, thus potentially lowering the rate of failed trials. It can also help find appropriate patients to participate in clinical trials, model the behaviour of molecules to help predict how they will behave in the human body, and find genetic biomarkers that allow medicine to be tailored to individuals.

Artificial Intelligence Needs Humans

In the above examples, artificial intelligence plays a part in preventing human errors. However, AI also still needs human oversight to prevent its own errors.

In July of last year, a bot designed to create phone cases based on popular image searches went terribly wrong and began creating cases with disturbing medical imagery and inappropriate images which were listed for sale on Amazon by the third party seller. In a far less amusing example of AI gone wrong, it took less than a day for Twitter to teach Microsoft’s AI account “Tay Tweets” to spout racism, sexism and love for Hitler. To prevent such malformed sentences, AI models need more training data and a proactive human oversight.

The stakes grow far more serious when AI operates heavy machinery or is involved in healthcare. Autonomous vehicles have been lauded for their potential to reduce collisions, 94 percent of which are caused by human error, according to the NHTSA. After all, autonomous vehicles won’t drive while drunk, tired or distracted. However, autonomous vehicles have already failed to prevent two deaths despite the presence of safety drivers. The safety driver of a 2016 Tesla S may have relied too heavily on the autopilot. Data showed that he ignored seven warnings to return his hands to the wheel before the vehicle failed confused the white of a tractor-trailer for open sky and drove right into it. Though we all believe, the autonomous vehicles would become the norm in the next decade, safety regulations and substantial human oversight are very much needed and will be needed for the foreseeable future.

From exploring places humans can’t go to finding meaning from sources of data too large for humans to analyze, to helping doctors make diagnoses to helping prevent accidents, the potential for artificial intelligence to benefit humans appears limitless. There is valid concern that even as AI saves lives and helps businesses thrive, it will destroy livelihoods. Without a doubt, AI is taking over jobs once done by humans. However, it also creates jobs, and AI needs people to train it and watch over it. At its best, AI works with people instead of in place of them — removing the tedious parts of jobs so employees can focus on better things, doing tasks that humans were unable to, and helping employees better do their jobs.

Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Priya Mohanty.

A Crossroads: Artificial Intelligence And Advertising

July 2nd, 2018

According to Elon Musk, artificial intelligence (AI) is “our biggest existential threat.” Whether that is fact-based or hyperbole is determined by the reader’s perception of Musk as either the real-life Iron Man or a classic hype marketer. Whether Elon is trying to wake humanity before it’s too late or simply sell tickets on a Mars-bound Tesla is beside the point. The focus here should be that Elon Musk has discovered and successfully exploited the intersection of AI and advertising and so can you.

We have reached an inflection point in the advancements in, and democratization of, artificial intelligence. The technology allows businesses to harness its value daily to realize new business development opportunities and capitalize on tangible results — chief among them is a more intelligent way to advertise products and services, verify campaign efficacy and measure return on investment. On top of this, and perhaps in direct contrast with Musk’s comments, legacy radio and television are poised to be the prime benefactors of this AI-driven advertising revolution.

For many years, digital advertising has been the safest and arguably most sound bet in advertising. Cookie tracking, intellectual property (IP) targeting and other technologies allow brands and agencies to gather user and audience data in order to target their advertising campaign placement, track overall efficacy and measure return on investment (ROI) down to the click. This level of ROI transparency is tough to argue with and ultimately led to digital ad spend reaching $209 billion worldwide, which accounted for 41% of the market in 2017. Digital finally eclipsed traditional TV spending, which brought in $178 billion, or 35% of the market. With no definitive way to target, track and measure advertising efficacy, radio and television have been struggling to compete with digital until now.

While digital advertising currently makes up the lion’s share of brand and agency advertising spending, traditional radio and television companies are fighting back in a big way thanks to artificial intelligence. Developments in natural language processing, logo recognition, object detection and other AI technologies have enabled radio and television broadcasters to bring structure to a medium that has been heretofore impossible. With every word, logo, object and face indexed in near real-time, radio and television content becomes just as searchable, trackable and actionable as digital content. This is critical because without true structure — a temporal record of exactly what aired — agencies and brands had been struggling to successfully target, engage and unlock the value hidden within radio and TV. Now, with AI, legacy challenges have fast blossomed into new opportunities and there is plenty of nectar to go around.

Just take it from top media agency Carat’s chief compliance officer (CCO) Shannon Pruitt, who, in speaking to CNBC regarding product placement within traditional distribution windows, said, “Advances in audience targeting, the understanding of the role of product integration, as well as the focus on measurement capabilities to prove ROI, while still not comprehensive, has elevated the acceptance and pursuit of the opportunity to be part of the story.”

In other words, the convergence of AI technology used for audience targeting and ROI evaluation with the shifting desires of TV and radio audiences away from traditional interruptive-based 30- and 60-second commercials, has agencies and advertisers alike rushing back to TV and radio to cash in on new in-content branding opportunities. According to PQ Media, the “value of U.S. product placements will reach $11.44 billion in 2019,” surging up from $6.01 billion in 2014. This type of growth for traditional mediums who had been left with mere scraps in recent years is one very concrete example of how AI, when leveraged appropriately, can revolutionize an industry overnight.

So whether you are looking to streamline operational efficiency, innovate products or unlock additional revenue streams, you might consider taking a page out of Elon’s book and look towards artificial intelligence.


Source: All the above opinions are personal perspective on the basis of information provided by Forbes and contributor Logan Ketchum.