Friday, December 14, 2018

Companies Must Take More Responsibility for Education

It's well known that there is a serious shortage of IT talent both of the type that is capable of developing new systems as well as the type that is capable of managing a digital organization. Companies that go through a digital transformation process, and a few have, find themselves in a world of new issues. Business models inevitably change, with cost of entry dropping in some cases and profitability of new ventures becoming more unpredictable, or at least reactive to different pressures.

Many companies still rely on the traditional education system to produce the needed people. But that system is incapable of responding to new challenges quickly enough. While companies seek more agility, the educational system, by its nature, is limited in its capacity to be agile.

So companies have responded by providing training programs, which can be good, but usually are limited in their scope and depth because of the constraints of taking people out of production in order to train them.

What's really needed is a radical transformation in the overall educational and corporate training systems. They need to communicate and work together more effectively. Institutions need to respond to the needs of business. Corporate training needs to be an extension of the education provided by the institutions. It already often is informally but not so often formally.

Deloitte and others have said that “Companies should invest more in educating and training workforces for the digital era.” There is probably no alternative if companies are to remain competitive.

They're right. Companies need to put more resources into education.

Wednesday, December 12, 2018

Impact of AI on humanity

AI is moving ahead quickly - so quickly that our traditional social institutions may not be able to keep up. Yet, AI promises to be pervasive within just a few years. When you look at how quickly Google has moved into our fact finding space, and how much we rely on it, we can get some sense as to how quickly AI can move.

This will raise some important questions. As humans work more closely with AI constructs, ranging from programs to intelligent robots, eventually those robots will become almost indistinguishable from humans, raising questions as to the rights of the robots, and the rights of humans vis-a-vis the robots. As humans work more closely with AI designed to augment their own capabilities, those capabilities will be vastly overcome by the technological. This will raise questions as to the responsibility for decisions and actions. Reliance on code - which is basically what AI is -  will increase the feasibility of amoral corporations and governments slanting that code to suit their own purposes in pursuing profit and power.

Pew Corp did a study asking some "979 technology pioneers, innovators, developers, business and policy leaders, researchers and activists" to answer these and related questions in a canvassing of experts conducted in the summer of 2018."

They found a variety of concerns, and opportunities for humans, but all agreed that massive change is in the works - with some saying that such change is likely to extend over the next fifty years or more. The change will not come as once, meaning that humans will need to be very responsive in dealing with the change as it comes. But it will come fast, which means that some people will be displaced and left behind. Which in turn means social unrest, more populist uprisings, perhaps dictatorships.

It's a massive challenge calling for restructuring of our social, educational and government institutions. The survival of our society - of humanity as we know it, is at stake. To gain a greater insight into these issues, check out this article on the Pew website.

Wednesday, December 05, 2018

AI for Better Customer Service

Companies, particularly retail businesses, have been making greater use of Artificial Intelligence to enhance their customer service. They can't always go totally online, so it is in their interests to enhance the customer experience by improving convenience and helping to build customer loyalty. This has been approached by providing customer service personnel with technology like tablets loaded with useful data and related AI apps, as well as apps designed to effectively close a sale and facilitate immediate delivery. With many companies that have not gone totally online, this has expanded to include a variety of new AI technologies and the means to deliver them. The latest trend includes the use of wireless technologies that can track customer movements, including when the enter the store, so they can be approached with knowledge of their interests and preferences.

One lesson that has been learned is that in many cases, direct human interaction is necessary before the deal is closed. Which means the technology must remain in the role of supporting the human activity rather than replacing it. The strategic issue has been to define the best mix of human and technological involvement in the process.

This is a process requiring continuous improvement which in turn requires that the actions of competitors must be closely watched in order to maintain or build on product differentiation.


Friday, November 23, 2018

Automation of Accounting

Over one-third of respondents to a recent Consumer Technology Association (CTA) survey say they plan to automate accounting tasks. McKinsey & Co estimates that about 20 percent of the tasks in a typical recording and reporting cycle can be automated and nearly 50 percent of those tasks can be mostly automated. "CIOs could consider looking at the ways their accounting department collects, processes and reports financial data. Many firms have been automating the process of producing and submitting regulatory filings, for example."

Most of the regulatory bodies in the world have set the stage for automating their filings by having adopted XBRL (eXtensible Business Reporting Language). XBRL presents a tremendous opportunity for companies to fully automate their process of preparing and submitting regulatory reports. It can fit into any accounting system from SAP to EXCEL spreadsheets.

This opportunity is not available for Canadian companies in their filings since Canadian regulatory authorities are way behind the rest of the world in adopting XBRL. However, Many of those companies need to file with the SEC in the US, and the SEC has required the use of XBRL for years. The movement to inline XBRL is even better,  because it makes possible the automation of the whole filing, since with inline XBRL, the need for a separate text based document is eliminated.

All of which means that XBRL fits beautifully into the process of digital transformation.

Monday, November 19, 2018

Watch Where Your Data Goes

Many of us have linked our phones to our cars. Such linkages enable hands free usage, making them popular. These linkages work through the use of bluetooth, a powerful but famously insecure technology that enables wireless transmissions over short distances. When a linkage is established, it makes all the personal information on your phone available to your car. Something many of us don't always think about.

Such information would include contact details, call and text logs, and perhaps even full text messages.

This vulnerability was brought to our attention in February by exposure of the CarsBlues Hack and since then has been addressed by some of the car manufacturers, so that some 2019 models have installed preventative measures. But others haven't. So this means when you give up control of your car, such as by selling it or returning it after leasing, it means you should wipe out the information in your car system. This can be done by using the settings function for your car's system. There are usually two steps - delete the phone connection, then delete the associated data from the system. For most cars, this is a relatively simple operation.

The problem with personal data on cars is similar to the issues around the growth of IoT devices, where any number of devices are connected to the internet. When you discard these devices, its wise to delete the data from the devices and also any related internet sites. This is not always simple, but worth doing in any event.

Tuesday, November 13, 2018

Smart Contracts Have Weaknesses to Address

The most common and at this point the most useful application of blockchain is for smart contracts. An industry is growing around this application, including Ethereum, Eos and Tazius, among others.

Smart contracts are designed to automatically implement contracts that involve some routine procedure that can be programmed. Program code is developed and entered into the blockchain for processing. Once an implementation is initiated, it cannot be changed; all blockchain based contracts are immutable. Code can contain errors, so proper development techniques are crucial.

Smart contracts are encrypted and so the encryption keys pose a risk. They need to be fully protected. Most attacks on blockchain contracts so far have involved attacks on the keys.

Setup is therefore critical for smart contracts, and must often involve legal reviews and audit reviews before they are executed.

Some commentators have given a false impression that blockchain contracts are free of risks and do not require any reviews or such procedures. Because of the need for accurate code, strong encryption keys and effective access control, this is simply untrue.

Thursday, November 08, 2018

The Need for IT Oversight

IT Governance has been a major area of concern to Boards of Directors for many years. The problem stems from the fact that the members of the Board usually have limited understanding of IT, yet the Board has overall responsibility for firm governance and is accountable for financial stewardship and results. And IT is a major element of corporate activities.

Many Boards have approached this issue by appointing a member of IT management to the Board, which helps improve communications. Others have formed an IT Oversight Committee, that is closely tied into IT governance and reports regularly to the Board. Still others have formed a digital strategy think tank, which obviously offers insight into IT Strategy for the Board to consider.

There is a place for all of these groups in corporate governance. And several different ways to organize these IT groups, some better than others. The best approach is to make them high level committee, reporting directly and regularly to the Board. Members of the ITO Committee must be very knowledgable about IT and involved in it's management or governance. Functional management groups, such as AI Implementation, Data Management, etc. would need to channel into the ITO.

In this way, overall IT Governance is a network of top management and Board members where IT becomes an integral part of Firm Governance.

It is now all but impossible to avoid IT in firm governance. So, the issue is not to consider including it, but rather how to include the IT issues in a way that can optimize Board awareness and lead to decisions on IT strategy that are most likely to enable achievement of corporate objectives.

Tuesday, November 06, 2018

AI Implementation Levels

The most common approach to AI implementation is to approach it as an exercise in automation. Companies look to the processes in their organization and decide which ones can be automated, thus removing or reducing the human content and saving money.

While this approach can be useful, and perhaps even a way to start, Gartner, in their release "Building the AI Business Case", points out that it is a mistake to stop there. They argue that many organizations are missing the best of what AI has to offer. That the way to approach AI is to find ways in which human effort can be augmented. That involves looking at decisions that need to be made and considering how AI can help that rather than looking at processes that can be automated.

There are several levels of AI - Reactor, Categorizer, Responder, Learner and Creator.

The reactor level involves simply automating existing processes, eg. filling orders. It's the most basic level. The categorizer level , as the name implies, is AI that can identify categories of transactions and apply algorithms to enhance those decisions.

A good example of responders is driverless cars. That level of AI can identify and react to a number of particular situations. This is quite a sophisticated level of AI. Which raises the issue that one of the considerations in implementing AI is the risk appetite of the organization, or its risk appetite in particular interactions, some being more sensitive or critical than others.

Learner levels can learn from experience and then use that experience to augment future decisions. One example of a learner level application is medical diagnosis - obviously a critical application.

An organized approach to AI implementation is critical to gaining the benefits and also to avoiding unnecessary risks. The Gartner paper offers some useful guidance.

Friday, November 02, 2018

Intelligent Automation, a Path to Digital Transformation

Digitizing parts of an organization is a complex process, involving determining what processes are used in the business, and which of them would benefit from automation. And the complex interaction between humans and technology needs to be taken into account.

Many organizations are now automating these processes using smart bots that can monitor an activity and learn how the processes work and determine which ones should be automated. For example, they can follow the work of an insurance representative, track the interactions with customers and potential customers, including the reactions of the people in different scenarios and learn from the experiences. In other words, the bots use machine learning.

The idea is to reduce repetitive, manual tasks to leave more time for the more interesting and important relationship enhancing work. The human/technology interaction is referred to as orchestration and the objective is to optimize it.

For a more in-depth article on this subject, check out this link.

Wednesday, October 31, 2018

Machine Learning, AI and Digital Transformation

AI refers to a variety of technologies, some pretty basic and others very advanced. Basic AI has been in use for many years. As for the advanced - well, it's hard to define that, since it keeps changing so fast.

A powerful use of AI now is in the area of autonomous data analytics. The word autonomous implies that the analytics are able to stand on their own - able to make their own decisions. This is what is happening with the help of AI and machine learning.

Companies have more data available to them than at any time in history. However, that data is of little use unless it is analyzed so as to yield useful insights and prospective information. Also, the analysis must go a lot further than simply being sufficient to support a particular hypothesis. Rather it must be mined to yield the secrets and lessons it holds.

Autonomous analytics, aided by AI, supports that approach by being able to recognize relationships in the data that can then be used to formulate further lines of enquiry. That's where machine learning comes in. All of this is automated. In addition, the analysis can encompass very large bodies of data, maybe even all the data available to a particular company.

Techniques for implementing such systems are advancing quickly and several companies have been reporting useful results.

For a good paper on this subject check out this one.

Friday, October 26, 2018

AI and the Trough of Disillusionment

Artificial Intelligence adoption is playing a major role in the implementation of digital transformation by businesses. The hype is strong and expectations are running high.

Recent Gartner surveys show that a major part of AI implementation is likely to be in the area of customer interaction. It's not going to happen in the next year or so. Five to ten years is being put forward as the most likely timeline. Can the hype survive such a wait? Not likely.

AI still needs to go through the Trough of Disillusionment as identified in Gartner's Hype cycle. With so much emphasis on customer interaction, that trough could be deep. Past and current attempts to have customers interact with computers have been rife with frustration on the part of the customers. Even the established and simple process of calling a company and being met with an array of choices in the form of selecting numbers still does anything but encourage customer interaction.

Of course, the new AI systems will be a lot better than that and will be conversation based. But they had better be very good. Anything less will bring us back to our experience with the more primitive systems of the past. And the trough of disillusionment could then be a canyon. For more on Gartner's take, check this out.

Monday, October 22, 2018

Facial Recognition - A technology to watch

There's a growing realization that facial recognition (FR) technologies, aided and abetted by AI, are becoming more powerful, will be used more often and pose a significant threat to privacy.
In the past, tests have shown that facial recognition is often not very effective. For example, at Boston Logan Airport, volunteers posing as terrorists could only be successfully identified 60% of the time during a test, a rate that was determined to be unacceptable.

The AI component is becoming more powerful, however, and performance will be better in the future.

Given the widespread interest in using FR for a variety of purposes, a major purpose being safety, its use will increase rapidly. Along with this will be a need for new regulations to protect individual privacy.

It will not be possible to seek permission for all applications, so other means will be required, such as oversight boards, and notices to inform people that FR is in use. It will be necessary to define when permission will be required. Or when people may be allowed to wear sunglasses. Lots of issues will arise. See this article for example,

The use of AI will likely be useful in dealing with privacy, by introducing logic that deactivates FR in certain circumstances.

The privacy implications of FR is a major issue in the battle of technology vs privacy and developments merit close scrutiny and monitoring.

Saturday, October 20, 2018

Some Outstanding IT Trends for 2019

Gartner recently released their much anticipated list of IT strategic predictions for 2019. There are a few trends that stand out.

In 2019, efforts will continue to adopt AI, but this will be a rocky road because of skills shortages. Although it may begin to improve by year's end. Also, AI will likely enter into emergency care of chronic patients through powerful AI screening techniques. Thus freeing up emergency rooms for true emergencies.

Privacy will continue to be under attack on several fronts. Increased use of facial recognition technologies will mean that roadside cameras and mobile phones will be able to identify people easily. Think about that. However, Gartner anticipates that public security monitoring will increase without opposition because of fears about public shootings. Also, privacy in social media will continue to be a problem which will remain unabated because people will continue to use social media.

Also in the privacy domain, blockchain has serious loopholes (particularly because it contains text fields that may not be encrypted), which will lead to more privacy issues as blockchain gains more adoptions.

There are other interesting insights or 2019 and beyond. Read the full list here.

Friday, October 12, 2018

How SYSCO is moving to the Cloud

Sysco is one of the world's largest corporations involved with food distribution. In this time sensitive industry, IT systems that are reliable and timely with good data and excellent responsiveness are critical.

There is no tolerance for downtime. Cloud systems offer up parallel systems so if a system goes down, action shifts seamlessly to the other systems. There is lots of scalability so the company doesn't get caught in lack of resource.

For these and other reasons, Sysco decided to move their systems to Amazon Web Services (AWS), one of the world's foremost cloud services. Sysco was in the midst of large ERP installations and upgrades, which are major, very expensive projects with the potential for downtime, particularly when the new services go live.

Sysco opted for a "strangler" technique of implementation, which involves identifying particular sets of functionality in the legacy systems and their ERP, rewriting them as modules so as to work in the new chosen systems and then implementing them on AWS. Eventually, the old systems can be shut down.

In recent years, they have been employing this method with considerable success. Costs are reasonable, and functionality is preserved and improved.

For a summary of this experience, check out this website.

Tuesday, October 09, 2018

Advanced Technologies Need Not Scare You

A growing body of research and literature is pointing out that many traditional jobs will be eliminated or substantially reduced because of the growth in availability of big data, and use of analytics, Artificial Intelligence and Big Data. As a result, many people are concerned about their jobs.

Some will indeed be eliminated, for sure, but in most cases, they will have little to worry about. In fact, they will have some new and interesting challenges.A recent study by the World Economic Forum directly addressed this issue. It has some very positive messages.

There is nothing new about technology incursions into the workplace.We've all experienced it. Taking accountants as an example, the more routine aspects of the job - bookkeeping and preparation of financial statements have been automated for years. The more judgemental parts of the job, such as valuation of assets, have remained largely with humans. However with the use of AI, more of these judgements will be supported and/or initiated by the AI software.

Already, AI is being used to support decisions. But it will move well beyond that. The way it is likely to play out is to imagine how decisions are often made now - through groups of people with different skill sets. Imagine when one of the members of the group is a computer, or an AI engine - one who fully participates in the discussion. Perhaps think of it as a robot. It can listen to ideas, comment on them and offer suggestions. It brings to bear past decisions in similar circumstances and the results of advanced analytics.

The people are still doing their jobs, but with more useful information at their disposal. Less time is spent on the mechanics of the analysis and more on the judgements and decisions to be made. Not everyone is going to know how to do advanced analytics, but some or all are going to need an understanding of them and how to use the results. Therefore as the technology evolves, the level of the people jobs will rise to more challenging and interesting levels.

According to the WEF study, "As companies begin to formulate business transformation and workforce strategies over the course of the 2018–2022 period, they have a genuine window
of opportunity to leverage new technologies, including automation, to enhance economic value creation through new activities, improve job quality in traditional and newly emerging occupations, and augment their employees’ skills to reach their full potential to perform new high value- added work tasks."

One of the results of these strategies we will hear more about will be augmentation strategies - strategies to augment existing jobs and processes with advanced technologies.

Sounds like an exciting new time, time to accept the challenges, not to be afraid of them.

Friday, October 05, 2018

Challenges Facing the Alignment of Business and IT Goals

The extremely fast growth in the rate of change in technology is creating new challenges for management, both the traditional business managers and IT management. For several years, there has been a recognition that the objectives of IT and the business overall need to be aligned to produce optimal results. Generally, this has been addressed by ramping up the role of the IT executives in the organization - creating CIO VP positions, having the CIO report to the CEO rather than the CFO, placing the CIO on the Board and other similar organizational and cultural steps.

All of this is good, but not all organizations have implemented these steps and even those who have are facing challenges.

A major source of the issues is simply the pace of change, which is rapid and unprecedented. The realization by business managers of the importance of digital transformation has led to growing requests to their IT people, from artificial intelligence to machine learning to the impact of the internet of things to simply automating greater swaths of the business activities of the organization.

The pressures on IT have led to resource, cost and budgeting issues, which of course sends pressure back to the business leaders.

To address these issues, both business and IT leaders need to change their outlook - and skill sets.

Business leaders (those executives who have not traditionally been part of the IT community) need to gain a greater understanding of IT management issues. This can be achieved by appointing the CIO as a VP and reporting to the CEO. This makes the CIO a peer with other senior executives with the concomitant elevation in the level of discourse between them. The organization also needs to create means by which the two groups can interact  - advisory committees, working groups, etc.

Such appointments can also lead to changes in the perspective of the IT leaders. Greater involvement in business issues through the board and other committees, will shape their perspective on the demands placed on IT. Over the long run, these changes will serve to shape the executive positions themselves as well as their educational processes, with people interested in business management gaining greater IT knowledge and IT managers enhancing their general business knowledge.

This is the trend anyway, but explicit recognition of it in corporate management will help to speed the process.

Tuesday, October 02, 2018

The Scope of Digital Transformation

Digital Transformation has been defined as "the profound transformation of business and organizational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritized way, with present and future shifts in mind." (i-scoop)

Implementation of digital transformation requires a defined strategy and all of what that implies, including definition of activities, processes, timelines and responsibilities. It also requires careful identification of technologies - those in place and those that might be adopted. It requires digitization of numerous processes in the organization, including those that have never been digitized before. True digital transformation is comprehensive.

Digitization of processes require proper process management, which includes business process reengineering and change management. Inevitably the involvement of the people carrying out these processes is required to make this work. People involvement is necessary all the way through, but one of them is in areas being changed that involve interaction with customers and other stakeholders. People who are closest to customer service should be involved, perhaps even the customers themselves.

In digital transformation as currently practised, there is an increased reliance on the latest technologies - big data retrieval and analysis, artificial intelligence, machine learning and internet of things in managing corporate assets. These are prime areas where digitization might replace some or all of what people are currently doing.

It's easy to see that digital transformation is a major area of corporate management - transformative and long term. Evolution of cultures and technologies cannot be ignored.

Future articles will delve more deeply into these issues.

Wednesday, September 05, 2018

The Value of Augmented Analytics

Most people agree that data is the lifeblood of most companies in the current environment. More and more data is available, but this leads to a need for a great deal of work to make good use of it. Raw data needs to be collected, cleaned, analyzed and insights generated that are useful in conducting business.

To do much of this work requires data scientists, but those professionals are notably scarce. Also, their business instincts may be low. Others can try to fill in, but with varying degrees of efficiency.

This is where augmented analytics comes in.

Augmented analytics makes use of machine learning and artificial intelligence to automate the cleaning, analysis and insight generation aspects of the process. Augmented analytics engines build a database of business-based algorithms to enable the generation of insights from the analysis that will be based on specific business elements and relationships. This is more than a data scientist would normally be able to do without significant additional training.

The analysis from augmented analytics is likely to be more relevant than any conventional analytics and, in addition, requires little or no human intervention.

It's a technological answer to a business need in a data-based world. Most large Business Intelligence providers are getting into augmented analytics.

Thursday, August 30, 2018

Cybersecurity - Looking to the Banks for Guidance

The growing complexity and urgency of cybersecurity is leading to a good deal of strategic thinking in business. Companies are and have been responding as best they can but they are still often searching for direction in the overall strategy for strengthening their security in cyberspace.

Banks have special demands put upon them and have special needs for good cybersecurity, so it makes sense to look to banks for guidance on what direction cybersecurity might or should take.

KPMG did this by discussing the major challenges facing their banking and financial clients in three major areas of the world - Asia, Europe and the US.  The results were published in a white paper on the firm's website.

Some of the major issues raised were:
  1. Cybersecurity needs to be seen as a business issue and not just a technology one. Nothing new here, but it seems  business is still struggling with this concept. Some of them are addressing this issue by creating a dedicated cybersecurity organization reporting directly to an Operational Risk group, thus enabling the business to own the issue.
  2. As with other industries, banks have experienced increased regulatory requirements, so regulatory risk has continued to grow as an area of concern. since regulatory risk can detract from other more threatening areas of risk, increased regulation carries a risk itself of shifting the cybersecurity actions of companies away from the most serious threats to that of compliance.
  3. Banks have been integrating their activities on money laundering and fraud with other cyber controls, raising a prospect of more efficient and hopefully more effective controls.
  4. Increased tailored training of business, non financial people on how cybersecurity incidents work - what they look like and what to watch for.
This brief white paper provides some interesting insights into the direction of cybersecurity controls and is worth a read.

Wednesday, August 15, 2018

Balancing Human and AI Activities

AI and machine learning has been making inroads into many aspects of commerce, with one of the notable areas being retail. Leaders like eBay are using a combination of AI and humans to achieve the best they can in customer service.

In a simplistic sense, AI basically uses data and algorithms to achieve the intended results. While powerful, modern AI has its limitations. For example, humans are better than machines at empathizing. Customers act differently with humans than they do with machines. Humans are better than machines in establishing the contest of particular purchases - for example, wedding and anniversary gifts call for different sensitivities than many other more routine purchases. Machines on the other hand are better at finding nuances in data being used, in determining product categories for particular market segments, even in determining customer clothing sizes.

What this means is that human and machine activities must be carefully thought out and implemented. Experience has shown that these activities should be as discrete as possible, so they don't overlap.

Effective implementation of AI also requires the means to update that strategy as experience accumulates.

For a particular use-case, check out this link.