Is AI a distraction???

AutomationI was recently in an exchange with a respected industry analyst where they stated that AI is not living up to its hype – they called AI ‘incremental’ and a ‘distraction’. This caught me a bit my surprise, since my view is that there are more capabilities and approaches available for AI practitioners than ever before. It may be the business and tech decision makers approach that is at fault.

It got me thinking about the differences in ‘small’ AI efforts vs. Enterprise AI efforts. Small AI are those innovative, quick efforts that can prove a point and deliver value and understanding in the near term. Big AI (and automation efforts) are those that are associated with ERP and other enterprise systems that take years to implement. These are likely the kinds of efforts that the analyst was involved with.

Many of the newer approaches enable the use of the abundance of capabilities available to mine the value out of the existing data that lies fallow in most organizations. These technologies can be tried out and applied in well defined, short sprints whose success criteria can be well-defined. If along the way, the answers were not quite what was expected, adjustments can be made, assumptions changed, and value can still be generated. The key is going into these projects with expectations but still flexible enough to change based on what is known rather than just supposition.

These approaches can be implemented across the range of business processes (e.g., budgeting, billing, support) as well as information sources (IoT, existing ERP or CRM). They can automate the mundane and free up high-value personnel to focus on generating even greater value and better service. Many times, these focused issues can be unique to an organization or industry and provide immediate return. This is not the generally not the focus of Enterprise IT solutions.

This may be the reason some senior IT leaders are disillusioned with the progress of AI in their enterprise. The smaller, high-value project’s contributions are round off error to their scope. They are looking for the big hit and by its very nature will be a compromise, if not a value to really move the ball in any definitive way – everyone who is deploying the same enterprise solution, will have access to the same tools…

My advice to those leaders disenchanted with the return from AI is to shift their focus. Get a small team out there experimenting with ‘the possible’. Give them clear problems (and expectations) but allow them the flexibility to bring in some new tools and approaches. Make them show progress but be flexible enough to understand that if their results point in a different direction, to shift expectations based on facts and results. There is the possibility of fundamentally different levels of costs and value generation.  

The keys are:

1)      Think about the large problems but act on those that can be validated and addressed quickly – invest in the small wins

2)      Have expectations that can be quantified and focus on value – Projects are not a ‘science fair’ or a strategic campaign just a part of the business

3)      Be flexible and adjust as insight is developed – just because you want the answer to be ‘yes’ doesn’t mean it will be, but any answer is valuable when compared to a guess

Sure, this approach may be ‘incremental’ (to start) but it should make up for that with momentum and results. If the approach is based on expectations, value generation and is done right, it should never be a ‘distraction’.


Lessons for IT services

handoffLast night, I went to a meeting of our local ham radio group and had a side discussion with another individual who also worked in the IT services space for decades. I was with Electronic Data Systems (EDS) for the majority of my career. He was with Perot Systems. We were comparing notes about what caused the demise of these organizations and came up with two main issues:

  • People are the service company – When HP purchased EDS or when Dell purchased Perot Systems, they both tried to use their deep product understanding in the services segment. For a product company, people are overhead, and the efficient generation of SKUs is king! For a service company, access to people is what you’re actually selling. In both cases, the HR organizations wanted to lower costs, so they initiated an early retirement offer that caused the flight of many of their senior, knowledgeable service personnel. Suddenly, they had customers screaming with no access to the depth of expertise they had relied upon. With nothing to sell, customer retention begins to spiral down, and costs go up. The exact opposite of what the leadership thought they were trying to do.
  • Value the difference – EDS in the late 90s was still organized by industry, leveraging support organizations for technologies. This was different than most IT service organizations, which were organized around services (like data centers or telecom) or individual customers. Customers were actually buying a relationship based on industry expertise — but it was difficult to compare between vendors.
    In 1998-9, EDS turned itself inside out, organizing around application development and maintenance, infrastructure, consulting…, with a leveraged industry-oriented, sales organization. Customers were initially happy, since they could see how much a network connection or support for a computer and OS cost.
    EDS also began to sell off many of the industry specific IP elements (e.g., financial systems, bank machines…). Though this action harvested cash, it began a spiral into ever more competitive commodity services, fueled by early cloud computing techniques that EDS instigated. Profitability and customer retention began a steady decline.

In both cases, the organizations were brought down by differentiators taken for granted. Once gone they were difficult to reproduce.

Service organizations need to really understand what makes their relationships sticky and view that difference as a strength, not as something too complex for the finance or HR organizations to understand. Unfortunately, hindsight is usually 20/20 and may be obvious. Let’s hope that DXC and NTT Data (who now own the remnants of EDS and Perot Systems) keep their eye on the ball.

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”

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…

IoT triggering some thoughts

A few weeks ago, I mentioned my initial foray into IoT for the home.  I now have my Ring Doorbell installed and a few Wemo switches.

It wasn’t hard to do and with IFTTT integration I can set up actions for numerous triggers like:

  • Turning on the lights at sunset
  • Log when someone comes to the door in a spreadsheet
  • Turn on the house lights when my phone is getting close to home
  • Use Google assistant to do a variety of things

My only complaint is that IFTTT is a bit slow in recognizing a triggering event (like motion) from the Ring doorbell. It takes a minute or more for the action to occur.

It is great that I can have my devices talk to each other, I just wish there was a bit more for them to say. A number of years ago I put together the following illustration:

IoT Value

It seems that IoT is like Metcalfe’s law for the internet:  the value generated is  proportional to the square of the number of connected devices in the system. The one thing that’s true though is that there are more devices with more interfaces all the time.

Shifting perspectives of value generation

resultsAs I was getting ready for the SAP conference this week, I listened to a speaker from Gartner discuss the Internet of Things. They went through the normal discussion about the number of devices, the need to use the data in new ways and then they said something that I’ve been saying for a very long time.

It is not about the things it is about the people.

I have another statement that is related.

It is not about the data it’s about the context.

Both of these perspectives are focused on the value side of what businesses are trying to do, not the technology side, still motivating so many in IT.

Last week, I was talking with a number of technologists who were enamored with problem solving — looking at new ways to address situations using technology. That’s great and a foundational element of any technical services organization, but it is not sufficient. By the time you may see the problem, the real opportunity may be lost. Today, organizations need to look deeper and not from a technologist’s perspective, but from the business. The CFO is likely to be the greatest ally to using technology for growth and impact. Organizations need to make the business case that they can internalize and the possibilities of Big Data, IoT, security and whatever is coming next will be realized.

There are software companies whose customers seem unwilling to take the next release (or worse uninterested). This is not an issue your typical sales person can address anymore. In today’s business, many clients are far into their internal sales process before their interest may even show up on the service or software sales organization’s radar. The context of their decision is developed through the organization’s social interactions and understanding of the business objectives. If organizations need to be “sold”, it is likely too late.

To address this, service and software companies need a real assessment of how these decisions are made (possibly by industry) and what capabilities will be impacting the value generation approach. They should float balloons of possibility early. Fund some projects that bring diverse perspectives together to see what other possibilities are out there. Just because your software has a feature map and investment plan, doesn’t necessarily mean that is it is actually used. Find those alternative perspectives and cultivate them.

We live in an unpredictable and ever changing world. Both the business leaders and technologists need to look for those serendipitous accidents that shift perspectives and buying behaviors. Make them happen.

Going to be at SAP SapphireNow this week

This is going to be an interesting week for me. Last month, the SAP media folks asked me if I’d be interested in covering SAP SapphireNow as a blogger. Since I didn’t really have anything better to do right now, I said ‘sure’. I’ve been to many a technical convention over the years, but this is the first time I’ve been to one by SAP and it definitely looks big.

I don’t think anyone will deny the importance of SAP as a software company. So I am definitely interested in their perspectives about the future trends of both business and technology. I’ll be looking for how they plan to address the current and upcoming shifts as well as shape demand and define new elements of business value today.

I hope to dig into their efforts with Big Data (HANA), the Internet of Things as well as what and how they can enable new approaches to business automation. One thing that surprised me about the invitation to attend was the lack of commitments on my part related to blogging… I guess they know if something interests me, I can’t help myself.

It should be an exciting week, since I’ll likely run into some folks that I’ve not seen in years and others I’ve talked with for over a decade and never actually seen – ever.