Companies in Chaos

If you walk into any large corporation that produces goods and ships them around the globe you will find the thousands of planners and operators that run their supply chain in chaos, simultaneously burdened by the technology that was supposed to save them and jaded by the mundane aspects of their jobs.

Despite most companies’ sophisticated and expensive planning and operations process software, dealing with probabilistic variation across demand and supply still requires a tremendous amount of human judgement in the form of (seemingly endless) spreadsheets and meetings. Planners get hundreds of thousands of alerts from their planning system every week – handling them manually is a Sisyphean task. They attend thousands of meetings and often courageously attempt to field the noise across silos. None of the technologies they currently have in place to help are particularly useful in amplifying their human potential, let alone helping the company predict and creatively shape what’s next.

I’ll tell you a secret: many people are operating this way; it’s the crisis of modern work.

For most of us living in a state of constant DRIP (data rich, information poor environments), the constant barrage of incoming information, all of it requiring human judgement and decisions, has become a grind.

But it doesn’t have to be that way. What if we used artificial intelligence to make sense of the very technology that is getting in our way? What if, instead of using AI to replace humans, we use it for what it’s best at: to automate the mundane and allow humans the time and space they need to solve the creative challenges that push society and business forward?


Where it went awry

Automation was never intended to replace the worker, only to free her up to be more creative. Business to business software took a wrong turn away from this goal sometime in the 80s, when Apple went after the consumer market and Microsoft went after the enterprise. In the enterprise, because the buyer of software was not the user, the user experience was overlooked. This is also true of ERP systems; they followed suit.

In fact, the history of enterprise apps is a push model. Ever-more complex spreadsheet apps push information at employees, creating the need for more and more information management. On the other hand, consumer software pulls them in, immersing them in game-like experiences.

The enterprise has forgotten the principle of ontological design: that the environment you design designs you back. What you design can evoke moods. Design a dumb system, you are creating a dumb workforce.

This is why the state of employee disengagement globally is appalling and getting worse. This year’s Gallup study showed 72% of workers are disengaged, costing companies $450-550 billion. How is a company supposed to succeed, especially in a complex, constantly creative environment, when it is effectively working with only 28% of its workforce?

No wonder there’s a real fear that artificial intelligence could worsen this situation.

AI as the Solution

We can use AI to fix this epidemic of disengagement by making workplace tools as engaging as the games on our mobile devices. We can use it to put the “flow” back into the enterprise workflow and make business as immersive as a video game. Now is the time to do it as a new generation enters the workforce and the institutional knowledge of the Baby Boom generation is on the way out.

It’s possible, if we re-design the digital environment so the actual design of the software elicits the best behavior from its users. In that way, we are also redesigning the fabric of work to turn up the level of engagement. That’s true design thinking.

Suppose you are a 25-year-old new hire and you’re not sure how to do your job. You’re anxious about making a mistake, so you make as few decisions in as narrow a space as possible. But we don’t want this new hire to do less, we want to amplify this 25-year-old with all the tools he needs to make him successful so he can do more, turning his creativity on rather than off.

The pain of all these large, existing business planning applications is that they shove methods down a new hire’s throat that don’t fit. He doesn’t start his job at the right level for his abilities, he starts it at the level the software delivered it to the last guy, who had been there for 20 years and knew this job cold. The new guy gets anxious. That’s why workers are rarely in flow at work.


“Of all the virtues we can learn, no trait is more useful, more essential for survival, and more likely to improve the quality of life than the ability to transform adversity into an enjoyable challenge.”

Mihaly Csikszentmihalyi, Flow: The Psychology of Happiness

Designing WorkFLOWs to go VIRAL

Instead, in our pull-based model, the next generation interface will create viral workflows, flows that are immersive and delightfully addicting. What do we mean by viral, and what does an employee need to get into flow?

V First, she needs visibility. Show her what is coming leveraging predictive modeling techniques that allow for de-noising signals and providing early planning visibility into upcoming events and trends both for the Hierarchical Demand and inbound Supply Risks

I Then, she need insight. Don’t just give her alerts, tell her what they mean and show her what to do. But don’t just stop there.

RA Give her a response action recommendation about what to do next. Example? Swap product from Mexico.

L Then let AI incorporate what she has learned from this situation, so she won’t see this problem again, or so she can repeat her success. At present, all that learning is in the heads of other employees, turning into gut feeling or cognitive bias. But that doesn’t help this woman improve, innovate, or create.

Through machine learning, we can create a systematic layer that can learn based on every cycle that runs. Our tools spot internal patterns, enrich them with external data, record them, and automate responses.

With this VIRAL design, we can draw workers into the same state of flow that gamers are in, making their work irresistible. By automating responses and reducing complexity, we move the worker’s skill level to the right, get his anxiety to decrease and get him and his colleagues into the state of flow.

Photo by Ryan Vitter on Unsplash


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