” But as digital technologies continue to improve, get less expensive and grow more widespread, those gaps are closing or becoming less relevant. Gaps based on knowledge and use, however, remain strong â€“ and in fact may be getting larger. Over time it seems â€“ and especially with respect to the adoption of social and digital technologies in organizations â€“ the digital divide is defined less by â€œwe canâ€™tâ€ and more by â€œwe donâ€™t wanna.â€”
Itâ€™s never been so easy to do so much with so little. The technological and financial barriers to adoption of incredibly powerful tools and platforms are generally very low.
New technologies create a â€œpeople paradox.â€ Although the idea is counter-intuitive to many, people are much more central to the Digital Era opportunities and challenges we face than technology.
The (r)evolution is bigger than we think. Many people falsely assume that new technologies only impact organizations in certain sectors (e.g., consumer goods and services), specific functional areas (e.g., marketing), and individuals in certain types of jobs and professions (e.g., IT) or at particular stages in their work lives and careers (e.g., digital natives).
We get in our own way. Though technological and financial barriers may be low, psychological barriers to new technology adoption are very high. These barriers are both cognitive and affective, and each type of resistance reinforces the other
We live in the past and like to play it safe. Temperamentally, most humans have a tendency to look backward rather than forward
Weâ€™re conditioned to be Luddites. Another significant barrier is that most organizations â€“ from schools to public sector entities to for-profit enterprises â€“ are dominated by Industrial Era thinking and operations
Thought leaders and champions need to not just trumpet the â€œcoolâ€ aspects of new technologies, but also their practical benefits.
Formal organizational leaders need to educate themselves about new technologies, their applications, and their implications.
Educators at all levels â€“ and especially in higher education â€“ also need to educate themselves about new technologies and their applications and implications.
Informal leaders who understand new technologies and their benefits and challenges can help others make the necessary transitions by being champions and cheerleaders
Self-leadership means we will all take it upon ourselves to understand new digital technologies and make educated and informed choices about which technologies we will embrace and leverage
” It seems we are approaching another turning point in technology where many concepts that were previously limited to academic research or very narrow industry niches are now being considered for mainstream enterprise software applications.”
In simple terms, machine learning is a branch of the larger discipline of Artificial Intelligence, which involves the design and construction of computer applications or systems that are able to learn based on their data inputs and/or outputs.
The discipline of machine learning also incorporates other data analysis disciplines, ranging from predictive analytics and data mining to pattern recognition.
To improve performance on some task, and the general approach involves finding and exploiting regularities in training data.
The combination of analytic methods can ensure effective and repeatable and reliable results, a required component for practical usage in mainstream business and industry solutions.
Representation means the use of a classifier element represented in a formal language that a computer can handle and interpret;
Evaluation consists of a function needed to distinguish or evaluate the good and bad classifiers; and
Optimization represents the method used to search among these classifiers within the language to find the highest scoring ones.
There are several scenarios where machine learning can have a key role: in those systems that are so complex that algorithms are very hard to design, or when an application requires the software to adapt to an operational environment, or with complex systems that need to work with extensive and complex data sets.
Model Driven. Emphasizes access to and manipulation of financial, optimization and/or simulation models
Data Driven. In general, a data-driven DSS emphasizes access to and manipulation of a time-series of internal company data and sometimes external and real-time data.
Communications Driven. Communications-driven DSS use network and communications technologies to facilitate decision-relevant collaboration and communication.
Document Driven. Uses computer storage and processing technologies to provide document retrieval and analysis.
Knowledge Driven. Knowledge-driven DSS can suggest or recommend actions to managers.
Despite what many business people might guess, machine learning is not in its infancy. It has come to be used very effectively across a wide array of applications.
In either case, machine learning is preparing to be part of the next evolution of enterprise intelligence business offerings.
“The need for transformation has never before been more keenly felt in the corporate world. Digital-first companies, such as Amazon, Facebook, Google, and Twitter, are amassing market share and capitalization, but only a few brick-and-mortar corporations (think Apple, Nissan, and HCL Technologies) have been able to change fast enough to catch up with their rivals. Why do companies that lose their relevance find it so tough to recover?”
One, digital technologies have shortened and simplified execution cycles, and compressed advantages built on physical reach
Two, with the emergence of specialized organizations that can handle manufacturing and logistics, customer support and after-sales services, and IT, entry barriers in many industries have fallen.
And three, the new technologies have made possible more consumer analytics, greater visibility, and scale, forcing a move away from standardization and towards personalized offerings and unique experiences.
As a result, the winning formula has become: Innovative Ideas + Delivering Unique Experiences + Enabling Leadership.
The Logic Trap. Companies often have to consider doing what others believe is impossible; they canâ€™t change radically by thinking within the boundaries of reason
The Continuity Trap. A comet leaves behind a tail long after it has disappeared, but astronomers, knowing that the comet has gone, quickly re-calibrate their telescopes to search for the next one. By contrast, many business leaders take comfort in the past â€” essentially staring at the long-gone cometâ€™s tail â€” rather than getting excited about the uncertainty of the future.
The Leadership Trap. If the source of todayâ€™s competitive advantage lies in the interface between employees and customers, the leaderâ€™s role must change from being a commander to an enabler of bottom-up innovation.
The impact of digital technologies on business and leadership models is the biggest issue facing corporations nowadays. Itâ€™s an opportunity for business leaders to stand up, be counted, and convert the threat into an opportunity for transformation without settling for incremental change.
“Where governments have failed to restore previous world growth levels, could a management renaissance do the trick? Noting in a Harvard Business Review blog that a mere 13 per cent of employees worldwide are engaged in their work, with twice as many disengaged or hostile, Richard Straub and Julia Kirby call for a â€œGreat Transformationâ€ that would set the world on a new path to sustainable growth.”
Clayton Christensen, holder of the unofficial title of the worldâ€™s most influential management thinker, blames managersâ€™ short-termism for companiesâ€™ preference for innovation that cuts costs (usually jobs).
dismantling the bonus culture that misdirects managersâ€™ investment decisions is the single most important task for economic and social policy today.
â€œInstead of liberating the creative and innovative energy of employees [ … ] blind processes and rigid hierarchies still hold them down.
A-list management voices as well as a cohort of younger thinkers and doers, have been calling for the reinvention of management along these lines for years. But nothing much has changed,
What locks them all together in a tight, self-reinforcing paradigm is shareholder value â€“ the assertion that the sole purpose of the company is to maximise returns to shareholders.
So, yes, an era of management-led growth is both feasible and urgently needed. But the renaissance will not flourish unless a stake is driven through the heart of the shareholder-primacy zombie first.
” Management science as it is taught today and embedded in firmsâ€™ structures and processes still assumes that the introduction of a new offering â€“ let alone a new business model â€“ is the exceptional event and not the norm.”
the evidence is that managers themselves have resigned themselves to not matter. There are so many practices that they are engaging in that cause management not to matter.
The problem is that most academics, in their attempts to create theories, begin and end at the level of data. And increasingly they donâ€™t know what is going on in the dumpster because they havenâ€™t spent any time living there.
They didnâ€™t create the data â€“ so they manipulate data without even recognizing that it is a proxy for reality. They think it is real.
If you have a construct, then itâ€™s just a hop, skip, and a jump away from understanding what really causes things to happen.
Corporations actually have diseases and they are rooted in processes inside of companies. I donâ€™t think Peter spent a lot of his time manipulating data. He tried to understand processes that go on inside the company so that he could understand, â€œyou have this disease, and you donâ€™t have that disease.â€ Of all the contributions that Peter Drucker gave to managers, above everything else is that he taught us how to think.
And so the evaluation of the ideas quickly turns into a review of how good the numbers look, as opposed to being a substantive discussion about things that are not known. Thatâ€™s why I think weâ€™ve regressed
Do managers matter? They actually donâ€™t matter unless they are trying to get ahead of themselves and create the insight to frame what is really going on in the world.
Much of me believes that the role of finance in our economies will diminish very significantly in the next ten years.
The cost of capital is negative. Seeing these kinds of things happen, I think banks, many of them, wonâ€™t exist ten years from now.