I recently posted from a Steve Jobs Interview his views on process versus content. He clearly said that the process is the problem, while content is the key. I feel that such successful people are the ones who should be our role models and not some ‘process expert’ or professor who never had to run a business by himself.

Frederic Filloux in his recent Monday Note post pointed me to Jeff Bezos 2016 shareholder letter. Jeff Bezos, the similarly charismatic CEO of Amazon discussed many of the subjects that the process community are targeting. They won’t like what he has to say.

True Customer Obsession

Jeff Bezos: “There are many advantages to a customer-centric approach, but here’s the big one: customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf. (…)
[Y]ou, the product or service owner, must understand the customer, have a vision, and love the offering. Then, beta testing and research can help you find your blind spots. A remarkable customer experience starts with heart, intuition, curiosity, play, guts, taste. You won’t find any of it in a survey. (…)
Good inventors and designers deeply understand their customer. They spend tremendous energy developing that intuition. They study and understand many anecdotes rather than only the averages you’ll find on surveys. They live with the design.”

Resist Proxies

Jeff Bezos: “As companies get larger and more complex, there’s a tendency to manage to proxies. (…) A common example is process as proxy. Good process serves you so you can serve customers. But if you’re not watchful, the process can become the thing. This can happen very easily in large organisations. The process becomes the proxy for the result you want. You stop looking at outcomes and just make sure you’re doing the process right. Gulp. It’s not that rare to hear a junior leader defend a bad outcome with something like, “Well, we followed the process.” A more experienced leader will use it as an opportunity to investigate and improve the process. The process is not the thing. It’s always worth asking, do we own the process or does the process own us?”

On Machine Learning

Jeff Bezos: “These big trends are not that hard to spot (they get talked and written about a lot), but they can be strangely hard for large organisations to embrace. We’re in the middle of an obvious one right now: machine learning and artificial intelligence.(…)
But much of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.”

My Perspective on the above

I have voiced similar opinions for many years and was often ridiculed by process experts for not falling in line. Yes, I am no Jeff Bezos but reasonably successful nevertheless. As I recently emailed to another manager: “Success comes with people, passion and ingenuity.” Clearly Jeff Bezos is making exactly these points in the above.

If you want to be successful you need to put people before numbers, passion before process, and make sure that the ingenuity does not interfere with or replace both as is currently targeted both with process management and machine learning. Both should be augmenting what people do and help them to make faster and better decisions, but never consider to substitute the human aspect of doing business.

Let me also add that Jeff Bezos is right that Machine Learning (ML) is a complex subject when viewed as an add-on to a current software portfolio. That is not the case if it is integrated into the software platform. Papyrus Software started to provide ML functionality in 2009 as part of its platform with the User-Trained Agent (UTA). There is no AI knowledge required and there is no need for experts who will manage the data. The core functionality of the Papyrus UTA is to learn from the users or customers which actions (Best Next Actions) are the right ones for a particular work scenario and data pattern.

While this may seem to ‘experts’ that this is a simplistic approach to AI or ML, it actually is not! It does not matter what complexity you add or pursue with ML functionality, you always try to figure out what to do next from past data. Which means that the UTA identifies what actions people took in the past based on prevailing data patterns. This includes decision-making as a whole, regardless of who at which level in the hierarchy took the decision to perform a particular action. So it is not simplistic, but simply to the point! Past data do not predict the future, but decision-making based on human experience is the best possible input we can get for future decisions.

So we make it easy for large corporations to get into AI without a huge investment into software or skills.