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.
Friday, November 02, 2018
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.
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.
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.
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.
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.
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.
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.
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.
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.
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:
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:
- 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.
- 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.
- 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.
- Increased tailored training of business, non financial people on how cybersecurity incidents work - what they look like and what to watch for.
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.
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.
Friday, August 03, 2018
How AI is Affecting Accountants
The accounting industry is gearing itself for a major upheaval because of the implementation of artificial intelligence. The massive changes on the way - and already happening - are truly impressive. A recent report by PWC makes this clear.
In a global sense the report states that GDP will be up by 14% by 2030 as a result of AI. A high portion of this growth will come the replacement of workers in routine jobs by AI, something which is not new for technology but will be speeded up and enhanced with AI. And there will be new jobs for those who must manage and supervise the AI applications.
The impact of AI by augmenting or replacing humans is well known. The PWC study goes a lot further. To illustrate, it includes the following example of an AI application:
"An online insurer has leveraged an AI bot to automate the claims process from beginning to end. Instead of the days or even months it traditionally took to settle a claim, the bot is able to complete the entire pipeline from claims receipt, policy reference, fraud detection, payout and notification to customers in just three seconds."
Both accountants and auditors are deeply affected by this kind of application. Both are required to have a knowledge of the control system. Since this control system has been placed entirely under the actions of an AI bot, the accountants and auditors need to have a good understanding of how that bot works - in principle and in practice. They need to know how to test the effectiveness of that bot.
Multiply this by thousands to AI bots and you have an appreciation of why people are calling the AI revolution transformative.
In a global sense the report states that GDP will be up by 14% by 2030 as a result of AI. A high portion of this growth will come the replacement of workers in routine jobs by AI, something which is not new for technology but will be speeded up and enhanced with AI. And there will be new jobs for those who must manage and supervise the AI applications.
The impact of AI by augmenting or replacing humans is well known. The PWC study goes a lot further. To illustrate, it includes the following example of an AI application:
"An online insurer has leveraged an AI bot to automate the claims process from beginning to end. Instead of the days or even months it traditionally took to settle a claim, the bot is able to complete the entire pipeline from claims receipt, policy reference, fraud detection, payout and notification to customers in just three seconds."
Both accountants and auditors are deeply affected by this kind of application. Both are required to have a knowledge of the control system. Since this control system has been placed entirely under the actions of an AI bot, the accountants and auditors need to have a good understanding of how that bot works - in principle and in practice. They need to know how to test the effectiveness of that bot.
Multiply this by thousands to AI bots and you have an appreciation of why people are calling the AI revolution transformative.
Thursday, July 19, 2018
Digital Transformation is a Long Term Strategy
There are degrees of digital transformation, but the term is generally meant to refer to maximizing the use of digitization in the organization. "Digital transformation is the integration of digital technology into all areas of a business, fundamentally changing how you operate and deliver value to customers", according to The Enterprises' Project.
That's a sweeping project that affects every aspect of the business. It means eliminating many paper based processes, and even whole jobs. It means training in new functionality and systems. It means overcoming the natural resistance to change of people.
Large scale implementation of technology, enterprise systems for example, has taught us that these - the people issues - are the most difficult part of any technology implementations.
So while some companies approach digital transformation as an event - something that just needs to be implemented and then life goes on - other wiser organizations recognize that it is much more than that. It is the beginning of the implementation of a new basic strategy, one that will become an ongoing part of the fabric of the organization. A recent article in Forbes Magazine puts it well, It is a journey.
It starts with strategic planning, with all the implications of that process - consultation, discussion, agreement, strategic objectives formulation, champion identification, project scheduling, action plans, monitoring, assessment and re-assessment and ongoing revision and refinement.
Remember that initial definition above - fundamentally changing how you operate and deliver value to customers. Those are fundamental to the business and any changes like that require a strong commitment by the people involved. Definitely not a one-off project.
That's a sweeping project that affects every aspect of the business. It means eliminating many paper based processes, and even whole jobs. It means training in new functionality and systems. It means overcoming the natural resistance to change of people.
Large scale implementation of technology, enterprise systems for example, has taught us that these - the people issues - are the most difficult part of any technology implementations.
So while some companies approach digital transformation as an event - something that just needs to be implemented and then life goes on - other wiser organizations recognize that it is much more than that. It is the beginning of the implementation of a new basic strategy, one that will become an ongoing part of the fabric of the organization. A recent article in Forbes Magazine puts it well, It is a journey.
It starts with strategic planning, with all the implications of that process - consultation, discussion, agreement, strategic objectives formulation, champion identification, project scheduling, action plans, monitoring, assessment and re-assessment and ongoing revision and refinement.
Remember that initial definition above - fundamentally changing how you operate and deliver value to customers. Those are fundamental to the business and any changes like that require a strong commitment by the people involved. Definitely not a one-off project.
Thursday, July 05, 2018
Disaster Recovery in the Cloud
When companies move their applications to the cloud, they need to update their Disaster Recovery Plan. The biggest reason for this is that, in the cloud, there is an increased reliance on independent service providers, or vendors. To do the update, the company needs to assemble and review all the contracts with the vendors. They also need to obtain and review all the Service Level Agreements (SLAs) with those vendors. SLAs deal with such issues as performance, uptime, service response, including any penalties against the vendor for service failures.
The vendors provide security and privacy for the data, which needs to be reviewed. Often audit reports are essential to achieve the necessary level of reliance. This is particularly true in cases of shared environments, where assurance need to be obtained about the level of effort going into ensuring that the privacy of the data is protected.
With this background, the DR plan needs to be developed and tested in conjunction with the vendors. For more, click this link.
The vendors provide security and privacy for the data, which needs to be reviewed. Often audit reports are essential to achieve the necessary level of reliance. This is particularly true in cases of shared environments, where assurance need to be obtained about the level of effort going into ensuring that the privacy of the data is protected.
With this background, the DR plan needs to be developed and tested in conjunction with the vendors. For more, click this link.
Friday, June 29, 2018
Business Needs to Look After the People
Possibly the most important issue we face in the modern world is the fact that economic "progress" of the post war (WW2) period has left a lot of people behind. It's true that economic progress has been phenomenal, with vast numbers living better lives than anyone has in history, nevertheless a lot of people have been left behind or, equally importantly, have felt they have been left behind.
This became an issue in the popular mind when we started talking about the 1%. Attention turned to the growing gap in personal incomes such as that between workers and CEOs. Now we see it in the growing populist movements around the world, and it is abundantly clear that the end result of these movements could be, and is likely to be, very ugly.
It also appears to be clear that we cannot rely on governments to resolve this issue. There is growing recognition that business helped to create the problem and needs to help to resolve it.
But what exactly should they do?
PWC recently released a report that offers some guidance on what business can do.
The changes needed in corporate reporting recognize that we are at a crossroads in our society and significant change is required to make it sustainable. Failure to do so will result in a governmental and environmental upheaval .
A better explanation of these guidelines is included in the PWC report.
This became an issue in the popular mind when we started talking about the 1%. Attention turned to the growing gap in personal incomes such as that between workers and CEOs. Now we see it in the growing populist movements around the world, and it is abundantly clear that the end result of these movements could be, and is likely to be, very ugly.
It also appears to be clear that we cannot rely on governments to resolve this issue. There is growing recognition that business helped to create the problem and needs to help to resolve it.
But what exactly should they do?
PWC recently released a report that offers some guidance on what business can do.
- Global connectivity and local initiative must go hand-in-hand
Increasingly corporate performance is measured globally. However, their work has major impacts on local communities. Overall objectives and initiatives need to be aligned between global objectives and local community objectives. - Look beyond financial performance
Corporate performance has traditionally been measured on financial results only. It rings hollow to certain communities, however, when a company announces that it has achieved record profits but has closed several plants, some of which were the lifeblood of those communities. Over recent years, some change in corporate reporting has been made. Corporate performance has increasingly included sustainability reporting, that focuses on impact on the environment. That's great, and is starting to have a positive impact on corporate behaviour. Corporate reporting has also been expanded to include ESG (Environmental, Social and Governance) But it is questionable whether the change in behaviour has extended to the impact on society and communities. The reporting has in many cases, but there is much more to be done. Companies can't be totally responsible for those communities, but they can be held responsible for significant actions they take that impact on the communities. - Technology doesn’t care. But we must.
Technology is people neutral. If people are harmed by the effect of technology in a corporation, only the management and other people in the corporation can help direct that effect to as positive a result as possible. - Educate for the future
Education and retraining must be a responsibility of the companies involved. They are often the first to see the need for new skills and the opportunities for education to develop those skills. They need to play a role in meeting the needs of the future.
The changes needed in corporate reporting recognize that we are at a crossroads in our society and significant change is required to make it sustainable. Failure to do so will result in a governmental and environmental upheaval .
A better explanation of these guidelines is included in the PWC report.
Monday, June 25, 2018
Digital Transformation - Change Management on Steroids
KPMG recently released their 2018 Global Manufacturing Outlook, a survey of 300 CEOs, part of a larger study which involved obtaining data from 1300 CEOs in 11 countries.
The results point to larger trends in business and are relevant far beyond manufacturing. All of the trends we know about are represented there - digital transformation, with growing use of artificial intelligence and the consequent encroachment on human activity by machines. This is probably the biggest worry to people working in manufacturing - or most other businesses.
The survey shows that this will increase in intensity, along with greater integration and collaboration across the world among companies. Of course this leads to the need for people to constantly learn new skills, which is not new but now a permanent part of the landscape. For example, there is a strong indication that the need for data scientists will continue to grow.
We started to hear about change becoming the only constant back in the 1960s. Since then, that has been a fact of life. But now the pace of change has accelerated to the point that it is likely to bring about radical societal change. Of course, this will bring resistance from some quarters. Some people always resist change. So the study identifies a resurgence of territoriality (political and economic) as one of the major risks of doing business over the next twenty years. Of course, we see this already.
In a broad sense, the transformation going on today boils down to a huge exercise in change management, with a need for strong leadership, clear foresight, good strategic planning, and tight management of the risks. It's change management on steroids.
The survey is available on the KPMG website.
The results point to larger trends in business and are relevant far beyond manufacturing. All of the trends we know about are represented there - digital transformation, with growing use of artificial intelligence and the consequent encroachment on human activity by machines. This is probably the biggest worry to people working in manufacturing - or most other businesses.
The survey shows that this will increase in intensity, along with greater integration and collaboration across the world among companies. Of course this leads to the need for people to constantly learn new skills, which is not new but now a permanent part of the landscape. For example, there is a strong indication that the need for data scientists will continue to grow.
We started to hear about change becoming the only constant back in the 1960s. Since then, that has been a fact of life. But now the pace of change has accelerated to the point that it is likely to bring about radical societal change. Of course, this will bring resistance from some quarters. Some people always resist change. So the study identifies a resurgence of territoriality (political and economic) as one of the major risks of doing business over the next twenty years. Of course, we see this already.
In a broad sense, the transformation going on today boils down to a huge exercise in change management, with a need for strong leadership, clear foresight, good strategic planning, and tight management of the risks. It's change management on steroids.
The survey is available on the KPMG website.
Thursday, June 14, 2018
How Analytics can be Used to Fact Check News Items
Companies have been focusing on the capture of big data using tools such as Hadoop for a few years now. However, it appears that many of them still do not identify big data as a strategic resource worthy of enterprise wide analysis. As a result, while there is much data available, it is being used in scattered ways by various departments operating in silos.
Some of the major analytical tools - Cloudera, Hortonworks and Map R have responded with high level and sophisticated offerings using artificial intelligence and machine learning techniques. They feel this will make the tools easier to use and more powerful.
A good example come from Cloudera, in the form of their application Reuters Tracer. This remarkable tool is used by Reuters News Agency for analyzing twitter feeds, fact checking them and producing results in a matter of milliseconds.
They recognize that Twitter has become a major news source but that it is difficult for people to sort through all the "noise" and determine what is true and what isn't. Reuters Tracer "processes about 13 million tweets daily, capturing events as they happen and determining: is an event true, is it newsworthy, and what is the scope and impact of that event."
"If a tweet is an opinion, Reuters Tracer can determine whether it comes from a recognized expert, and is therefore of news value. In delivering its results, it provides journalists and businesses with a 'newsworthiness score' for each event that rates its assessed level of accuracy and credibility." These results can be produced in as little as 40 milliseconds - basically real time.
Fact checking in the old sense has become something of an industry Reuters Trace can automate, if not all, much of the fact checking needed to provide a sound basis for decision making.
Many companies are considering applications like this for their own business purposes, perhaps with a big data source like customer or supplier activity with analytics embedded to focus on key strategic decisions. Auditors can definitely use tools like this to improve the analytical techniques used in audits - something that is badly needed.
For more, check out these references - A recent article on the subject and the Cloudera website.
Some of the major analytical tools - Cloudera, Hortonworks and Map R have responded with high level and sophisticated offerings using artificial intelligence and machine learning techniques. They feel this will make the tools easier to use and more powerful.
A good example come from Cloudera, in the form of their application Reuters Tracer. This remarkable tool is used by Reuters News Agency for analyzing twitter feeds, fact checking them and producing results in a matter of milliseconds.
They recognize that Twitter has become a major news source but that it is difficult for people to sort through all the "noise" and determine what is true and what isn't. Reuters Tracer "processes about 13 million tweets daily, capturing events as they happen and determining: is an event true, is it newsworthy, and what is the scope and impact of that event."
"If a tweet is an opinion, Reuters Tracer can determine whether it comes from a recognized expert, and is therefore of news value. In delivering its results, it provides journalists and businesses with a 'newsworthiness score' for each event that rates its assessed level of accuracy and credibility." These results can be produced in as little as 40 milliseconds - basically real time.
Fact checking in the old sense has become something of an industry Reuters Trace can automate, if not all, much of the fact checking needed to provide a sound basis for decision making.
Many companies are considering applications like this for their own business purposes, perhaps with a big data source like customer or supplier activity with analytics embedded to focus on key strategic decisions. Auditors can definitely use tools like this to improve the analytical techniques used in audits - something that is badly needed.
For more, check out these references - A recent article on the subject and the Cloudera website.
Monday, June 11, 2018
Digital Transformation requires BPR
In the current frantic push of enterprises to digitize their operations, in the form of digital transformation, there is one old process they can't get away from and that's Business Process Reenginering (BPR).
BPR has been around forever, but really came into prominence during the heyday of big ERP (Enterprise Resource Planning) implementations in the 80s and 90s. Those implementations were very difficult and costly and it soon became obvious that BPR was necessary in order to fit the technology and the business together and at the same time make best use of the technology to optimize the business.
Now, the situation of ERP systems is very different. They are well established in, and in many cases, central to the processes of the business. Where once they were the disruptive technology, now they are the legacy systems. Many companies are moving them to the cloud.
Cloud based ERP systems are different from those legacy ERP systems. Partly because ERP has evolved in recent years, and partly because of having transformed to cloud applications, which require new and different operational and security processes.
In the process of digital transformation, many organizations are now using DevOps, which involve automating the processes of software development and IT teams. Since the IT teams must necessarily be concerned with BRP, the DevOps processes must be consistent with the BRP efforts, particularly where they meet.
All of this means that digital transformation can be a tremendously complex affair.
Here's another article on this general topic.
BPR has been around forever, but really came into prominence during the heyday of big ERP (Enterprise Resource Planning) implementations in the 80s and 90s. Those implementations were very difficult and costly and it soon became obvious that BPR was necessary in order to fit the technology and the business together and at the same time make best use of the technology to optimize the business.
Now, the situation of ERP systems is very different. They are well established in, and in many cases, central to the processes of the business. Where once they were the disruptive technology, now they are the legacy systems. Many companies are moving them to the cloud.
Cloud based ERP systems are different from those legacy ERP systems. Partly because ERP has evolved in recent years, and partly because of having transformed to cloud applications, which require new and different operational and security processes.
In the process of digital transformation, many organizations are now using DevOps, which involve automating the processes of software development and IT teams. Since the IT teams must necessarily be concerned with BRP, the DevOps processes must be consistent with the BRP efforts, particularly where they meet.
All of this means that digital transformation can be a tremendously complex affair.
Here's another article on this general topic.
Thursday, June 07, 2018
Blockchain and the Accounting Revolution
It is being said that blockchain will revolutionize accounting, because it enables an independent record of all transactions in a separate distributed ledger which is available, shared, independently recorded and unchangeable. Essentially, the entries would flow from the record of smart contracts, under which commitments entered into by parties to a transaction would become part of the shared distributed ledger and then the settlement of that contract would be automatically implemented by the contract and also recorded in the distributed ledger. Thus all parties to the contract would have a record of the entire transaction stream from beginning to end. Since these entries flow from the agreed contract and are then generated by that contract independently of the parties, it forms a tremendously valuable part of the audit trail for those transactions. Some have even suggested that this would eliminate the need for auditors, and although this is an overstatement of its effect, there is absolutely no doubt that it will transform the way that auditors work.
The aspect of blockchain that involves creation of the distributed ledger has been referred to as triple-entry accounting. For those with some knowledge of accounting history, this is a jarring nomenclature, as it evokes memories of Yuji Ijiri, the noted professor at Carnegie Mellon University who published a monograph of that name in 1982 along with a paper in The Accounting Review in 1986 outlining the nature of triple-entry accounting. Some academic writing has focused on this similarity and asked the question is the triple-entry accounting of Ijiri the same idea as that of blockchain? Some have said no and others yes, at least conceptually.
It’s not a simple issue. The essence of Ijiri’s model was the introduction of a new measure of performance called momentum and a Statement of Force that shows the rate of change in the organization. The addition of the Force Statement to the traditional Balance sheet and Income statement gives rise to the triple entry concept.
In blockchain, the third element to the accounting process arises from the creation of the distributed ledger that shows a complete record of all transactions in the enterprise – a very different concept.
However, the distributed ledger could easily be used to create Force Statements as it contains verifiable dates of all events through cryptographic methods. So, a logical conclusion is that the Ijiri and blockchain concepts are very different but at the same time that the two are very compatible. Will the Ijiri concept make a comeback? Who knows?
Blockchain is being adopted quite extensively, particularly in situations where smart contracts make sense. And an industry is forming around it. But it has not reached the level of general adoption across the spectrum of accounting. Whether it will remains an open question. But there is no question that it will be a major force in accounting providing new and better accounting controls and perhaps leading to the extension of accounting into new dimensions, like those of Ijiri, or something like that.
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