New Monthly Articles – AI, Data and Analytics Strategies
I published a new article on my CIO.com column in February. The main argument is that bias in AI algorithms can cause damage for enterprises. I compare it to the impact of data breach on an enterprise to make that point. Sure, you can argue about how they are different but that is not the point. Instead focus on the serious impacts of bias and how to prevent, detect and respond to it.
When we are struggling to adopt a new technology and deal with maturing it and growing our capabilities we tend not to focus on the risks until the damage is done. Data breaches are an example. We focused on collecting and using data to automate systems and expose them on the internet (and other IoT) and prioritized business and functional concerns at the expense of business risk management until too late.
I do post on my business site blog, Cloud Commmerce Consulting periodically as well. I hope you enjoy them and find value.
A Few Mega Sites Are Scooping Up Traffic Faster Than Web User Numbers
Quantcast.com’s Top Sites July 2017
A few sites including Twitter, Facebook, Amazon, Google, Yahoo, Microsoft’s sites, LinkedIn, eBay, Instagram are scooping up all the organic traffic leaving businesses more reliant on paid traffic (and these sites) for audience and survival.
You probably consider internet growth to be massive. That is true and Internet users numbers continues to grow but the growth in websites is even faster. In 1993 there were 108k web surfers for each web site. A decade later, 19 people for each website. Today there are fewer than 4 internet users for every site. Quantcast reports that the top 5 site get one billion monthly visitors a two billion visit the top 17 sites.
I hope stats like this are useful. But the critical issue is what should businesses who rely on traffic for revenue or leads do about this fact. This release focuses on the challenges facing B2B marketers in this age. I hope you find it valuable.
Startup Founders Sometimes Struggle to Transition to Growth Phase
I wrote my first article for Business.com 5 Reasons Promising Startups don’t scale. It was fun to write and I look forward to writing more. Writing is a great way to get your thoughts together on a topic.
In the article, I focus on the big transition a founder/manager needs to make to switch from startup to growth phase. Raising growth capital is your way of telling the world that you tested the market and have a solution to a need or problem. That is only true if dollars in can be converted into growth.
This phase requires all new skills and focus and the founder is expected to shift his or her own focus on a dime. This entails many things. The critical focus on the company is on marketing and sales activities. Marketing is critical to reaching the audience that you built the solution for.
Company operations need to change a lot too. The founder needs to empower his teams to become leaders and building a top notch management team that can stay aligns with strategy and execute are a critical test of leadership.
Another point I make is about getting better about performance management. Impressing the funder is the key to success but at scale this leads to odd behaviors, distorted incentives and bad execution.
Please check out the article and consider sharing it on your social platforms. Also send me any suggestions that you have for future article ideas.
Amazon’s Innovation Model is Fueled by Data and Computing Power
How is it that Amazon goes from ecommerce for books to being a dominant player in cloud computing, grocery delivery and so many other businesses.
It is wrong to look just at innovation or investments for the explanation. Amazon is a data-first company that invests big in analytics, machine learning and computing power. This creates a virtuous cycle that drives innovation in previously unexpected ways.
I hope this new post from Cloud Commerce Consulting adds some value.
I Was Accepted as a Contributor on Business.com
I like writing and do it for fun and because it helps me to think about topics from different angles. It is a little like walking a route for the first time instead of driving it. As you walk the route you notice things you didn’t previously. The slower journey makes you see details.
A joke. I haven’t seen a typewriter in years and am in no way nostalgic.
I have written a lot on LinkedIn and been happy with the response. I enjoyed it as well. Writing for Business.com is a bit of a departure. Their site emphasizes instructive content. The emphasis is to empower their readers to learn how to do something. I typically have written about technologies, trends or news. This will be a bit of a new direction for me.
I am looking forward to pitching some new ideas. I may stick to startups or technology tips for business owners. That takes some thought.
My first article was accepted and is in the publishing queue. I will share it online when it goes live. I am already thinking about additional topics
July Release is a Great Accomplishment For Our Teams
The Completed.com has done a great job of navigating the trials of the startup world. The team started off with a great R&D project to rethink the traditional processes of user generated reviews. From there they built a great prototype and an extensible framework that helped us get some market validation and raise seed funds.
At this stage we really started to think about the features and usability and this led us to rethink the original code base. This meant a lot of rearchitecting and refactoring. We added some additional new technical talent and UX expertise and set out to rethink the user experience.
Now in July the teams are nearing a series of releases to launch that will change Completed.com both above and below the surface. But what won’t be visible on the screen is all the work then went into maturing the processes, the late nights and the hard work. So when we celebrate this team’s accomplishments, there is a lot more to be proud of than you can see.
An Introduction to Key AI Technologies
I wrote a primer for executives to understand AI terms. For a quick overview of the key terms…
Natural Language Generation refers to using data to generate text
Hardware with Integrated AI such as GPUs or integrated AI appliances used in entertainment and gaming but with the ability to massively accelerate machine learning processing
Deep Learning Platforms is used for pattern recognition or classification
Decision Management or EDM/BDM is for optimizing operational decisions
Machine Learning Platforms are used in applications to predict outcomes or classify things
The Widening Gap Between Business and Data Threatens Traditional MBAs
I recently published a LinkedIn post on an MIT Sloan article that argues there is a growing gap between our capability to great new insights and the capability of managers to apply these insights in meaningful ways. A critical argument by the author of the original post is that managers need to understand AI better. That way managers can intelligently utilize the outputs but not blindly rely upon them. I have said that I agree that implementing AI will be a requirement to keep up and new winners in every space will come from new strategies that fully leverages AI/Big Data/Analytics. That may become the most critical source of innovations for years to come.
So let’s say you buy the premise. If AI will revolutionize finance and marketing and so on then it is the people that know how to leverage the technology best and really get the most from the opportunity that will rise to the top. That means that the top business positions will require some degree of data science. That means it is time to rethink business education. Below is the current required curriculum for the Harvard Business School MBA program. This is not a criticism that colleges are too ivy tower. Schools do make an effort to be adaptable to changes in business and a few examples exist below with many, many more in the list of electives. The issue is that the fundamental goal of business schools has not changed. We are still trying to teach general business skills to students. As a result they cover a broad range of skills like finance, strategy and marketing.
The MS/MBA From Harvard Combines Business & Technical Skills
The opposite viewpoint does have a lot of adherents too. Here is a post that argues that AI will eliminate the need for data scientists because we will just use it as a tool to do all that complex stuff. It is an interesting argument that I don’t agree with and I will articulate more why later.
My argument is that business leadership does require people to understand data, analytics and machine intelligence and automation. Perhaps the future of business education is a blend of what we teach today with business intelligence and data science. Take a look at the required coursework at for the Harvard MBA and MS in data science programs and see if we are not creating gaps between them. To its credit, Harvard has created a joint MS/MBA program that blends the two. I think this may be the single most valuable degree on earth. So is this the future of business education and will traditional MBA’s be left behind?
The Harvard Business School – MBA Required Courses
Financial Reporting and Control (FRC)
Leadership & Organizational Behavior (LEAD)
Technology & Operations Management (TOM)
RC Startup Bootcam
Business, Government, and the International Economy (BGIE)
The Entrepreneurial Manager (TEM)
Leadership and Corporate Accountability (LCA)
FIELD Global Immersions: Global
Harvard Paulson School of Engineering & Applied Science – Master of Science in Data Science Required Courses
Data Science I
Data Science II
Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference, and Optimization
Systems Development for Computational Science
One semester of the new Critical Thinking and Data Science course
At least one research experience. This requirement can be satisfied by the AC 297r Capstone project course or a semester-length independent study project
Social Media Platforms vs. Business Profile Sites
Working on strategy for Completed.com I have spent a lot of time studying other services. Viadeo is an interesting one. There are a lot of interesting models out there. One way to look at them is from the perspective of user acquisition. Sites like Facebook and later LinkedIn got very good at network effect. Profile sites often have to rely on organic search and other traffic sources. This seems to be an inherent disadvantage. In general, models that rely upon organic traffic sources other than network effect seem to have a maximum potential.
I have been focused more on fundraising this year. I found the results of the Journal of Financial Economics outlines how Amazon Web Services has made it easier to launch startups. I completely agree. But with everything, there are unintended consequences which includes higher failure rates as ‘B’ round funding has not increased similarly. This post on Cloud Commerce Consulting’s website offers more details.