Accelerating Competitive Advantage with AI: How Organisations are Moving from Experimentation to Business Impact

This blog is provided by Dr. Jennifer Barth and her team, as a companion to her interview on Innovating Leadership, Co-creating Our Future. This interview, Accelerating Competitive Advantage with Artificial Intelligence aired on 1/7/20.

Research Overview

We collaborated with Microsoft for the third year running during summer 2019, to explore the current state of AI across four specific industries, retail, manufacturing, health and financial services within the UK. We analysed how organisations within these sectors can implement AI in an ethical, cost effective and optimal way.

With rapid advancements in AI, our research answers questions around ethics, responsible innovation and the future impact of AI on our industry sectors and workforces. We gathered practical advice on how organisations can create robust and scalable AI investments.

Key Research Findings

  • 56% of organisations in the UK are using AI enabled solutions with notable advances in use of machine learning and analytics
  • Organisations already using AI at scale are performing an average of 11.5% better than those who are not – up from 5% just one year ago
  • Last year 51% of organisations did not have an AI strategy at all, a number which has decreased to 37% of organisations this year.
  • 38% of business leaders want to be leaders in AI innovation – a figure that has more than doubled since last year

Report Findings

How exactly can UK organisations scale their use of AI and secure a competitive edge while, at the same time, doing so in a way that is ethical, responsible and in line with the needs of their employees, partners and customers? Our research explores three key themes that allow organisations/leaders to truly accelerate their competitive advantage through AI enabled solutions.

  1. Moving from Experimentation to Implementation

Of all the business leaders we surveyed, only 8% classified their organisation as Advanced AI users while nearly half (48%) currently remain in the experimentation phase. Thus, over half of all British businesses using AI don’t seem to have an AI strategy at all, mainly because they lack a clear understanding about what AI can do for their business. As the people tasked with setting an organisation’s strategic direction, leaders need to quickly ascertain exactly what role AI can and should play within their organisation and provide adequate training and resources for successful AI implementation. Currently, only 21% of leaders have completed training in how they can use AI in their jobs, and only 21% are sure they can meet staffing needs related to skill changes caused by AI. Overcoming these obstacles will be crucial in enabling UK organisations to implement AI quickly and responsibly across their organisations to stay relevant in the future.

Luckily, advanced AI-organisations recognise this as those that are successfully employing the technology at an organisational level, rather than just a local or departmental one, are much more adept at evaluating the business benefits of AI investments and ensuring they have a clear objective at the outset. They are also more agile in how they operate than those that are experimenting with AI, meaning they are better equipped to respond to customer and employee needs, changes in technologies, or market conditions

  1. Create a Culture of Participation

Ensuring workers have the tools to augment their job roles with AI is critical – The change is as much about culture as it is about technology. It involves a move away from a situation in which only certain people or business functions have the tools to experiment with AI, to a democracy – where everyone has the building blocks to integrate AI into their working day and actively contribute to the development of new solutions, regardless of where they sit in the organisation

Building out your culture to equip your people will be the best competitive asset you have. Our research found AI-advanced businesses lead to stronger democratic practices, as organisations that are more advanced in their use of AI are more likely to:

  • Ensure AI is used responsibly
  • Understand and develop the skills and mindset needed to work with AI
  • Create and implement workforce diversity plans
  1. Make AI work for everyone

By establishing a clear set of developmental standards and operating principles to ensure the technology is deployed ethically, with attention to bias and in a way that actively promotes diversity and inclusion. Our research shows us that firms advanced in AI are better at tackling overall bias, as 77% of advanced organisations say they have the capability to identify bias in their organisation when it is observed (58% experimenting).

Two of the most important criteria here are the ability to accurately identify all ethical issues as they arise and understanding how to respond when they do. Crucially, the more advanced an organisation is in its AI-led digital transformation, the more likely it is to have established the operational logistics to deliver against an ethical criteria.

Take Away: Tips for Scaling AI successfully

  • Treat it as a business change programme – this needs to be something the entire organisation is involved and invested in
  • Make sure everyone is supported in knowing how the technology works – an understands how they can use AI to be more effective in their role
  • Embed a culture of integrity and ethical behaviour – it’s up to leaders to communicate internally and establish a framework for making ethical decisions – companies advanced in their AI implementation know how to operationalise solutions to these problems

Research Methodology

Our research used a mixed-method approach to analyse the current state of AI within the UK in the spring and summer of 2019. Including an in-depth literature review of academic, industry and media sources, subject matter expert interviews and case studies across a variety of academics, professionals and organisations, a social experiment on augmentation. The research also included a survey of 1000 leaders and 4000 employees in organisations with over 500 employees with focus on four industries (finance, retail, manufacturing, and healthcare). From these sources, we developed a set of dimensions as a lens through which to consider the opportunities for AI in the UK today.

More Information

To find out more about this research, click here.

To become a more innovative leader, you can begin by taking our free leadership assessments and then enrolling in our online leadership development program.

Check out the companion interview and past episodes of Innovating Leadership, Co-creating Our Future, via iTunes, Google Play, TuneIn, Stitcher, Spotify and iHeartRADIO. Stay up-to-date on new shows airing by following the Innovative Leadership Institute LinkedIn.

About the Author

Dr Jennifer Barth is an experienced ethnographer and social researcher, with a PHD from the University of Oxford. Her work is informed by empirical research on the intersections of emerging technologies and socioeconomic change. She provides companies with thought leadership and media engagement opportunities on global issues impacting and shaping our current and future socio-cultural lives.

Her current research focuses on the human impact of artificial intelligence (AI) through fieldwork experiments with IBM Watson and other providers, leading Digital Transformation and AI implementation research for Microsoft, Reinventing Loyalty with Adobe, and more. She is skilled at research design, qualitative research and analysis, quantitative analysis, new methods using emerging technologies and working with people to bring to life the stories behind numbers.

 

3 Customer Experience Equations – Math You’ll Actually Use

This blog is provided by Dave Cherry, as a companion to his interview on Innovating Leadership, Co-creating Our Future. This interview Boring Retail is Dead. Long Live the Customer Experience Industry aired on 10/15/19.

Like many of us, I took Algebra in school. My daughters, now in high school and middle school, are now doing the same. And they’ve asked me the same question that I asked many years before: “When will I ever need to solve a linear equation or calculate the slope of a line in real life?” The answer, for many of us, (with apologies to Mrs. Curry – my 9th grade math teacher), is never.

But today I’ll share 3 simple equations that are critical to success in the customer experience industry.

 

First, let me define this new industry, which actually isn’t new at all. It is a singular composition of all B2C and B2B companies that have customers. The hard lines between different segments (e.g. retail, banking, insurance, energy, etc.) have become blurred as customers (that includes all of us) engage with providers across this spectrum. As we do so, we use both the excellent and poor experiences that we have with each provider to influence our future expectations from the next one. So, companies like Starbucks, Uber, Target, Marriott, Southwest Airlines, Nordstrom, Walmart, Nationwide Insurance, Chase and more are all competing against one another in delivering customer experiences that are meaningful and memorable.

Amid constantly rising customer expectations, companies must develop a Customer Experience Strategy that is Enabled by Innovation and Informed by Analytics to stay competitive in today’s customer experience industry. Below I’ll discuss the critical equation for each element:

The Customer Experience Equation: Content + Context = Connection

A great customer experience starts with a relevant product or service that you offer. This is Content. Content comes in many forms, both tangible (e.g. a reliable, stylish watch) and intangible (e.g. insurance coverage that provides confidence and security). It also comes with a minimum level of quality as a baseline. Using the watch example, if it is not accurate, then the content of that product becomes irrelevant – it does not serve it’s intended purpose.

But content is not enough. It requires the addition of Context. You must provide the product or service to the customer in the right setting at the right time. The richest, most delicious cup of hand-crafted artisan hot chocolate isn’t that appealing on a 100-degree day in the summer. Even though the content in this example is exceptional, offering it in the wrong context diminishes the customer experience.

But when Content and Context combine in a relevant and meaningful way, you create a Connection with your customer that delivers on their experience expectation. When Uber delivers a comfortable and clean ride, combined with the convenience of a frictionless checkout when you are in a rush to get to the airport on time for your flight, the combination of Content + Context delivers a Connection between company and customer. It generates affinity, loyalty and ultimately profitability.

The Innovation Equation: Ideation x Execution = Value

Once you understand the goal state customer experience, there are bound to be gaps for two reasons. First, no company is perfect. So, whether due to legacy systems, suboptimal prior decisions or tactics, or some other reason, most have some gaps in capabilities. Second, even if you by chance have no gaps today, customer expectations are constantly rising and gaps will appear soon enough.

To close these gaps, we start with the relatively easy and fun task of Ideation. Brainstorming, thinking, riffing and imagining the future are fun activities. And more often than not, result in large numbers of possibilities (usually depicted by 100s of post-it notes covering conference room walls). Following ideation comes some sort of prioritization (e.g. dot voting) that results in a roadmap.

Now comes that hard part…Execution. Delivering on the promise of the future is a challenge because it requires changing the present while at the same time operating in the present. And when obstacles arise (which they will), many lack the resilience and confidence in their convictions to keep pressing forward. It is only through successful Execution on top of Ideation that significant Value (hence the multiplication) can be delivered.

Back in 1993, AT&T delivered some amazing Ideation. In their “You Will…” campaign, they asked these questions:

  • “Have you ever borrowed a book from 100 miles away from the library?”
  • “Have you ever crossed the country without stopping to ask for directions?”
  • “Have you ever sent someone a fax…from the beach?”
  • “Have you ever paid a toll without slowing down? “
  • “Have you ever tucked your baby in from a phone booth?”
  • “Have you ever opened doors with the sound of your voice?”
  • “Have you ever carried your medical history in your wallet?”
  • “Have you ever attended a meeting in your bare feet?”
  • “Have you ever watched the movie you wanted to the minute you wanted to?”

Each of these items have two things in common. First, we all utilize and enjoy all of them almost daily. Second, none of them were delivered by AT&T. They had great Ideation, but their Execution was flawed, incomplete or too slow. Hence the Value that we all derive from these experiences were ultimately delivered by others.

The Analytics Equation: Insight + Intuition = Improved Decisions

The primary purpose of analytics is to deliver Improved Decisions by increasing the decision makers confidence. This is achieved through identifying patterns in data to uncover anomalies or Insights that were previously unknown.

Insights must be both timely and relevant to the decision at hand. Yet even when this is achieved, we don’t yet get to optimal decision-making confidence. We must add Intuition, or as it is also known, experience or gut. There is value in experience. There is also value in gut, which brings elements of context, risk and strategy into the analytical equation. Given identical data, a more aggressive or conservative risk posture could lead you to different decisions – take the blackjack player who “feels lucky” and takes a hit on 16 when the dealer shows a 5 as an example. The player may have confidence in pulling a 5, though most analytical models would recommend staying. And regardless if the player wins the hand, they made a better decision by knowing the odds (data) and incorporating their feeling (gut) and risk posture (context).

So, when will we actually use these equations? Potentially daily, and often, multiple times each day. Consider the “Decision Modeling” approach below, that can be leveraged for both large scale strategic decisions as well as daily important operational decisions.

                                                                        “Decision Modeling”, ©Cherry Advisory, LLC

 

Start by identifying an Action (or Decision) that may help improve the customer experience, creating a Connection. Then acquire the data/information to uncover the Insights that will improve your decision-making confidence. Combine those with your Intuition to make a decision and set the course of action. Finally execute well, and you’ll realize the Value desired by your organization and required by your Customer.

So, in the end, there’s a fourth and final equation:

(Content + Context = Connection) +

(Ideation x Execution = Value) +

(Insight + Intuition = Improved Decisions)

——————————————————————–

= Customer Experience Success.

 

To become a more innovative leader, you can begin by taking our free leadership assessments and then enrolling in our online leadership development program.

About the Author

Dave brings over 20 years of strategic consulting experience focused on strategy (digital, customer experience, innovation) and advanced analytics. He has worked with and for leading organizations such as LBrands, Polo Ralph Lauren, ascena Retail Group, Journeys, DSW, Disney, Alliance Data, Nationwide Insurance, AEP, Huntington Bank, Cardinal Health, OhioHealth, Deloitte Consulting and Price Waterhouse. He holds a BS in Economics from The Wharton School at the University of Pennsylvania, serves on the International Institute of Analytics Expert Panel and also as an Advisory Board member for the Women in Analytics Conference and CbusRetail.

Contact Dave on LinkedIn at https://www.linkedin.com/in/cherrydave/ , Twitter @davecherry or check out his website: www.cherryadvisory.com.

Check out this and past episodes of Innovating Leadership, Co-creating Our Future, via iTunes, Google Play, TuneIn, Stitcher, Spotify and iHeartRADIO. Stay up-to-date on new shows airing by following the Innovative Leadership Institute LinkedIn.

 

Co-creating Our Future with Robots

This is a guest blog by Susan Harper as a companion to the Voice America interview with Dale Meyerrose, PhD, Redefining the Workforce: When Robots Pay Union Dues and Learn Too

 

Many of us have seen the futuristic movies so popular in our culture for decades like Star Wars, Star Trek, even the time traveling series Back to the Future.  In Back to the Future II, made in 1985, they predict what they believe the advances of technology will be in 30 years.  That was 2015 and is now 4 years in our rearview mirror.  Some advances we still haven’t managed, like the levitating car, but some we have so far outpaced that the movie producers never could have imagined the advances we have made in technology, such as the capabilities of the smart phone.

How do we harness that technology to reinvent our workforce and make our companies that much more efficient?  RPAs, Robotic Process Automation, give leaders the opportunity to approach their work force and identify the tedious tasks and then work to remove those tasks from their human work force and automate it.  This frees up the human work force to do the complex and meaningful work.

What does this look like? The challenge for leaders is to identify the highly cognitive and highly valued tasks that humans need to do and allowing technology to be used as a solution that can make up for gaps in the human workforce.

 

The benefits of implementing RPAs to complete work force tasks include:

  • they can work 24×7—continually perform without taking a rest,
  • they can be taught a myriad of tasks,
  • they can always be on call,
  • they work faster, longer, and make less errors than people on routine,
  • repetitive tasks and every action can be fully audited.

 

While implementing the RPAs leaders need to be mindful of the human workforce who are fearful of these digital workers.  Often human work force will believe that they’ll be replaced and lose their job, they are fearful of having to train and upskill in order to remain employable, they don’t understand how to leverage the bots and have a reluctance to learn.

 

How is this technology already being employed in our companies?  One of the biggest sectors is in the financial industry.  Credit card companies would never be able to use humans to process the millions of transactions that occur each day.  The RPAs are trained to look for inconsistencies in the charges and flag them for things like location, amount, or unusual patterns.

Another large sector utilizing the RPA technology is the health care industry.  They are being used in almost every aspect of the patient’s care. RPAs begin by assisting in scheduling appointments.  They can assist in finding treatments once a doctor has made a diagnosis.  They can ensure a schedule for a treatment plan is closely followed by setting up future appointments.  They are involved in the claims and billing process.  They can direct patient questions to the appropriate person.  They can manage and forward patient records.  This automation of tasks frees up the medical staff to do the tasks that require a human intervention.

The age of automation is here and how our companies use these technologies and innovate their businesses will determine the success of their businesses.

To become a more innovative leader, please consider our online leader development program. For additional tools, we recommend taking leadership assessments, using the Innovative Leadership Fieldbook and Innovative Leaders Guide to Transforming Organizations and adding coaching to our online innovative leadership program. We also offer several workshops to help you build these skills and system to create a regenerative, inclusive and thriving organization that will have a positive impact in the world.

 

 

Do Not Let Machine Learning Advances Outpace Your Organization

This blog a companion to the Voice America Interview on “Innovative Leaders Driving Thriving Organizations” with  James Brenza and Joe Hammond, founders of XDS on May 18, 2018, Machine Learning and Analytics: Case Study.  The blog is a guest post provided by James Brenza. James is the coauthor of the Innovative Leaders Guide to Implementing Analytics Programs.

The future of many industries and businesses is increasingly about data and how analytic models can increase agility, accelerate decision velocity, and improve outcomes. Whether you are working in retail, manufacturing, distribution, healthcare, financial services or public sector, you are probably already feeling the pressure. As the clouds are forming on the horizon are you, your leadership team, and your organization embracing this change?

The machine learning and artificial intelligence tsunamis are not about to arrive; they have already arrived. The effort to integrate data and develop analytic models has been compressed from weeks to hours. The effort to deploy models has been compressed from hours to minutes. Some of the most advanced firms are revising models intraday. The future of your organization and personal leadership is being measured by your ability to embrace and adopt the agility created by these technologies.

An entrepreneur’s perspective

As entrepreneurs, we have embraced this new reality into the fabric of our organization. As a team, we have aligned ourselves on customer centricity and agility. When we refer to customer centricity, we mean understanding their primary challenges and their barriers to adopting productive solutions. We accomplished this by listing all of our constraints and our customers’ constraints. We then systematically design and deploy solutions that step over those barriers.

Our focus on agility certainly applies to technology. All of our development is done in weekly sprints and two month iterations. This allows us to make small course adjustments very frequently to ensure we are being responsive. We can also adjust our strategic plan when better information becomes available. Beyond technology, agility also applies to how we run our organization. All initiatives and campaigns are managed with agile principles. We continuously test outcomes and adjust our course as needed. While a strategic plan is necessary, adaptability is the new key to survival. Through that lens, a major portion of our strategy is to remain agile and responsive.

The impact on analytic products

Our products and services are based on analytics. Many organizations have had analytic initiatives trudging along for years without significant benefits. Other organizations have tried to start for months without any demonstrable progress. Analytic agility has become the key to our success (and probably your future). We designed our solution architecture to embrace agility and continuous change. While we work predominantly with structured data (i.e., organized tables that contain billions of rows), our analytic model capability is completely agile, responsive, and based on machine learning. We have adapted to slices of data that can arrive periodically. Our models must adapt to every revision of these datasets. Rather than fight that reality, we designed our products to embrace it and take full advantage of our ability to respond quickly.

Recent transaction outcomes are treated as just one more data source with every model execution. This allows us to capture the very best outcomes from prior model executions as well as input from business experts. Since our machine learning engine is highly automated, it can build multiple models concurrently, select the very best features, create hybrid models, and allow experts to compare the model outcomes. This has reduced weeks of work to just hours. By continuously incorporating recent outcomes, we have integrated continuous change and learning. The future of automated machine learning is not on the horizon – it’s here and it’s now.

How can a leader respond?

  1. Embrace change as your primary link to surviving the future. We need to look beyond just revising business plans annually or quarterly. We need to evolve plans and develop products that learn and adapt continuously.

360 degree thinker

2.       List your barriers and have your team focus on removing them. If you put your barriers on a list in front of you (instead of letting them swirl in your head), you can attack them more vigorously. For every barrier you list, challenge yourself to list three creative solutions that let you step over that barrier.

unwaverin commitment

3.       If you and your team cannot overcome barriers, enlist external perspectives. The only shame is not enlisting assistance and allowing it to sink your ship in silence.

inntely Collaborative

4.       Create a culture that flourishes on innovation. We recommend creating a team that is dedicated to staying on your forefront, providing them with a collaborative environment, guiding them to the problem (without shackling their solutions), and injecting some impatience for solving problems. Hint: work in one-onth iterations to demonstrate small solutions quickly rather than allowing the problem to fester for multiple months.

professionally humble

5.       Make sure your personal leadership inspires a commitment to change. This needs to include both your external voice, internal voice, and observable actions. Your team will know you are sincere when you are interested and “in the game” with them.

inspire followership

Do those items sound like leadership platitudes? Here is the translation for getting into the continuous change analytics game:

  1. Create a one-line statement that declares how you will use analytics to guide your day-to-day business.
  2. Identify the barriers to that statement and list experiments to overcome them.
  3. Partner with an expert when your team cannot create a breakthrough in one month.
  4. Collocate your business and technical vanguard team. Let them focus on creating a single, demonstrable solution in one month.
  5. Remain visible to the team, set guardrails, support them, but do not micromanage them. They need to own their outcomes and learn through that process.

Embracing this new pace of change created by these technologies is going to be difficult. Ignoring it seals the fate of your organization. While you may not know all of the answers, you can create a culture and organization that will adapt and flourish.

To become a more innovative leader, please consider our online leader development program. For additional tools, we recommend taking leadership assessments, using the Innovative Leadership Fieldbook and Innovative Leaders Guide to Transforming Organizations, and adding coaching to our online innovative leadership program. We also offer several workshops to help you build these skills.

About James Brenza

James is an Information Technology and analytics leader with twenty years of diversified experience and success in delivering analytical, functionally rich, complex solutions. A hands-on leader that carefully balances strategic planning, business communications and technical delivery. Extensive experience with motivating mixed-shore teams to deliver high quality, flexible results.

The top 3 benefits James provides are strategically aligned solutions, cost savings and change leadership.

Specialties: Alignment of business and technology strategy, data analytics, business process improvement (Six Sigma and Lean), data management (data warehousing and business intelligence), program management, contract negotiations, traditional SDLC and Agile solution development.