Technology
Blockchain, Data Governance, and Smart Contracts in a Post-COVID-19 World
The last few months have been very disruptive to nearly everyone across the globe. There are business challenges galore, such as managing large remote workforces – many of whom are new to working remotely and managing risk while attempting to conduct “business as usual.” Unfortunately, most businesses’ systems, processes, and internal controls were not designed for this “new normal.”
While there have been many predictions around Blockchain for the past few years, it is still not widely adopted. We are beginning to see an uptick in adopting Supply Chain Management Systems for reasons that include traceability of items – especially food and drugs. However, large-scale adoption has been elusive to date.
I believe we will soon see major shifts in mindset, investment, and effort toward modern digital technology driven by Data Governance and Risk Management. I also believe that this will lead to these technologies becoming easier to use via new platforms and integration tools, which will lead to faster adoption by SMBs and other non-enterprise organizations, and that will lead to the greater need for DevOps, Monitoring, and Automation solutions as a way to maintain control of a more agile environment.
Here are a few predictions:
- New wearable technology supporting Medical IoT will be developed to help provide an early warning system for disease and future pandemics. That will fuel innovations across industries, including Biotech and Pharma.
- Blockchain can provide data privacy, ownership, and provenance to ensure the data’s veracity.
- New legislation will be created to protect medical providers and other users of that data from being held liable for missing information or trends that could have saved lives or avoided other negative outcomes.
- In the meantime, Hospitals, Insurance Providers, and others will do everything possible to mitigate the risk of using Medical IoT data, which could include Smart Contracts to ensure compliance (assuming a benefit is provided to the data providers).
- Platforms may be created to offer individuals control over their own data, how it is used and by whom, ownership of that data, and payment for the use of that data. I wrote about this in 2013.
- Data Governance will be taken more seriously by every business. Today, companies talk about Data Privacy, Data Security, or Data Consistency, but few have a strategic end-to-end systematic approach to managing and protecting their data and their company.
- Comprehensive Data Governance will become a driving and gating force as organizations modernize and grow. Even before the pandemic, there were growing needs due to new data privacy laws and concerns around areas such as the data used for Machine Learning.
- In a business environment where more systems are distributed, the risk of data breaches and Cybercrime Increases. That must be addressed as a foundational component of any new system or platform.
- One or two Data Integration Companies will emerge as undisputed industry leaders because of their capabilities in MDM, Data Provenance and Traceability, and Data Access (an area typically managed by application systems).
- New standardized APIs akin to HL7 FHIR will be created to support a variety of industries as well as interoperability between systems and industries. Frictionless integration of key systems becomes even more important than it is today.
- Anything that can be maintained and managed in a secure and flexible distributed digital environment will be implemented to allow companies to quickly pivot and adapt to new challenges and opportunities on a global scale.
- Smart Contracts and Digital Currency Payment Processing Systems will likely be core components of those systems.
- This will also foster the growth of next-generation Business Ecosystems and more dynamic collaborations.
- Ongoing compliance monitoring, internal and external, will likely become a priority (“trust but verify”).
All in all, this is exciting from a business and technology perspective. Most companies must review and adjust their strategies and tactics to embrace these concepts and adapt to the coming New Normal.
The steps we take today will shape what we see and do in the coming decade, so it is important to get this right quickly, knowing that whatever is implemented today will live, evolve, and hopefully improve over time. Don’t wait for perfection, as the risks are too high.
Could this Pandemic Create New Business Opportunities?
Originally posted on LinkedIn.com/in/chipn
For most businesses, now is a time of caution and uncertainty. Mitigation and emergency planning are likely underway. The CDC has provided solid guidance, and new information is forthcoming daily. Communication Plans are being rolled out and revised as needed. Travel and meetings are being curtailed. Disruption may become the new normal for the next several months.
Alexander Fleming, the Nobel Prize winner who invented Penicillin, is quoted as saying:
“The unprepared mind cannot see the outstretched hand of opportunity.”
More people will be working from home, face-to-face meetings will be limited, large gatherings will be avoided, and travel to those meetings or gatherings. Working from home can be challenging for people not accustomed to it, so helping them transition may be very important to your financial bottom line.
Collaboration tools like Slack, Basecamp, and Asana can help maintain productivity and foster necessary interaction. Some tools include video conferencing; tools like Zoom or Webex can help internally and externally. Seeing the person you are speaking with increases engagement and leads to more effective communication by helping you spot nuances, such as facial expressions, that could otherwise be missed.
Secure, easy-to-implement tools (cloud-based solutions have an advantage here) that are easy to learn and use can be a cost-effective way to keep your business on track. Another benefit is building an effective distributed workforce.
But wait, there is more!
You may have important projects you can pull in and start now. That is another way to keep your teams engaged and focused. This could also be an opportunity to enhance skills with online training or research new technologies or business models.
This could also be a great time to buy and sell products and services. Business demands could temporarily decrease in many market segments.
- Sales organizations could use that opportunity to offer appealing deals to customers and prospects.
- Buyers could use their ability to purchase quickly to secure better deals during this lull in business.
Reasonable concessions can be mutually beneficial and a boon for both parties.
Negative events like a pandemic are not ideal and should not be taken lightly, but they can create opportunities to advance your business and position you for even greater success once the situation is under control. It is like that old saying, “When life gives you lemons, make lemonade.”
IoT and Vendor Lock-in
I was researching an idea last weekend and stumbled across something unexpected. My view on IoT has been that it provides a framework for a rich ecosystem of hardware and software products and their use. That flexibility and extensibility foster innovation, which in turn leads to greater use and adoption of the best products. It was quite a surprise to discover that IoT was being used to do just the opposite.
My initial find was a YouTube video about “Tractor Hacking” that lets farmers make their own repairs. That seemed like an odd video to appear in my search results, but it made sense about halfway through. The video discusses not having access to software, replacement components not working because they aren’t registered to that tractor’s serial number, and the only alternative being costly transportation of the equipment to a Dealership to have a costly component installed.
I initially thought there had to be more to the story, as I found it hard to believe that a major vendor in any industry would intentionally do something like this. That led me to an article from nearly two years earlier that contained the following:
“IoT to completely transform their business model” and
“John Deere was looking for ways to change their business model and extend their products and service offering, allowing for a more constant flow of revenue from a single customer. The IoT allows them to do just that.”
That article closed with the assertion:
“Moreover, only allowing John Deere products access to the ecosystem creates a buyer lock-in for the farmers. Once they own John Deere equipment and make use of their services, it will be very expensive to switch to another supplier, thus strengthening John Deere’s strategic position.”
While any technology – especially platforms – has the potential for vendor lock-in, the majority of vendors offer some form of openness, such as:
- Supporting open standards, APIs, and processes that support some degree of portability and third-party product access.
- Providing simple ways to unload your data in at least one of several commonly used non-proprietary formats.
Some buyers may deliberately implement systems that support non-standard technology and extensions because they believe the long-term benefits of a tightly coupled system outweigh the risks of being locked into a vendor’s proprietary stack. But there are almost always several competitive options available; always consider all viable alternatives.
Less technology-savvy buyers may never even consider asking questions like this when purchasing. Even technologically savvy people may fail to consider IoT as a key component of everyday tools and services – thus failing to recognize the implications of a closed system relative to their purchase.
It will be interesting to see whether deliberate business strategies like these change because of competitive pressure, social pressure, or legislation over the coming years. In the meantime, the principle of caveat emptor may be truer than ever in this age of connected everything and the Internet of Things.
Good Article on Why AI Projects Fail
Today I came across this very good article focused on lessons learned, which could help anyone interested in these topics. It included a good mix of non-technical problems.
This is the link to the article, along with my commentary on the Top 3 items listed: https://www.cio.com/article/3429177/6-reasons-why-ai-projects-fail.html
Item #1:
The article discusses how the “problem” being evaluated was misstated using technical terms. At least some of these efforts are conducted “in a vacuum.” Given the cost and strategic importance of getting these early-adopter AI projects right, that surprised me.
In Sales and Marketing, you start the question, “What problem are we trying to solve?” and evolve that to, “How would customers or prospects describe this problem in their own words?” Without that understanding, you can neither vet the solution initially nor quickly qualify the need for it when speaking with customers or prospects. That leaves room for error when transitioning from strategy to execution.
More collaboration with Business likely would have helped. This was touched on at the end of the article under “Cultural challenges,” but the importance seemed to be downplayed. Lessons learned are valuable – especially when you are able to learn from the mistakes of others. This should have been called out early as a major lesson learned.
Item #2:
This second area had to do with the perspective of the data, whether that was the angle of the subject in photographs (overhead from a drone vs horizontal from the shoreline) or the type of customer data evaluated (such as from a single source) used to train the ML algorithm.
That was interesting because assumptions may have played a role in overlooking other aspects of the problem, or the teams may have been overly confident they could get the right results with the data available. In the examples cited, those teams identified the problems and took corrective action. A follow-up article describing the process used to determine the root cause in each case would be very interesting.
As an aside, from my perspective, this is why Explainable AI is so important. Sometimes, you just don’t know what you don’t know (the unknown unknowns). Understanding why and on what the AI is basing its decisions should help provide better-quality curated data up front, as well as identify potential drifts in the wrong direction while it is still early enough to make corrections without impacting deadlines or deliverables.
Item #3:
This didn’t surprise me, but it should be a cause for concern as advances are made at faster rates and organizations race to be first to market with an AI-based competitive advantage, potentially with less validation than ideal. The last paragraph under ‘Training data bias’ stated that based on a PWC survey, “only 25 percent of respondents said they would prioritize the ethical implications of an AI solution before implementing it.“
Bonus Item:
The discussion about the value of unstructured data was very interesting, especially when you consider:
- The potential for NLU (natural language understanding) products in conjunction with ML and AI.
- This is a great NLU-pipeline diagram from North Side Inc. in Canada, one of the pioneers in this space.
- The importance of semantic data analysis relative to any ML effort.
- The incredible value that products like MarkLogic’s database or Franz’s AllegroGraph provide over standard Analytics Database products.
- I personally believe the biggest exception to this assertion will be GPU databases (like OmniSci) that easily handle streaming data, can accomplish extreme computational feats well beyond traditional CPU-based products, and have geospatial capabilities that add an extra dimension of insight to the problem being solved.
Update: This is a link to a related article that discusses trends in areas of implementation, important considerations, and the potential ROI of AI projects: https://www.fastcompany.com/90387050/reduce-the-hype-and-find-a-plan-how-to-adopt-an-ai-strategy
This is an exciting space that will grow significantly over the next 3-5 years. The more information, experiences, and lessons learned are shared, the better it will be for everyone.
One Successful Approach for Managing Innovation
When I owned a consulting company, we viewed innovation as an imperative. It was the main driver of differentiation, credibility, and opportunity. We had an innovation budget, solicited ideas from the team, and evaluated those ideas quarterly.
Almost as important to me was that this was fun. It allowed everyone on the team to suggest ideas and participate in the process. That was meaningful and supported the collaborative, high-performance culture that had developed. The team was inspired and empowered to make a difference, and that led to an ever-increasing sense of ownership for each employee.
The team also had a vested interest in having the process work, as quarterly bonuses were paid based on their contributions to the company’s profitability. There was a direct cause-and-effect correlation with tangible benefits for every team member.
We developed the following 10 questions to qualify & quantify the potential of new ideas:
- What will this new thing do?
- Be very detailed, as this was used to create a shared vision of success based on the presented idea.
- What problem(s) does this solve, and how so?
- This seems obvious, but selling this new product will be an uphill challenge if you are not solving a problem (such as “lack of organic expansion”) or addressing an immediate pain point.
- What type of organizations have those problems and why?
- This was fundamental to understanding whether a fix was possible from a practical perspective, what value that fix might have for the target buyer, and how much market potential existed to scale this new offering.
- What other companies have created solutions or are working on solutions to this problem?
- The lack of competition today does not mean you are the first to attack this problem. Due diligence can help you avoid repeating others’ failures by learning from their lessons and avoiding similar pitfalls.
- Will this expand our existing business, or does it have the potential to open up a new market for us?
- Each answer has upsides and downsides, but breaking into a new market can take more time and be more difficult, time-consuming, and expensive.
- Is this Strategic, Tactical, or Opportunistic?
- An idea may fall into multiple categories. When the Sarbanes-Oxley (SOX) Act became law, we viewed a new service offering as a tactical means to protect our managed services business and an opportunistic means to acquire new customers and grow the business. While this is not true innovation, it was an offering that flowed from this defined process.
- What are the Cost, Time, and Skill estimates for developing a Minimally Viable Product (MVP) or Service?
- What are the Financial Projections for the first year?
- Cost to develop and go to market.
- Target selling price, factoring in early adopter discounts.
- Estimated Contribution Margin Ratio (for comparison with other ideas being considered).
- Break-even point.
- Would we be able to get an existing customer to pre-purchase this?
- A company willing to provide a PO committing to purchasing the MVP within a specific timeframe increased our confidence in the idea’s viability.
- What are the specific Critical Success Factors to be used for evaluation purposes?
- This lesson learned over time helped minimize emotional attachment to the idea or project and provided objective milestones for critical go/no-go decision-making.
This process was purposeful, agile, lean, and fairly aggressive. We believed it gave our company a competitive advantage over larger companies that tended to respond more slowly to new opportunities and smaller competitors that did not want to venture outside their wheelhouse.
With each project, we learned, became more efficient and effective, and made better investment decisions that positively impacted our success. We monitored progress on an ongoing basis relative to our defined success criteria and adjusted or sunset an offering if it stopped providing the required value.
The process was not perfect…
For example, we passed on some leading-edge ideas, such as a “Support Robot” in 2003, an interactive program that used a pseudo machine-learning algorithm. It would be trained using historical log files, tested quickly and safely in a representative pre-production environment, refined as needed, and ultimately validated and rolled out.
This automation could have been used with our existing managed services and Remote DBA customers to further mitigate the risk of unplanned outages. Most importantly, it would have provided leverage to take on new business without jeopardizing quality or adding staff – thereby increasing revenue and profit margin.
At the time, we believed this would be too difficult to sell to prospective customers (“pipe dream” and “snake oil” were some of the adjectives we envisioned), so it appeared to lack a few items required by the process. Live and learn.
In summary, a defined approach to something as important as business needs innovation to grow and prosper, as best demonstrated by market leaders like Amazon and Google (read the 10-K Annual Reports to better understand their competitive growth strategies, which are largely based on innovation).
Implementing this approach within a larger organization requires additional steps, such as securing buy-in from a variety of stakeholders and aligning with existing product roadmaps, but it remains key to scalable growth for most businesses.
Where Ideas, Experiences, and Lessons Learned Intersect 