As machines get smarter, will jobs become increasingly scarcer?  That’s the fear of many, including some economists.  And while yes, some jobs will be lost, those with the right skills will partake of the silver lining of smarter machines and the future of artificial intelligence.  According to an article in the April 30th issue of The Wall Street Journal, AI “opens up opportunities for many new jobs to be created — some that we can imagine and many we probably can’t right now.”

For those who tool up, the Journal expects the following list of jobs to be among those that will benefit from our smart new future.

  1. AI Builder. Case in point: iRobot, a maker of robotic mops and vacuums has quadrupled its staff of software engineers focused on consumer robots, making robots smarter through advanced AI and computer-vision systems.  Many of these are Ph.D.-level scientists, so they’re certainly not Everyman-style jobs, and so the company has expanded its talent search to a global effort.
  2. Customer-Robot Liaisons. People are going to need help easing into working with robotic systems, and this role is currently among the most sought-after AI-related positions according to jobsite ZipRecruiter.  Ensuring clients are happy with robots that have been rented out as security guards on a graveyard shift is the job of one 36 year-old at Palo Alto’s Cobalt Robotics.  The trick, they say, is to get a “good handle” on how comfortable clients are interacting with robots by monitoring usage reports, interacting with customers through calls, texts and visits, and (what else?) building relationships.
  3. Robot Managers. While robots can be amazingly smart, their judgment and the judgment within the AI realm generally, is lacking when compared to humans. Ditto for empathy, customer relationships and a myriad of other soft skills.  The need for human oversight might be the most underestimated part of all according to one McKinsey partner who focuses on automation.
  4. Data Labelers. For AI to understand the world, it needs humans to explain what things are. That means labels.  Identifying objects in images or parsing sentences may be things we humans take for granted, but robots will need our help.  Self-driving car developers, for instance, can have hundreds of folks labeling data.  Sometimes it’s simple, sometimes it’s subtle.  Posters and pictures around an office may seem like trespassers to a robot, and they need to be ‘taught’ that these are not potential threats.
  5. Drone Performance Artists. Drones are becoming more and more a fixture in the film world, flying props, handling lighting and providing overhead shots at sporting events.  Artists who can customize them to suit the needs of different performances like concerts, musicals, circuses and sporting events are increasingly in demand.  Said one such artist, “It’s a crazy opportunity because I have a blank slate and can develop whatever I want this field to be.”
  6. AI Lab Scientists. Smart software is remaking drug development, sifting through vast troves of data faster than humans to come up with new directions for medical research.  Data scientists like computational biologists can help AI systems learn so that computers can surface novel ideas, with human technicians also testing the AI results to see which are valid and which are not.  The feedback they give AI machines only serves to make them smarter.
  7. Safety and Test Drivers. Self-driving vehicles are not there yet, in the opinion of industry insiders, but they are expected to spread slowly across the automotive landscape.  That provides opportunities for people to help the vehicles do their jobs safely, and take over when necessary.  Testers today provide feedback to manufacturers when a vehicle encounters a situation it’s unsure how to handle.  One company doing so is tripling its number of testers, and hiring test engineers to devise scenarios for shuttles, not to mention maintenance, testing and cleaning crews.

Reporting and business intelligence can both be of critical importance to a company today.  After all, it’s often said that in the past we adopted technology to aid the business (or perished along the way), whereas today, we are all technology companies.  So let’s take a quick look at a few key distinctions between these two entities.

A Washington D.C. company called T3 Information Systems offers the following two definitions which seem to fit the bill nicely:

Reporting refers to an account or statement that describes in detail an event or situation. The purpose of reporting is to give a detailed status update of a situation.

Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better decision-making in business.

Reporting is mostly concerned with what happened in the past (recent or otherwise) or with the current status of things (i.e., sales, receivables, inventory).  Aging reports, sales analyses, customer ledgers and income statements are examples of reporting.

Business intelligence, on the other hand, is concerned with what has happened so far, or what exists in our repositories of data, that can be used to effect and improve future business performance.

3T explains BI simply as… Business Intelligence is built using multiple sources of data, giving the user the ability to cross-analyze and explore relationships that may not have been previously considered. The main goal of BI technology is to be flexible and open to discovering new insights.

An easy-to-understand example of a real-life business intelligence situation would be discount cards. Stores use discount cards to track customer purchases and targeted marketing campaigns. Business intelligence then analyzes and explores this data to inform future decisions.

In short then, business reporting is about status updates, past and current.  BI is about making future decisions. They involve different tools (a topic for another time) provided by an ever-increasing range of software vendors.  In some respects, it’s fair to say that one is intended to pick up where the other leaves off.

Yet you need both — eventually.  It’s just important to recognize the distinctions, and to decide for yourself when you need more than just reporting.  Then you can start exploring your options.


A lot of companies’ ERP projects run longer and cost more than originally expected.  If you’re among them, you’re not alone.  A recent state of ERP report for 2018 from Panorama Consulting confirms with most ERP providers have long known: a few key project drivers make all the difference.

Panorama points out that nearly two-thirds of companies spent more than budgeted on their ERP projects in 2018 nearly 80% took longer than expected (we suspect the other 20% were lying or misinformed).

The report drew five key conclusions regarding the factors that matter when it comes to mitigating time and cost overruns.  They included:

  1. Setting a clear alignment between the ERP project and the organization’s overall business strategy. They give the example of the company who stated business transformation effort was aimed at leveraging technology to surpass its competitors.  Their main goal was to improve customer service.  But their implementation was more focused on using tech to improve and streamline back office functions.  Nothing wrong with that, mind you; it’s just that you can expect a longer timeline and deeper budget when your priorities are allowed to shift in this fashion mid-project.  Keep your eyes on the prize.
  2. Establish clear expectations during planning. “When expectations aren’t aligned with reality, bad decisions with rippling effects can result,” say the authors.  Committing your team to unrealistic project possibilities in terms of time and cost will likely cause you to cut critical project activities and end up with less than satisfactory results.
  3. Stay laser-focused on the people and the organizational change management. Studies say that ignoring these is the number one reason for project delays and cost overruns.
  4. Start with effective business process management and process improvement. Systems today are so robust and flexible that you can do almost anything – and that’s a problem.  Take the time to study and prescribe your organization’s unique process requirements and workflows before you begin actual software implementation.  Plan the work, then work the plan!
  5. Maintain Strong project management, governance and controls. Panorama recommends that you clearly define your project team, governance and controls as part of your project charter. Consider hiring independent, third-party experts that manage these sorts of implementations for a living.  Make sure clear roles and responsibilities, as well as priorities, are in place and that everyone knows what’s expected of them.  It’s a team project, but it requires that someone be “in charge” when decisions need to be made quickly or roadblocks are encountered.  No surprise here: project management is key.

We agree with the assessment, and concur that if you manage these five areas above, the rest of your project can fall into place in a manner that’s congruent with the project you thought you were conducting at the outset.  Easier said than done, no doubt.  But if you want to save time and money, this is where the magic happens.


The average American checks their phone 47 times a day – that’s every 19 minutes of our working lives – according to Haley Edwards in a Technology Section article in Time Magazine published recently under the title “The Masters of Mind Control.”

If you find that troubling, some folks at an outfit called Boundless Mind would like to help you change that.  According to the American Psychological Association two-thirds of Americans think it’s a good idea to unplug for the sake of our mental health, while a University of Texas study showed that the “mere presence of our smartphones, face down on the desk in front of us, undercuts our ability to perform basic cognitive tasks.”

Meanwhile, Silicon Valley’s basic premise is to keep us engaged, enthralled even, with our devices.  Some have called it a “full-blown epidemic.”  We are not the customers for Facebook and Google, it has been said – we are the product.

The phenomenon is known as persuasive technology, the study of how computers can be used to control human thoughts and actions.  In the tech realm, it has fueled the proliferation of interfaces and devices that “deliberately encourage certain behaviors (keep scrolling) while discouraging others (convey thoughtful, nuanced ideas),”according to Edwards.  And every major consumer tech company today from Amazon to Candy Crush uses some form of it.

It’s not that we’re weak-willed, it turns out.  When your child collects Snapchat badges to maintain daily consecutive use streaks, his “brain is being engineered to get him to stay on his phone.”

The brain’s basic process it turns out is trigger, action, reward.  And that’s just the beginning of the feedback loop engineers can work on.

Boundless Mind’s business model is to develop new versions of these same persuasive tools, but then use them to sell to nonprofits and companies promoting education, health or social welfare.  For example, they apply VR (virtual reality) therapy to patients with chronic pain at 190 hospitals.  One application is a virtual game that helps manage post-operative pain by challenging patients to shoot little red balls at bears in a virtual world.  To work, the therapy needs to create an addictive interface to get patients to keep coming back, from which the interface can learn from the patient’s behavior and be personalized to make it uniquely rewarding for each user.

Boundless Mind debates the potential ethics of a client before taking on a new one, to ensure their tools are put to good use, and to hold themselves accountable.  The owners hope to be something of a “counterbalance” to the massive data scraping conducted by the big players, like Facebook, Instagram, Twitter, Google and their ilk.  They plan to develop persuasive-technology tools and then “release them to everybody” as their way of leveling the playing field.  They see the future as “promising,” and co-founder Ramsay Brown notes “We have the power to control our minds.  That’s quite a gift.”

It’s good to see someone trying to apply our device addiction more broadly for nobler purposes.

An ERP software provider called Abas (abas-erp.com) recently released a paper called “Writing a Better RFP” intended to advise companies on what’s wrong with most of their RFP processes, and how they might do better.  While we have no affiliation or relationship with Abas, we thought their advice was very wise and up-to-date in tackling the old paradigm for software selection.

Abas points out two flaws in most companies’ current Request for Proposal strategies:

  1. Putting excessive internal resources into filling out unnecessarily long RFP templates, and
  2. Paying third-party RFP specialists to create complex RFPs.

They make the point that these methods do little more than to make the process very expensive and bog down the selection process – and are of little help in selecting a vendor anyway.

The article’s author goes on to point out that today there are a great many common core functionalities across ERP packages.  Your goal should be to “reveal areas of competitive differentiation between potential vendors.”

So skip the generic questions they advise (which virtually all of today’s modern packages can handle) and cut to the questions that really matter to your company’s work, and how you run the business. They give the example of: “Is the ERP system capable of recommending an available-to-promise date or hard allocating inventory at order entry?”  You get the idea: ask the questions that are truly your choke points, or that relate to your competitive differentiators, to understand how the solution could improve your workflows.

Also, they advise: ask questions that seek to determine whether the vendor has experience and domain knowledge in your particular industry.  In this regard, all systems – and all vendors – are definitely not the same.  You want not just software fit, you want implementation expertise.

Abas points out – and we could not agree more – that RFPs are far too lengthy, and we too often find them filled with hundreds of largely irrelevant, or at least ‘generic’ questions that waste everyone’s time, and do nothing to help you establish clear winners or losers.  They further advise to give more ‘weight’ to the more important questions (to your business) and to the perceived expertise of your provider, and less weight to many of the generic components that most any system can handle, so you’re weighing in a manner that’s relevant to your most important needs.

What’s the right number of questions?  Believe it or not, Abas suggests (and again, biased or not – we prefer to think of it as ‘experienced’ – we couldn’t agree more…) that about 10 to 15, industry-specific  questions will tell you all you need to know to differentiate among vendors. 

Your RFP should be proactive, not reactive.  It should ask the questions most critical to the issues your business faces – and not just short-term, but down the road as well.  What emerging technologies might cause you disruption?  How well will your solution scale, or morph to fit your possible future needs?  Can it be changed and modified easily, and by whom?  All good food for thought.

And finally, ask yourself: Are you looking at cost, or value?  Sure, cost is important and the bottom line matters.  But focusing on cost alone is short-sighted.  Look at the bigger picture: total cost of ownership (TCO), along with the value proposition to your business over the next ten years, not the next two or three.


Each year Panorama Consulting publishes an annual report on trends in Enterprise Resource Planning software and their implementations at companies large and small across the country.  They recently published a brief summary of their conclusions, drawn from this year’s report, that yielded what they call their five key takeaways.  We share those with readers today.  Most of what follows is taken directly from their report, which can be found here.

[We should note that the average company size reported was over $400 million, across many industries, so our small to mid-size clients should take these with a grain of salt.  Small companies’ needs, budgets and buying criteria often vary greatly from their larger counterparts, but some of the broader conclusions still hold true.  Your mileage may vary.]

  1. Cloud ERP software adoption may have finally reached a tipping point. We saw a very large increase in cloud ERP software adoption this year compared to past years, with this year’s mix of SaaS and cloud deployments increasing to 85%, compared to 15% on-premise deployments. While this number may not be striking on the surface, it is a big difference from last year’s data, which showed less than 50% of organizations were deploying cloud and SaaS solutions.
  2. The grand illusion of lower ERP implementation costs. Past years have shown that the average total ERP implementation costs anywhere from 4% to 5% of a company’s annual revenue. This number includes a project’s all-in costs, including software licenses, implementation costs, hardware upgrades, organizational change management, training, backfilling internal resources, and any other costs associated with the transformation.  This year, that number decreased to 3.6% of annual revenue. While this may sound positive on the surface, it actually reveals a flaw in our data: since most deployments are cloud solutions (see point #1 above), initial costs are naturally going to be lower. However, our implementation cost data only captures the initial implementation costs – not the ongoing costs. In most cases, cloud deployment costs less money up front, but can increase longer-term outlays due to higher annual subscription costs. It is important to take this data with a grain of salt.

[The reference figure of 3.6% of annual revenue holds relatively true for even smaller companies.  A $20 million company might expect an outlay of around $500,000 all told.]

  1. ERP implementations are taking longer and resulting in more operational disruption. Despite lower up-front costs, ERP implementation durations are increasing. While the total average duration increased a relatively innocuous 16.9 to 17.4 months, those that took longer than expected increased from 59% to 79%. Again, this can be largely attributed to the increase in cloud deployments, which creates a false sense of implementation speed and ease and results in unrealistic expectations along the way.  Operational disruptions saw a similar increase. Those that experienced a material disruption following go-live – such as being unable to ship product or close the books – increased from 56% to 66% last year.
  1. Despite relatively high satisfaction with ERP software vendors, overall ERP implementation satisfaction levels plummeted to 42%. Customer satisfaction with their chosen and implemented ERP software increased to 68% this year. However, satisfaction with their overall implementations plummeted from 81% to 42%, which suggests that more companies are either struggling with their deployments and/or managing to unrealistic expectations surrounding those initiatives.

[Or… they suggest a flaw in the data?]

  1. Organizational change management still reigns as the biggest challenge to a successful ERP implementation. For the second straight year, organizational change management was atop the list of top reasons why projects took longer or cost more money than expected. Ironically, many organizations think they will actually save time and money by cutting this important corner, but research tells a different story. You are more likely to find that you have underinvested in managing organizational change, and those that do find that they implement faster, less expensively, and with a higher ROI than those that don’t.


A lot of companies fall into the “We Have To” category when it comes to upgrading their business software.  As in, we have to, because… our software is terribly old and outdated, or… it’s not supported any more, or… we’re so heavily modified in unnecessary ways that it just makes sense to start over.

Valid considerations all.  But should they be the foundational purpose – the raison d’etre if you will – for your upgrade?  In a word, no.

In fact, software upgrades provide the perfect opportunity to take a big step back.  Instead of simply replacing your old technology, you can recognize that software has taken huge leaps in the past few years, and that a new implementation is the ideal time to look at the big picture, the new tools, and the process realignment and organizational change management that fit so perfectly with a new system or upgrade.

View your effort as a digital transformation project, says Eric Kimberling, CEO of Colorado’s Panorama Consulting.  He recommends that companies “step back and define a clear vision for [their] ERP.”  He suggests that companies ask themselves: “What exactly are you trying to accomplish?  What business improvements do you expect?  How will modern technology help you realize those improvements?  How will your project governance align with those goals during implementation?”

It’s the right time to clearly define the benefits you expect to derive from your new system, and to better understand your own internal processes and workflows, whether automated or not.  You can then look at who is responsible for what, to determine whether that’s properly aligned – something the odds are you haven’t looked at in a very long time.

Your business case should extend beyond merely justifying your project.  You should be able to create gains, and then track those efforts in whatever sort of scorecard works for you going forward.  Defining just a few key performance indicators, and then monitoring these over time, remains one of the best prescriptions for implementing a new system that we’ve ever heard, or given.

As an added incentive, it’s worth recognizing the plethora of tools now available that didn’t exist, at least in manageable form, even a few years ago.  Business Intelligence reporting is a key one.  Companies today are finding gold from analyzing all the data they can get their hands on, often in unexpected places.  And when it comes to saving money through better understanding of your key business data – like inventory, turns, cash turnover and the like – it’s worth the investment.

It all comes down to planning.  If you work with your internal staff and a good outside consulting team, you’ll find it won’t take very long to get the momentum rolling toward improving your processes, refining your strategies, streamlining your workflows, and turning the “we have to do it” implementation blues into the “why did we wait so long” jig.