An article on the negative side of gamification

Back when I worked in HP labs, one of the areas I focused some attention to was gamification. In a recent article in Fast Company they looked into the dark side of gamifying workAnother interesting article was in the January 2012 issue of Wired titled The Curse of Cow Clicker.

For me, the simple definition of gamification is “Metrics-based behavior modification” or using game mechanics to influence real-world behavior. Some view this as a way to improve the worker experience for business functions, while others view it less positively as “exploitware”. We see it all around us in healthcare, retail and new areas all the time.

You may wonder “Can sitting on a help desk and answering calls from consumers be turned into a competitive game that improves the experience for everyone?” — it turns out it can. Many activities can be tracked, rewarded and tuned to the needs of the day. People respond when you give “points” for things like “resetting passwords”, “resolving install problems”… as long as the points mean something to the individuals doing the tasks.

Human behavior can be manipulated by just pulling on a few of the right strings. This is one way companies can tap into the streams of data and the inherent human intellect in their business to drive value. Businesses just need to listen and invest in understanding what drives those they want to influence and define systems to meet that unspoken need. One key though is to not make it so blatant that those involve feel manipulated.

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Is automation forcing divergent paths of quality vs. cost?

robots-too-humanI saw an interesting post: When Robot Writers Take Over, Will Freelancers Be Obsolete? The article was focused on freelance writing, but it did make me wonder about the whole concept of freelancing, in general.

The relatively fixed and easy to automate positions in many fields are ripe for automation. Those that require creativity or unique insight should be safe for a long time to come. In fact, automation could make the freelancers life less mundane and more interesting. It reminded me of a situation earlier in my career…

Back in the early 90s, I worked in the AI space for Electronic Data Systems (EDS). We focused primarily on solving problems for GM and the US government. Somewhere around here I have a coffee cup with the moto of the group: “Make it Work, Make it Real”. Unfortunately, the folks working in the group had felt it really meant that if we could make it work, it wasn’t really AI — since someone would always say that it was just regular old programming, no matter what innovative technique or esoteric language we used.

One of the projects I led was called Knowledge-based Tool Design. We were trying to automate tooling design for clamping and welding car parts using CAD techniques, a project far ahead of its time. Programmatically determining the right type of clamp and the correct way to swing it into place was too difficult spatially, for the time. We just didn’t have the compute power and the algorithms determine orientation and approach. A good human tool designer could see the solution intuitively.

We did figure out that people are not good at pulling together the bill-of-materials to ensure that the clamp and all the hydraulic and mounting components… were defined. We shifted our attention to defining that type of detail using computers — reducing the errors and rework later in the process.

Similarly, in other industries, there are so many annoying and resource intensive, low hanging fruit to be picked that the return on investment for tackling truly intuitive problems just isn’t there. That can all change though as better algorithms and computing capabilities develop.

There are a couple of ways this could go:

  • The intuitive functions will likely become more of a freelance function, since companies will not need (or be willing to pay) for those expert roles all the time and the work will be interesting.
  • The focus shifts to less high-quality designs that can be automated.

In any case, employment as we know it will be changing.

What’s the real outcome of Salesforce’s AI predictions?

automated decisionsYesterday. I was catching up on my technology email and came across this post stating that Salesforce now powers over 1B predictions every day for its customers. That’s a pretty interesting number to throw out there, but it makes me ask “so what?” How are people using these predictions to make greater business impact.

The Salesforce website states:

“Einstein is a layer of artificial intelligence that delivers predictions and recommendations based on your unique business processes and customer data. Use those insights to automate responses and actions, making your employees more productive, and your customers even happier. “

Another ‘nice’ statement. Digging into the material a bit more Einstein (the CRM AI functions from Salesforce) appears to provide analysis of previous deals and if a specific opportunity is likely to be successful, helping to prioritize your efforts. It improves the presentation of information with some insight into what it means. It appears to be integrated into the CRM system that the users are already familiar with.

For a tool that has been around since the fall of 2016, especially one that is based on analytics… I had difficulty finding any independent quantitative analysis of the impact. Salesforce did have a cheatsheet with some business impact analysis of the AI solution (and blog posts), but no real target market impact to provide greater context – who are these metrics based on.

It may be that I just don’t know where to look, but it does seem like a place for some deeper analysis and validation. The analysts could be waiting for other vendor’s solutions to compare against.

In the micro view, organizations that are going to dive into this pool will take a more quantitative approach, defining their past performance, expectations and validate actuals against predictions. That is the only way a business can justify the effort and improve. It is not sufficient to just put the capabilities out there and you’re done.

It goes back to the old adage:

“trust, but verify”

Simplicity, the next big thing?

Complex processRecently, Dynatrace conducted a survey of CIOs on their top challenges. Of the top six, almost all deal with concerns about complexity. There is no doubt there are numerous technologies being injected in almost every industry from a range of vendors. Integration of this multivendor cacophony is ripe with security risks and misunderstanding – whether it is your network or IoT vendor environment.

Humans have a limited capacity to handle complexity before they throw up their hands and just let whatever happens wash over them. That fact is one of the reasons AI is being viewed as the savior for the future. Back in 2008, I wrote a blog post for HP that mentioned:

“the advent of AI could allow us to push aside a lot of the tasks that we sometimes don’t have the patience for, tasks that are too rigorous or too arduous.”

IT organizations needs to shift their focus back to making the business environment understandable, not just injecting more automation or data collection. Businesses need to take latency out of decision making and increase the level of understanding and confidence. A whole new kind of macro-level (enterprise) human interface design is required. Unfortunately, this market is likely a bit too nebulous to be targeted effectively today other than through vague terms like analytics…  But based on the survey results, large scale understanding (and then demand) appears to be dawning on leadership.

The ROI for efforts to simplify and encourage action, should be higher than just adding a new tool to the portfolio ablaze in most organizations. We’ll see where the monies go though, since that ROI is likely to be difficult to prove when compared to the other shiny balls available.

Six thoughts on mobility trends for 2018

mobility walkLet’s face it, some aspects of mobility are getting long in the tooth. The demand for more capabilities is insatiable. Here are a few areas where I think 2018 will see some exciting capabilities develop. Many of these are not new, but their interactions and intersection should provide some interesting results and thoughts to include during your planning.

1. Further blurring and integration of IoT and mobile

We’re likely to see more situations where mobile recognizes the IoT devices around them to enhance contextual understanding for the user. We’ve seen some use of NFC and Bluetooth to share information, but approaches to embrace the environment and act upon the information available is still in its infancy. This year should provide some significant use cases and maturity.

2. Cloud Integration

By now most businesses have done much more than just stick their toe in the cloud Everything as a Service (XaaS) pool. As the number of potential devices in the mobility and IoT space expand, the flexibility and time to action that cloud solutions facilitate needs to be understood and put into practice. It is also time to take all the data coming in from these and transform that flow into true contextual understanding and action, also requiring a dynamic computing environment.

3. Augmented reality

With augmented reality predicted to expend to a market somewhere between $120 and $221 billion in revenues by 2021, we’re likely to see quite a bit of innovation in this space. The wide range of potential demonstrates the lack of a real understanding. 2018 should be a year where AR gets real.

4. Security

All discussions of mobility need to include security. Heck, the first month of 2018 has should have nailed the importance of security into the minds of anyone in the IT space. There were more patches (and patches of patches) on a greater range of systems than many would have believed possible just a short time ago. Recently, every mobile store (Apple, Android…) was found to have nefarious software that had to be exercised. Mobile developers need to be ever more vigilant, not just about the code they write but the libraries they use.

5. Predictive Analytics

Context is king and the use of analytics to increase the understanding of the situation and possible responses is going to continue to expand. As capabilities advance, only our imagination will hold this area back from increasing where and when mobile devices become useful. Unfortunately, the same can be said about the security issues that are based on using predictive analytics.

6. Changing business models

Peer to peer solutions continue to be the rage but with the capabilities listed above, whole new approaches to value generation are possible. There will always be early adopters who are willing to play with these and with the deeper understanding possibilities today new approaches to crossing the chasm will be demonstrated.

It should be an interesting year…

HaloLens – my interest is peaked

Augmented reality has always interested me and I finally got around to signing up for Microsoft’s HaloLens community. I used to do quite a bit of work with Microsoft (somewhere around here I have a crystal cube for the ‘lasting contributions’ to Visual Studio 2005) but I’ve not exercised those skills in a while – so HaloLens seemed like an ideal opportunity.

The hardware shown looks powerful and flexible. I’ll need to come up with some use cases that can exercise its capabilities. I am sure that somewhere between ham radio, data analytics, 3d printing and my other interests there must be something.

Unfortunately, it is unlikely that I’ll make it to a build event but hopefully I’ll get my hands on one somehow.