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Archive for the ‘Bidness, and Other Current Economic Realities’ Category

Our cohorts at Panorama Consulting often write good pieces about the importance of business process change management, especially when it relates to firms in growth mode who also happen to be implementing success strategies and software systems aimed at supporting that growth.

Recently they penned a piece on the topic of what you can learn from your business process management mistakes.  Because we also spend our days reviewing firms’ business processes, we thought their words worth sharing with our audience.  You’ll find their original piece here.

 

Just as researchers search furiously for the cause of disasters involving ships and planes, they suggest we too search for causes behind operational disruptions, which often cause morale problems among employees, inadequate software implementations and customizations, frustration all around, and low benefit realization.

To learn from our failures, the authors suggest we

  • Forgive – “Take a deep breath, forgive ourselves and others” to gain a clear head.
  • Analyze – Conduct a “lessons learned meeting to review project deliverables. Quantifying the direct and indirect costs in terms of time and money will give you an idea of the benefits you’ll need to realize to achieve a positive ROI on failure.”
  • Disseminate – Share lessons learned across the organization.

Panorama notes that “operational disruptions can be avoided by developing an effective business process management plan.”  They suggest including…

  • Business Process Mapping. We wholeheartedly concur, because any successful implementation always starts here.  At a high level, we map current processes and future-state processes, looking for technology touch points, redundancies (and ways to eliminate them), and how to do away with multiple and sometimes proprietary silos of information.  You reengineer your processes in order to optimize your workflows, both human and machine, to best capture the talents of your organization and the areas where you lend the most value to your customers.
  • Organization Change Management. Implementing new business solutions can often result in a decrease in productivity initially.  As the authors note: “Business process management cannot succeed without customized training and targeted employee communication, both of which should begin before software selection.”
  • Continuous Improvement. It’s a mentality.  And it will help ensure that you maintain optimized processes consistently into the future.  Set KPIs and other benchmarks which allow you to record progress and build toward improved performance.  Measure regularly.  If you can’t measure it, you can’t improve it.

Good advice all to anyone implementing process change, organizational change, or structural changes from software to process management.

 

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A tip of our hat to our friends (and accountants) at Insight Accounting Group for providing business owners and financial managers with a little clarity on the new tax law changes as they apply to capital expense rules and the Section 179 deduction.  You can read the full text from their May newsletter for yourself, along with past newsletters, at their site.

 

To briefly recap here though… Sec. 179 deductions are important investment tools for most business owners, allowing them to quickly recapture the benefits of their investments in capital equipment, including business hardware and software.  Following are some changes Insight Accounting wants everyone to know about going forward.

  • The new law increases the amount of business property purchases that can be expensed, from the former $500,000 to $1,000,000. Section 179 allows you to get the tax break immediately in the year the property is placed into service, rather than spreading that depreciation over several years.
  • An eligibility phase-out for Section 179 ensures it’s only used by small businesses, and that phase-out has been raised from $2 million to $2.5 million. If you spend over $2.5 million on business property in the year, your ability to use the $1 million Sec. 179 deduction is reduced dollar-for-dollar above that amount.  The deduction, by the way, applies to new and used equipment.  And, you can now use Sec. 179 on property used to furnish lodging (rental and real estate) and for improvements to nonresidential real estate like roofs, HVAC, etc.
  • Bonus depreciations limits have been improved under the new law, but for a limited time. Now, first-year bonus depreciations increases to 100% of the qualified asset purchase price for the next five tax years.  This is particularly useful for assets with a 20-year or less useful life, and thus includes equipment and software.  Bonus depreciation formerly applied only to new equipment, but can now be applied to used equipment as well.  The depreciation starts to decline in 2022, declining by 20% per year thereafter.
  • Remember finally that while the new tax law gives you expanded tools to accelerate depreciations, they’re not always your best bet; sometimes the standard tax treatments are more advantageous. The benefits have more to do with the timing of the expense, and not the amounts, so always be sure to check with your tax adviser or accountant first.

Again, our thanks to Insight Accounting Group for their guidance.

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Recently The Wall Street Journal ran an article we thought worth sharing about “what research tells us about effectively taming your inbox, when to use all caps, whether to use emoticons, how quickly to respond to message – and much more.”

(Well, we guess, that should cover it.)  Here’s what they found…

  • Replying to email promptly? Not always a good thing.  In companies whose cultures “emphasize speed of response, workers are more stressed, less productive, more reactive and less likely to think strategically.”
  • Handling email after hours? Also detrimental, the Journal report opines.  While some may feel more pressure to respond, those who do aren’t necessarily more efficient – they simply generate a higher volume of mail without actually getting more work done.
  • On the other hand… findings from a study of extroverts suggest that when they are working on routine tasks, “being interrupted by an email notification might be good for them – the social stimulation… may help avoid boredom and complete tasks more efficiently.”
  • When’s the best time to send an email? Studies show that when faced with a screen packed with information, people focus on what’s on top, so you want your email to correspond to when people are checking.  Based on a study of 16 billion emails, it was found that people “replied more quickly early in the week, and those replies were also longer. “ The same applied to time of day – between 8:00 AM and noon was best.  Apparently then, your best bet is to fire off your most important missives on a Monday morning.
  • What about email as a negotiation tool? Here, take advantage of email’s strengths, as most would agree that as a negotiating tool it pales in comparison to the face-to-face meeting, right?  Email’s strengths include ”the ability to rehearse what to say and convey a lot of information in a clear specific form that people can refer back to later on.”  As one researcher said, “if you understand how to use email effectively, it can be very helpful for your negotiations.”
  • SOME all caps is fine. It’s a long held tenet of email that using ALL CAPS is shouting!  But research says that’s not always right.  When used judiciously a word or two in caps can provide emphasis, communicate urgency or inject humor.  Just don’t do your whole email that way.
  • What about emoticons? Turns out, those little faces and pictures have been shown to help with comprehension, they shave a bit of negativity out of a message (or add a note of positivity), and are fine to use with people you know.  The caveat is to avoid using them in the wrong circumstances, such as in an introductory business email that sets the wrong first impression in a business context.  People may view you as ‘less competent’ and will thus be less likely to share information with you.
  • Take the time to view messages from the other person’s perspective. Research found that people are “consistently overconfident in their ability both to understand emotion in email and to convey it.”  Instead of skimming emails and firing off quick responses, they say you should take the extra time to view those exchanges from the other person’s perspective.

Good email communication, the Journal concludes, “is not about our intentions, but about the meaning that other people assign to what we write.”  In other words, the way people read your email might be different from how you thought you wrote it.  It happens… all the time.  They suggest asking yourself, “This is what I meant, but is this what the other person will get?”

 

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We noted in our prior post that underlying the cryptocurrency called “bitcoin” is what, in the long run, may be the more important element at play here: the blockchain.  Our prior post quotes The Wall Street Journal’s Christopher Mims’ fine explanation of the concept.  Now we’ll look at some important applications of blockchain technology.

In logistics, Walmart already uses a blockchain to list for sale over a million items, including chicken and almond milk, that provides its supply chain with traceability all the way forward and backward from source to sale.

Global shipper Maersk uses IBM’s blockchain technology to track shipping containers and move them through customs faster.

Both efforts are expanding rapidly, and other companies cited by Mims include Kroger, Nestle,Tyson Foods and Unilever.

A company called Everledger was started in 2014 with the intent of creating a blockchain that traces every certified diamond in the world.  It already has over 2 million diamonds in its registry, and adds another million or so per year.  Everledger records 40 measures of each stone, lending it traceability “from when it’s pulled from the earth to the day it’s purchased by a consumer.”  Every participant in that chain from miner to retailer maintains a node with a copy of the database in the blockchain.

A company in Israel puts internet-connected sensors on pallets and uses business intelligence analytics to determine when and where items could be damaged.  Blockchain participants can record every stage of the package’s journey via package, pallet and shipping container.

Even whole countries are adopting blockchain.  Dubai intends to be “the first blockchain powered government in the world by 2020.”  By moving its central record of all real estate transactions onto a blockchain, it will be faster and easier to transfer property titles, for example.

As blockchain technology becomes more widely accepted and integrated into supply chains, it has the potential, as Mims notes, to be a “fundamental enabling technology,” similar to how new data transmission standards across networks made the internet we know today possible.  It could one day underlie everything from “how we vote to whom we connect with online to what we buy.”

That being said, it’s wise to recognize that the current bitcoin craze is merely one application of the blockchain technology.  Clearly, much more will be, and is, possible through blockchain.  Bitcoin may — or may not — be here to stay; but blockchain seems to have all the merits and rapid adoption of a technological foundation that could change the way businesses run.

 

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With all the hype surrounding bitcoin these days making it sound more and more like a modern-day equivalent of the 17th century tulip bulb mania, it’s important to remember that there actually is something important going on here.  And it’s not about the bitcoin.  It’s about the underlying technology for bitcoin – the blockchain.

Investment manias may come and go, and bitcoin will likely make some folks rich (it already has for those who bought bitcoin at the start of 2017 at $963 and watched its price soar to nearly $20,000 by year-end; it’s since fallen back to around $8,300 as of this writing), and likely leave some ‘greater fools’ broke a little further down the line.  After all, bitcoin has no intrinsic value, it’s not based economically on anything, and its essential value is merely the result of what some other person is willing to pay for it.  As a currency proxy, it has a ways to go.

But the blockchain that bitcoin is built upon – that’s another thing.  And a recent article by Christopher Mims in The Wall Street Journal provides some of the best explanation we’ve seen for why it matters.

What is a blockchain?  As Mims explains:

“It’s essentially a secure database, or ledger, spread across multiple computers.  Everyone has the same record of all transactions, so tampering with one instance of it is pointless.”

He goes on to explain that the underlying cryptography…

“…allows agents to securely interact – transfer assets, for example – while guaranteeing that once a transaction has been made the blockchain remains at immutable record of it.”

Blockchain has the power to transform industries for three reasons, notes Mims.

First, it’s well-suited to transactions that require trust and a permanent record.

Second, blockchain requires the cooperation of many different third parties.

And third is… the hype.  “The excitement around cryptocurrency gives blockchain the visibility to attract developers and encourage adoption.”  In this way, blockchain resembles the cloud, which also gave many industries “new business processes, disruptive startups and new divisions within existing companies, an ecosystem of supporting technologies, and new ways to charge for services.”

We’ll take a look at some of that disruption in our concluding post, so stay tuned.

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We started this series of three posts, concluding today, with the story of “Lena,” the so-called first lady of the internet, named for a former Playboy model whose image in 1972 became the gold standard of sorts for compression algorithms used in the efficient transfer of digital images.  In the follow-up post (here) we noted the paucity of women in programming at that time, and the study that led to the shift towards an intrinsic bias towards men that has dominated the programming employment picture for decades.  Those posts were based on the work of Emily Chang in an article for Bloomberg BusinessWeek and a new book entitled Brotopia: Breaking Up the Boys Club of Silicon Valley.  Today we’ll conclude with some of Ms. Chang’s thoughts on the recent past and the subject of women in tech.

Chang points out that in Google’s early days, founders Sergey Brin and Larry Page sought to hire women for key positions, and succeeded wildly when you consider that they brought on board Susan Wojcicki who helped build Google’s AdWords and AdSense, two products that formed what Chang calls the “near-perfect business model” that today drives Google’s $100 billion business.  They then brought on Sheryl Sandberg who had been chief of staff to Larry Summers at the U.S. Treasury to help transform Google’s new self-serve ad operation that’s now “bigger than any ad agency in the world.”  Today Sandberg is CFO at Facebook.  Finally, they brought in Marissa Mayer as a product manager for Google’s search page.  She would eventually become CEO at Yahoo.

But despite hiring some of the most powerful and successful women the tech industry has seen, by 2017 Google disclosed that only  31% of its employees were female, and only 25% of leadership roles and 20% of technical roles were filled by women.

The issue, according to Chang, has much to do with what happens when you start to scale hiring.  Industry standard recruiting models collectively feature many of the same school job fairs, the same recruiting websites and they subscribe to the same ‘questionable’ theories about what makes for a good engineer.  Google eventually concluded that the hiring velocity caused them not to be as ‘thoughtful’ about the hiring process, nor cast as wide a net, as they could.

Determined to make changes, in 2015 the newly rebranded Alphabet, Inc. hired several women to key positions and ended up with a management team that is 40 percent female.  As yet, none of the company heads of Google’s 13 key divisions are women – but still, it’s progress.

The lesson from the past though is clear: Women like Wojcicki, Mayer and Sandberg brought wider skill sets to the company in its earliest days, and they succeeded wildly as a company.  Notes Chang: “If subsequent managers at Google understood this lesson, that might have quieted the grumbling among engineers who had a narrow idea of what characteristics made for an ideal employee.  Google’s early success proved that diversity in the workplace needn’t be an act of altruism or an experiment in social engineering.  It was simply a good business decision.”

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If you haven’t already, be sure to read our prior post before this one.  It’s the brief historical story of Lena, the early quality standard for algorithms that enable the transfer of digital images, and the precursor of today’s ubiquitous JPEG picture-file format.  If you know Lena’s original story, then please read on.  (Our post is excerpted from the work of Emily Chang of Bloomberg BusinessWeek and her new book “Brotopia: Breaking Up the Boys Club of Silicon Valley.”)

When Deanna Needell, now a math prof at UCLA, first encountered “Lena” in a computer science class, she quickly realized that the original image model was nude (she was culled from the pages of Playboy in 1972) and it made her realize, “Oh, I am the only woman here.  I am different.”  Needell says, “It made gender an issue for me where it wasn’t before.”

Her male colleagues, predictably, didn’t see the big deal.  Said one, “when you use a picture like that for so long, it’s not a person anymore, it’s just pixels,” in a statement that naively laid out the problem of sexism that Needell and her colleagues tried to point out.  But with so few women among the ranks of the programming class, it’s no surprise.

It wasn’t always that way.

As we’ve pointed out previously a post here, the early days of programming were predominantly fueled by women.  In that early, post-WWII era, programmers were mostly women, and the work was considered more of a clerical nature, and thus ‘better suited’ to women.  Only later, when the economy turned down and computers looked to be a key tool of the future, did men begin to enter the programming ranks, eventually even pushing women out as the image of computers and programming pivoted to something more suited to “introverts and antisocial nerds.”

In one pivotal study in the 1960s, two psychologists, William Cannon and Dallis Perry profiled 1,378 programmers, of whom by the way only 186 were women.  Their results formed the basis for a “vocational interest scale” they believed could predict “satisfaction” – and thus, success – in the field.  They concluded that people who liked solving various types of puzzles made for good programmers, and that made sense.

But then they drew a second conclusion, drawn, remember, from their mostly male sample size, in which they concluded that happy software engineers “shared one striking characteristic” according to Ms. Chang: They don’t like people.  They concluded in the end that programmers “dislike activities involving close personal interaction and are more interested in things than people.”  As Ms. Chang pointedly notes then… “There’s little evidence to suggest that antisocial people are more adept at math or computers.  Unfortunately, there’s a wealth of evidence to suggest that if you set out to hire antisocial nerds, you’ll wind up hiring a lot more men than women.”

So while in 1967 Cosmopolitan was letting it be known that “a girl senior systems analyst gets $20,000 – and up!” (equivalent to $150,000 today) and heralded women as ‘naturals’ at computer programming, by 1968, Cannon’s and Perry’s work had tech recruiters noting the “often egocentric, slightly neurotic, bordering on schizophrenic” demeanor of what was becoming a largely male cadre of coders, sporting “beards, sandals and other forms of nonconformity.”

Tests such as these remained the industry standard for decades, ensuring that eventually the ‘pop culture trope’ of the male nerd wound up putting computers on the boy’s side of the toy aisle.

By 1984, the year of Apple Inc.’s iconic “1984” Super Bowl commercial, the percentage of females earning degrees in computer science had peaked at 37%.  As the number of overall computer science degrees increased during the dot-com boom, notes Chang, “far more men than women filled those coveted seats,” and the percentage of women in the field would dramatically decline for the next 25 years.

We’ll finish out this series of posts with a look at the state of women in tech today and what that might mean for tomorrow, so stay tuned.

 

 

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