Editorial Guidelines

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Cutter Business Technology Journal — Calls for Papers

For nearly 30 years, the monthly Cutter Business Technology Journal has served as a forum for thought leaders in academia and industry to present innovative ideas and solutions to the critical issues facing business-technology professionals. Please consider sharing your insight with us for the following topics. For questions or to send article ideas, please contact Christine Generali at cgenerali[at]cutter[dot]com.

Editorial Guidelines   Editorial Calendar   Sample Issue

Digital Architecture

Guest Editor: Gar Mac Críosta
Abstract Deadline: Aug 23, 2019
Article Deadline: September 27, 2019

Digital Architecture means many things to many people. As I was thinking about this issue, I polled some colleagues to understand what they understood Digital Architecture to mean. The responses are interesting, varied and probably illustrative of the challenge we face when all the good words have been abused and misused.

  • "Architecture for the Digital Age" – The Visionary – Public Service Digital Delivery Lead
  • "An underlying architecture used to deliver a digital transformation strategy/objective" – The Consultant – Head of Product Development
  • "The fluffy stuff inside of the cloud" – The Cynic – CISO Financial Services
  • "A waste of energy" – [writing about it] – The Anti-waffler – The Chief Architect Public Services
  • "Start with Intel 8086 V Motorola 68000 architecture [everything else evolves from that]" – The Builder – Solution Architecture Financial Services
  • "Use of digital innovation in various workplace scenarios" – The Aspiring Innovator – Solution Architecture Financial Services
  • "Turning Technology into Business Transformation" – The Strategist – VP Architecture Product Company
  • "An organising construct that promotes and preserves order in the face of the natural tendency towards entropy" – The Pragmatist – Digital Architect Large Tech Company

Rather than argue about the definition, let’s summarize the debate like this: a digital architecture enables a digital business to effectively extract value from the digital technologies it has deployed, to create an opportunity or amplify an existing advantage. The dynamics of a digital business are fundamentally different than the dynamics of a traditional business, therefore, a digital architecture must enable, address and support the needs of a digital business.

Opportunities open and close, creating transient advantages [Rita Gunther McGrath, HBR]. Enterprises must be able to enter new markets, establish an advantage, extract value from that advantage, and exit once that advantage no longer exists. I liken it to surfing a wave, pulling all the energy from the barrel, and exiting before being crushed on the reef.

A forthcoming issue of Cutter Business Technology Journal sets the scene for how software is tearing up the script for enterprises, business models, value chains and industries. An increase in market turbulence, changing market dynamics, unpredictable customer expectations, competitor behaviour, low-end disruption, reduced barriers to entry, greater challenges creating strategic moats, impacts of aggregators, and multi-sided platforms are all changing the game.

With the fast moving, ever-evolving developments in ‘as a service’ offerings, cloud scale infrastructures, IoT, and AI/ML, a super-hyped environment is being created. This hype is then intensified with release cadences measured in days and weeks thus setting the scene for a perfect storm. As described in my recent article, No More Snake Oil: Architecting Agility in a Complex Environment, co-written with Barry O’Reilly, we stated that “rather than aiming to control, or to remove control, we should seek to build systems, both technical and business, that aim to be antifragile to change.” I believe that this must become an underpinning goal of all digital architectures.

The variety, pace, and unavoidable complexity of these changes require a digital architecture that can respond positively in the face of these drivers. The demands of business on these architectures moving from a supply-based, phased IT delivery model to a business, demand-driven, continuous delivery model fundamentally changes the variables underpinning classic architectures. Volatility, uncertainty, complexity & ambiguity (VUCA) are inherent characteristics of this world, mocking our sacred cow, prediction-based architectures.

This issue of Cutter Business Technology Journal will explore how a business can successfully transform its current architecture to a digital architecture and the key issues, approaches, strategies and potential roadblocks associated with this transition.

Articles ideas may include (but are not limited to) the following:

  • What are some of the benefits, opportunities, and challenges of transforming to a digital architecture?
  • What processes, techniques, and frameworks can be used to develop a digital architecture?
  • How do we design better business and operating models to ensure we are delivering value to our customers?
  • What does a digital architecture look like? How is it different? How does it address the demands imposed by the dynamics of a digital business?
  • How do we organise to deliver on transient advantages?
  • How do we evaluate the effectiveness of a digital architecture?
  • Is low-code/no-code a viable strategy for organisations with no engineering culture building digital architectures?
  • How do we scale capacity in the face of internal/local talent challenges?
  • What does a digital architecture platform look like?
  • What key decisions/trade-offs need to be considered in building a digital architecture?
  • How can legacy systems be migrated or replaced to transform to a new digital architecture?
  • How do we build digital architectures that make exits and pivots easier?
  • What are the differences and transitions for digital architectures from explore and invent stages to exploit and scale?
  • What governance, compliance and control mechanisms are a must?
  • What techniques and approaches are needed to build digital architectures that leverage/contain/enable the constant flow of new technologies emerging on a daily basis? How can we measure the value of a digital architecture? Are there key metrics that can be used to measure value? [e.g. 4 key metrics - Accelerate ]

Submit article ideas here!

ARTICLE IDEAS. Please send article ideas to Gar Mac Críosta and Christine Generali (cgenerali@cutter.com and gar@businessmodeladventures.com) including an abstract and short article outline showing major discussion points. Accepted articles due September 27, 2019. Final article length is typically 2,000-3,500 words plus graphics. More editorial guidelines.

AI: Avoiding and Addressing Unintended Consequences

Guest Editor: Lou Mazzucchelli
Abstract Deadline: Aug 3, 2019
Article Deadline: September 6, 2019

I’ve been around long enough to see at least three AI waves - the first in the late 70s, when LISP machines emerged. I remember talking with Patrick Winston at Symbolics, who blithely remarked that, “in the future, every computer will be a LISP machine.” (He was right, but only because general-purpose architectures later got fast enough to run LISP at scale.)

I characterize this first wave as “our AI reach exceeded our hardware performance grasp” - many projects were tried, very few succeeded, and the first wave subsided.

This does not mean that AI disappeared, but it went offstage and people worked on it in the wings. I’ve discussed this phenomenon at length for years.

The second AI wave was ushered in by natural language recognition. Drastically increased CPU cost/performance allowed designers to create devices that do a reasonable job of dealing with voice in ever-less-restricted domain areas. This technology has been further enhanced by the harbinger of the third AI wave.

The third AI wave is being led by machine learning (ML). ML generates responses using directed pattern-matching and feedback to satisfy a goal, like “detect an edge” or “indicate this is a picture of a cat,” or “indicate this human is a felon.” These systems gain “skill” ingesting ever-larger data sets (“training”). We feed the systems ever-larger data sets to improve this training. We have observed some spectacular results (world class Go-playing systems “grown” in weeks, etc). However, we are at a loss to explain, at a micro level, how decisions in these systems are made.

In the human world, accepting a decision without questioning the facts leading up to it is a definition of “trust.” By that definition, we are placing a lot of trust in ML systems that are increasingly running the joint, from Google pet searches to hiring decisions. I see several problems emerging:

  1. Where is the record of initial training approaches for any ML system? We cannot be sure that bias has not been introduced into the system without knowing initial conditions and weights.
  2. Where is the record of changes in response to training input, and how is that input supplied or collected? Who gets to decide?
  3. Where does liability lie for ML mis-characterizations?

While we can laugh at stories about ML misidentifying US Congress members as criminals, life becomes more difficult for someone denied a job or promotion by an opaque ML-based system.

Perhaps the most dangerous aspect of the third wave of AI is its apparent efficacy. Putting a monster in a tuxedo may make it appear less threatening, but likely only masks other problems.

Getting ahead of the issues around ML from the start is easier than dealing with negative consequences after the fact. An upcoming issue of Cutter Business Technology Journal will explore ways to deal with problems of transparency, responsibility, and consequences for users and designers of new AI-based systems.

Topics of discussion may include (but are not limited to) the following:

  • What are some examples of unintended consequences of AI and how can they be prevented or minimized?
  • How can the fairness of algorithms be ensured? Is it even possible? How can the transparency of AI algorithms be improved?
  • What types of organizational controls/protocols should be implemented to improve transparency? 
  • What type of organizational governance is needed?
  • Where does liability lie for ML mis-characterizations?
  • How can the introduction of bias into a system be addressed?
  • What kind of risks can stem from the use of AI/ML systems? How can they be identified and mitigated?
  • How can organizations prepare themselves for any possible fallout from AI/ML?
  • How can you stop algorithms from being manipulated?
  • How should the risk of security breaches be managed?

Submit article ideas here!

ARTICLE IDEAS. Please send article ideas to Lou Mazzucchelli and Christine Generali (cgenerali@cutter.com and l.mazz@verizon.net) including an abstract and short article outline showing major discussion points. Accepted articles due September 6, 2019. Final article length is typically 2,000-3,500 words plus graphics. More editorial guidelines.

1. https://www.techrepublic.com/article/amazon-ai-misidentifies-congress-as-criminals-proves-its-not-ready-for-enterprise/
2. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G

Call for Papers: Is Software Eating the World?

Guest Editor: Greg Smith
Abstract Deadline: July 6, 2019
Article Deadline: August 3, 2019

I have been increasingly convinced in the last couple of years that Marc Andreessen’s “Why Software is Eating the World” essay is coming true. Combined with AI, the rise of software represents the biggest single challenge and opportunity to business.

Spurred by rapid-fire technological innovation, the present-day software revolution has not only propelled the growth of new software organizations; it has motivated traditional businesses, in pursuit of greater profitability, greater market share and increased enterprise value to transform into software organizations, as well.

What’s the play for established incumbents that have yet to digitally transform? How can they compete with rival software organizations who have the potential to disrupt (or have already disrupted) their market? What resources are needed to transform their operations and infrastructure to a digitally-enabled one?

Eric Ries defines a pivot as a change of strategy without a change of purpose; you can’t have a pivot without vision. This feels like a good way to think about the change needed for most businesses with respect to software. What type of leadership and strategic vision is needed to effect a successful transformation?

An upcoming issue of Cutter Business Technology Journal with Guest Editor Greg Smith seeks to address the complexities faced by today’s organizations competing in our software-driven world.

Topics of discussion may include (but are not limited to) the above issues as well as the following:

  • What happens when your business has to become a software company?
  • What happens if you are innovating in a physical system and your competitor is innovating in a software system?
  • If innovation in your business is now software-driven, can you still outsource this to third parties?
  • What are the measures and indicators that indicate whether a business is thriving or failing as a software-enabled organisation?
  • What barriers might keep you from transforming your legacy systems successfully? How can these barriers be addressed?
  • How does the leadership team need to change to reflect this? Who on the exec team understands this world and how do decision making processes get remade?
  • What happens when you separate the software system from the physical activity system and it potentially becomes worth more than the legacy business?

Submit article ideas here!

ARTICLE IDEAS. Please send article ideas to Greg Smith and Christine Generali (cgenerali@cutter.com and Smith.Greg@adlittle.com) including an abstract and short article outline showing major discussion points. Accepted articles due August 3, 2019. Final article length is typically 2,000-3,500 words plus graphics. More editorial guidelines.

Editorial Guidelines

These notes are intended to give authors some guidance and direction for articles submitted to Cutter Business Technology Journal (CBTJ) for publication.

Length: The average article in CBTJ is 2,000-3,500 words, unless otherwise specified by the Group Publisher.

Article Format: Please send your article in word document format for editing purposes. Please do not send it as a PDF.

Editorial: Cutter Business Technology Journal is professionally edited by our team who evaluates articles for content, substance, grammar, and style and provides valuable feedback so that authors can revise and improve their papers before publication. Publishing turnaround times are short. Articles are also peer-reviewed by the Guest Editor who is an expert in the field.

Audience: Publishing with Cutter affords the opportunity to present your insights and research to a global corporate audience that is highly interested in emerging developments. Typical readers of CBTJ range from CIOs, CTOs, business techcnology executives and vice presidents to directors, technology managers, project leaders, and very senior technical staff. Most work in fairly large organizations: Fortune 500 organizations, universities, large computer vendors, NGOs/IGOs, and government agencies and spanning industries such as finance and banking, education, energy, entertainment, food, government, healthcare, insurance, and manufacturing. 48% of our readership is outside of the US (15% from Canada, 14% Europe, 5% Australia/NZ, 14% elsewhere).

Editorial advice: Introductory-level, tutorial coverage of a topic is not very popular with our readership because they're fairly senior people. Delete the introductory "fluff" and get to the meat of the topic. Assume you're writing for someone who has been in the industry for 10 to 20 years, is very busy, and very impatient. Assume he or she is mentally asking, while reading your article, "What's the point? What do I do with this information?" Apply the "So what?" test to everything you write.

General comments: We enjoy controversy and strong opinion; we like the fact that we can provide an alternative to standard "refereed" journals that sanitize articles. Because we don't carry any advertising, we can publish critical or negative comments about specific vendors or products. However, we obviously don't want to publish anything libelous or slanderous. Conversely, we don't publish self-serving commercial messages praising one's own product or service.

Style, grammar, and mechanics: For advice on good writing style, we recommend Merriam-Webster's Collegiate Dictionary, 11th ed., The Chicago Manual of Style, and The Elements of Style (Strunk and White). We are fanatics about the editorial quality of Cutter Business Technology Journal; anything you can do to help us in this regard will be greatly appreciated.

Graphics: Please keep your use of graphics to a minimum and submit original, editable files (not static images). Preferred formats include MS Excel for graphs, MS Word for tables (1-2 pages), and MS PowerPoint/MS Word/Adobe Illustrator (v17 or less) for vector art. Please send all other types as high-res JPEG, PDF, PNG, or TIFF. All images owned by another party may only be used with owner’s permission. It is the author’s responsibility to obtain permission. Copying images off the Internet without permission infringes on copyright and is unacceptable for publication.

All graphics (figures and tables) must include captions and a reference within the text; for example, “(see Figure 1)” or “Figure 1 illustrates….” Please note that we may remove graphics deemed unnecessary. Please be minimalistic in your design: limit colors, shadings, and typefaces. For additional questions, please contact Linda Dias (ldias@cutter.com).

Deadlines: The deadline you agree to when you commit to writing an article is a "hard" deadline; if you're going to be late, let us know and we'll negotiate a mutually agreeable delivery date. If the deadline passes without our having heard from you, we will assume that you have vanished and are unable to provide the article.

Editorial process: Once we get your article, we commence two parallel editorial passes: one for content (by the guest editor) and one for substance, grammar, and style (by our managing editor, Cindy Swain (cswain@cutter.com). Either or both of these editorial reviews may result in some questions or feedback from us. In any case, we will send you a first draft "page proof" of your article for your review and approval. Articles published in the journal must meet certain criteria relating to audience, technical content, and presentation. In the unlikely occurrence that, upon editorial review, your completed article does not meet with these requirements, Cutter Consortium reserves the right to decline the publishing of your article in the journal.

Biographical sketch: At the end of each CBTJ article, we like to include a brief (200 words or less) biographical sketch of each author along with email address of author(s). Click here for a sample. We also like to provide a color headshot. Please include a high-res color headshot (at least 300x300 pixels in size) of each author. We accept formal or casual photos that present authors in a professional manner. For samples, see the “Meet the Cutter Experts” section at https://www.cutter.com/our-experts.

Copyrights: When you submit an article to us, you warrant that you (or your employer) are the sole owner of the article, that you have full power and authority to copyright it and publish it, and that it has not been previously published elsewhere. You also warrant that it does not infringe on any copyright, violate any property rights, or contain scandalous, libelous, or unlawful matter. If you request, we will grant you, or your designee, copyright of the article providing you extend first-time publishing privileges, in print and electronic formats to Cutter Information LLC; otherwise, the article will be copyrighted by Cutter Information LLC.

Sourcing Content: When you do draw on the work of other authors and researchers, cite your sources accordingly in the relevant part of the text (using endnote numbers or hyperlinks). Given that Cutter Consortium has no relationships with vendors, we discourage the use of references, quotes, statistics, and figures from analyst/research firms with vendor ties (Gartner, MetaGroup, Yankee Group, Forrester, IDC, among others), as the data may be biased. If you feel information from one of these sources is critical to your article, please bring it to our attention early in the editorial process and we will be happy to discuss the issue. Note that Cutter Consortium conducts studies and surveys occasionally in its various practice areas. This data is available for use in your articles or reports. If there is specific data you are looking for to support an argument, please contact us for more information. We will be happy to send you any relevant data.

Keep in mind that if your article uses too many sources, it is often an indicator that your piece summarizes research too heavily and lacks original thought. Remember our readers are interested in your insights; above all, speak in an expert voice.

Promotion: We will, at your request, provide you with a link to share with your colleagues and contacts where they can register and receive a complimentary PDF download of your complete article. You can post this link on your website, blog, tweet it, promote on social networks, etc. It is only acceptable for your final, Cutter-edited article to be downloaded from the Cutter site, and it may not be posted anywhere else without express permission from Cutter*. You may also excerpt a passage or section from your article with attribution to CBTJ, and link it back to the full article on the Cutter website. We also ask that once the issue is published, that you do not post the entire issue PDF on any websites or social media sites out of respect for our paid clients/subscribers.

* CBTJ accepts no advertising, has no outside sponsorship, and is completely subscriber-supported. In order for us to continue providing this venue for debate to our authors, and your valuable insights to our subscribers, we thank you in advance for your respect of our copyright.

Author Compensation: We are pleased to offer Journal authors an online, one year complimentary subscription to Cutter Business Technology Journal upon the signing of the license agreement. In addition, we occasionally pull excerpts, along with the author's bio, to include in our weekly Cutter Edge email newsletter, which reaches another 12,000 readers. We'd also be pleased to quote you, or passages from your article, in Cutter press releases. If you plan to be speaking at industry conferences, we can arrange to make copies of the issue in which you're published available for attendees of those speaking engagements -- furthering your own promotional efforts.

Reprints: If you would like an authorized reprint of your article for promotional purposes or to post on your website, contact Customer Service (Tel: +1 781 648 8700; E-mail: service@cutter.com) for more information. We can arrange for a reprint with the CBTJ cover, logo, and other details.

Endnotes/References: When you draw on the work of other authors and researchers, please cite your sources. All sources/side commentary must be noted in relevant part of text (using endnote numbers) and listed in sequential order (i.e., order of appearance, not alphabetical order) at end of article in “Endnotes.” All sources should include basic publishing information (i.e., author(s) name(s), complete title, publisher, date, and hyperlink and/or URL). Sources can be repeated but must be listed as a new endnote. The following are examples of various types of endnotes:

1DeMarco, Tom, and Timothy Lister. Waltzing with Bears: Managing Risk on Software Projects. Dorset House, 2003.

2In this survey, “innovation” refers to any new initiatives to introduce innovative, leading-edge, or unconventional software project development methods, processes, tools, or techniques.

3Hall, Curt. “AI & Machine Learning in the Enterprise, Part XI: Success of AI Application Development Efforts.” Cutter Consortium Data Analytics & Digital Technologies, Executive Update, Vol. 19, No. 3, 2019.

4DeMarco and Lister (see 1).

   5Smart grid.” Wikipedia.

Editorial Calendar

Month Topic Guest Editor
October 2019 Fintech/Blockchain Karolina Marzantowicz
September 2019 Digital Architecture Gar Mac Críosta
August 2019 AI: Avoiding and Addressing Unintended Consequences Lou Mazzucchelli
July 2019 Is Software Eating the World? Greg Smith
June 2019 Industry 4.0 Keng Siau
May 2019 Cutting Edge Agile II Alistair Cockburn
April 2019 Technology-Empowered Solutions: Redefining Decision Support Dr. Karen Neville and Dr. Andrew Pope
March 2019 Cutting Edge Agile Alistair Cockburn
February 2019 The Next Frontier in Automation: Opportunities, Challenges and Impact San Murugesan
January 2019 Business Technology Trends & Predictions 2019 Cutter Consortium
November/December 2018 Fintech: Emerging Trends, Future Directions Steve Andriole
October 2018 Riding the Next Wave of Cloud Computing Frank Khan Sullivan
September 2018 Building a Digital Business Starts with Data Barry Devlin
August 2018 The Critical Need for Governance Claude Baudoin
July 2018 Architecture + Agile: The Yin & Yang of Organizational Agility Whynde Kuehn
June 2018 Fog/Edge Computing: Opportunities, Case Studies, Challenges  Cutter Consortium
May 2018 Transforming the Customer Experience Jeanne Bliss
April 2018 Blockchain: Where Are We Now? Where Are We Headed? Phil O'Reilly
March 2018 A Disciplined Agile Approach to Business Agility Scott Ambler and Mark Lines
February 2018 AI: Fear It, Face It, or Embrace It San Murugesan
January 2018 Business Technology Trends and Predictions 2018 Cutter Consortium
December 2017 Change Leadership in a Digital Era Sheila Cox
October/November 2017 Trends in Big Data Technologies and Analytics Bhuvan Unhelkar
September 2017 Insurtech: Reinventing the Insurance Industry Steve Andriole
August 2017 Agile Leadership: Foundation for Organizational Agility Don McIntyre
July 2017 The Industrial Internet: Driving Digital Transformation C. Patrikakis
June 2017 Leveraging Enterprise Architecture for Digital Disruption Roger Evernden
May 2017 Beyond Fintech: New Frontiers Phil O'Reilly
April 2017 The Frontier of Fintech Innovation Phil O'Reilly
March 2017 Business Opportunities in the New Digital Age San Murugesan
February 2017 Information Superiority and Digital Capital Borys Stokalski and Bogumil Kaminski
January 2017 The 21st Century Technology Leader Paul Clermont
December 2016 Technology Trends, Predictions, and Reflections 2017 Cutter Consortium
November 2016 FinTech and the Digitization of Financial Services Philip O'Reilly
October 2016 Cognitive Computing: Applications, Trends, and Implications Paul Harmon
August/September 2016 Business-Driven Digital Transformation Whynde Kuehn
July 2016 Security in the Internet of Everything Era Patrikakis Charlalampos and George Loukas
June 2016 Cultivating Success in Big Data Analytics Barry Devlin
May 2016 The Role of Ethics in Algorithm Design Robert Charette
April 2016 IoT Data Management and Analytics Bhuvan Unhelkar and San Murugesan
March 2016 Technical Debt: The Continued Burden On Software Innovation Tom Grant
February 2016 Disruption and Emergence: What do they mean for Enterprise Architecture? Roger Evernden
January 2016 Technology Trends and Predictions: 2016 Cutter Consortium