Focus your Innovation on customer success, not just satisfaction


The single most important differentiating factor in the success of an innovation initiative is the user/customer insight, not opinions. Strive to make the customer successful, because what they are asking today may not be enough for them to be successful.

Focus your Innovation on customer success

Selfie from 2016

I was brought in to accelerate new product development in a Business to Business (B2B) scenario. The client created advanced materials for ICT sector. They had some rare talent and know-how but were struggling to compete on speed to market. Their material development cycle was typically 18-36 months, which was too long for their customer developing ICT hardware, which goes obsolete in 24-36 months. A simple discovery session into their sales process revealed the root cause. The Account Managers would wait for the Requests for Proposal (RFP) from the customer’s purchasing department. By then, it was typically too late to address the development cycle time. This client needed the ability to forecast their customer requirements at least a year ahead of the formal RFP in addition to accelerating the R&D activity.

Now, if you come to think of it, your customer just does not wake up one morning and issue an RFP. We all know, they work on it for a while! It is upon us to think like our customers or connect with them at their development roadmap level. So, we put an important new connection in place where the client’s R&D head would connect with the R&D head of the B2B customer to forecast their requirement, while the sales team tracked the RFP. Our client got the ability to deliver quality materials and gave them a competitive edge over their direct competitors, playing the speed to market game. On some specific items, they got exclusive development partnership programs to even offset part of the investment because of their unique engineering talent. Since then, we have successfully implemented this technique with a few other companies to build their innovation profile. It works.

Customer Insight

As Theodore Levitt said, People do not want a quarter-inch drill, they want a quarter-inch hole.”  Strategyn’s ‘Jobs to be Done’ Framework (Theory to Practice; Anthony W. Ulwick; Book; 2016) centers around the concept that instead of thinking about what features or benefits a customer would want to buy, an innovation should instead try to find out what job/activity/outcome a customer is trying to accomplish, and then develop something which helps them achieve that outcome.

Simply asking people what jobs they have is unlikely to result in any insightful answers, as people themselves often do not realize or cannot verbalize what they are trying to accomplish. What you need are insights, not opinions. You need a profound and unique knowledge about customer’s pain points and desirable gains. We should also consider the fact that often customers know what they do not want, even though they may fail to articulate what they want. For example, customers did not know they wanted Netflix, … they knew they did not want late fees and limited movies! Cry of the customer is a for of VOC.

Steps to Capture Customer Insight

Hopefully, you concur that you must aspire to understand what makes customers successful, not just satisfied. On many occasions, customers show requirements that are a level lower than what the problem they are trying to solve. Best practices include building a team of marketing and domain experts, reaching deep into the marketplace including customer’s customer, and gathering customer roadmap/intent, wherever practical. The steps below show various levels, providing progressively better insight.

  1. Conduct data research and analysis, using tools such as Google, Government databases, 3rd party research databases.
  2. Conduct discovery Interviews with standard questions, with a focus on listening rather than selling, getting to facts and not opinions, asking why?
  3. Shadow and observe customer actions, reactions, emotions, feelings.
  4. Immerse yourself in customer’s daily life, and make a note of your actions, reactions, emotions, feelings.
  5. Create a prototype or simulation and test your hypothesis or run the ‘What if’ conversation with customers.

More on Customer Insight

Customer insight is more than what product features or service performance the customers will receive during the transaction. It also involves delivery (how and where they receive it), consumption, and payment (how and when) aspects. Today, data is becoming a valuable commodity, and most of us do not keep it with us either. Online retailers are monetizing millennial’s desire to not go to the shop, whatever the product.

Customer insight is more than a process in the marketing department to get customer input. It is intertwined with ongoing company engagement cultural improvements, and the most vital part of any innovation culture.

As an example, look at the difference between the success of Sony’s Action Cam and GoPro action cameras. While Sony may deliver better quality videos, GoPro has been far more successful because it was designed to address customers’ desire to film themselves in action. By giving users ways to mount the camera on helmets, bikes, even on their dogs, and to rapidly edit and share footage, GoPro solved a real problem. It fulfilled a conspicuous customer desire and subsequently won massive customer market share (48 percent to Sony’s 8 percent in 2015, according to investment research and analytics company Market Realist. Robertson notes, Sony had every advantage in the marketplace, But GoPro started with what the customer wanted, and that’s how they came out ahead.

In Summary,

Customer insight means much more than what the customer is asking for. It means interpreting what they would be willing to pay for. It helps understand the consumer, so your innovation has a better chance of market acceptance.

If you like this blog post, you will like my book – “Inspiring Next Innovation Value Chain” available on Amazon.

If you wish to engage with me in a conversation, on this topic, please register for an online session on Feb 25, 2021 at 9AM ET co-hosted by Nerac.

Inspiring Next Purposeful Innovation

The Fourth Industrial Revolution has put innovation at the center stage of discussion across the world since 2015. We need an open mind and a suite of processes to develop, adapt, and apply digital technologies that are rapidly fusing with the physical reality. The global pandemic pushed everyone out of their comfort zone, providing a strong motivation to innovate. Every community scrambled to manage the health of the population, while trying to juggle the economic realities of social distancing. Creativity at home and innovation in the workplace witnessed enormous opportunities coming out of human survival instincts. The next few years will be an era for the innovator to bring a new normal to the world.

Structured Innovation is clearly the need of the hour. This brief article is synopsis of the first volume of a 4-Volume Book series on innovation, focused on Purpose (why). We will bring Portfolio (what), Profile, and mindset (how) in coming months.

Volume-1 Inspiring Next Innovation Purpose

Innovation and strategy are often mistakenly viewed as separate approaches, and I hear CEO’s saying “let’s get our strategy first, and then we will work on innovation.” That is as good a sign of an aging organization as any.  Leaders realize purposeful innovation ought to be the strategy, not just a keyword or an action item to support strategy. It is the way for an organization to be forward-looking and deliver true lasting value, besides financial responsibility and sustainability. Ray Stasieczko says, “Innovative organizations understand the importance of relevant products; while dying organization stay obsessed with selling the relevancy of their soon to be obsolete products.”

The purpose generally comes from the heart of the leadership, and it can be at various levels, broadly classified below:

Innovation Purpose

Financial Drive: Where the purpose is to provide enough sales and profit margins, to stay in business, and perhaps grow. I find this to be the lowest level of purpose, although mostly described, justified, and referred to under the context of Business decisions. I would prefer to call it merely an objective so you can exist for a larger purpose, … to create value in some form.

Technology Push (Industry 4.0): When the purpose is to successfully develop, leverage, enable, exploit the cyber-physical integration into process, product, service, or business application. It is OK to have a technology development as a defined purpose, but it makes a lot more sense to connect it with an impact on everyday living.

Social Pull (Society 5.0): When the purpose is to create a better life for human beings. This is the Japanese perspective and response to Germany’s Industry 4.0; Cyber-Physical-Human confluence to create a smart society. This is the onset of purposeful innovation and it now makes sense. Technology for the sake of technology or money only brings us halfway. Application for the benefit of humanity is where it ought to lead us.

Sustainability: This is where your purpose goes beyond humanity and addresses the sustainability of life on our planet for a long time to come. True sustainability requires a balance of economic, social, and environmental factors in equal harmony. Sustainable development is defined as ‘Development that meets the needs of the present without compromising the ability of future generations to meet their own needs.’

I submit that the purposeful innovation is the right way to go. The purpose around sustainable planet and smart society, through a balanced use of technology should be at the core of every business, community activity, and personal actions, while financial objectives are just a means to the end.  I also understand sustainability may not be your purpose. It is OK as long as it finds place in your strategy as a limitation or a constraint, and there is an appreciation of how your decisions might impact society of the planet.

If you are interested in learning more, please register for our webinar here.

If you wish to purchase our books, they are available on Amazon and Kindle worldwide; and all author royalties go towards ocean cleanup.

Learn more about InspiringNEXT Series

Ethics and NDE 4.0

Ripi Singh & Tracie Clifford

Sound of an Alarm

There are too many unknowns around explosive growth of Industry 4.0 technology applications, that it needs a hard conversation around ethics. The situation is particularly alarming as decision making shifts from humans to autonomous machines that can learn action but incapable of fear of penalty.

One of the aspects of any revolution is that innovation happens faster than laws and regulations needed to keep the business drivers in check, and particularly where there is no precedence to provide initial guidance. The graphic below depicts that dangerous zone, where on one is looking for general public.

Ethics and NDE 4.0

What is Ethics?

The field of ethics[1] (or moral philosophy) involves systematizing, defending, and recommending concepts of right and wrong behavior. Philosophers today usually divide ethical theories into three general subject areas: metaethics, normative ethics, and applied ethics.

Metaethics focus on the issues of universal truths, the will of God, the role of reason in ethical judgments, and the meaning of ethical terms themselves.

Normative ethics involve articulating the good habits that we should acquire, the duties that we should follow, or the consequences of our behavior on others.

Applied ethics involves examining specific controversial issues, such as abortion, infanticide, animal rights, environmental concerns, homosexuality, capital punishment, or nuclear war.

The topic of NDE 4.0 relates closely to Normative Ethics.

Proposed Ethical Principles for AI in NDE 4.0

The U.S. Department of Defense officially adopted a series of ethical principles[2] for the use of Artificial Intelligence on Feb 24, 2020 following recommendations provided to Secretary of Defense Dr. Mark T. Esper by the Defense Innovation Board in October 2019. These principles encompass five major areas: Responsibility, Equity, Traceability, Reliability, and Governance. Those recommendations came after 15 months of consultation with leading AI experts in commercial industry, government, academia and the American public that resulted in a rigorous process of feedback and analysis among the nation’s leading AI experts with multiple venues for public input and comment. We can adopt those to the NDE sector.

The adoption of AI ethical principles should align with the organizations growth, NDE digitalization strategy, and the lawful use of AI systems in host state/country. The adoption of AI ethical principles will enhance the organization’s commitment to upholding the highest ethical standards, while embracing the strong history of applying rigorous testing and validation of inspection technology innovations and methods. The proposed AI ethical principles should build on existing ethics framework in use within the organization and longstanding norms and values.

While the existing ethical frameworks provide a technology-neutral and enduring foundation for ethical behavior, the use of AI raises new ethical ambiguities and risks. These principles address these new challenges and ensure the responsible use of AI by the organization.

These principles will apply to both inspection and non-inspection functions and assist the organization in upholding legal, ethical and policy commitments in the field of AI.

The AI ethical principles encompass five major areas adopted from DoD and sixth one data specific to NDE data here:

Responsibility. NDE personnel will exercise appropriate levels of judgment and care, while remaining responsible for the development, deployment, and use of AI in NDE capabilities. [Notes: such as ASNT Level 3 is responsible for requirements, validation, and training, whereas a Level 2 can deploy it on qualified techniques]

Equity: The digital inspection system developers will take deliberate steps to minimize unintended bias in AI based NDE capabilities. [Notes: This includes development and training data. Training data should come from diverse users and decision makers, as supported by DEI expert. Refer to the section on bias for further details]

Traceability: The AI capabilities will be developed and deployed such that relevant NDE personnel possess an appropriate understanding of the inspection technology, development processes, and operational methods applicable to AI capabilities, including with transparent and auditable NDE methodologies, data sources, inspection procedure and documentation.

Reliability: The AI capabilities will have explicit, well-defined uses, and the safety, security, and effectiveness of such capabilities will be subject to calibration, validation, and POD assessment within those defined uses across their entire life cycles.

Governance: The digital inspection system developers will design and engineer AI capabilities to fulfill their intended functions while possessing the ability to identify and avoid unintended consequences, and the ability to disengage or deactivate deployed systems that demonstrate unintended behavior.

Data Management: The NDE personnel will honor the data acquisition, transfer, storage, analysis, processing, security, and ownership/sharing rights as determined by organizational policy and contractual obligations.

Call for Action

If you are working on autonomous machines with learning capability, please consider ethics seriously. What we have known and practiced up until now may not be adequate.

If you have an opinion on the content presented above, please engage in a conversation and lets us refine it together.

About Tracie Clifford

Tracie is Quality Manager, ANDE-1 Examination Center, Nondestructive Testing and QA/QC Programs, at Chattanooga State. She has over 30 years of experience in quality assurance and is a champion of training and certification programs in USA. She serves ANSI TAG-176 in development of ISO standards on quality terminology, quality systems, and quality technology.

[1] Internet Encyclopedia of Philosophy.

[2] DoD Adopts Ethical Principles for Artificial Intelligence; US DoD – Feb. 24, 2020.