23 new resources
EA planning helps link IT with business users, especially for digital transformation projects, according to a recent CompTIA survey.
Thanks to cloud, lines of business are increasingly engaging in technical activity. But without deep architectural expertise, things could get very messy -- and expensive.
A new generation of IT leader has been arriving on the scene, more in-tune with the business, more collaborative, and with better soft skills, but a legacy tangle of tech stands in the way of moving towards the future.
The concept of an open enterprise architecture that links plant floor operations with business operations across an entire corporate entity has been around for a while in many industrial sectors. But making this concept a reality remains challenging. This is particularly true for those companies that lack huge IT staffs or budgets. IIoT, with its compelling promise of accessing, aggregating, and analyzing data from previously stranded assets and systems to improve decision support and thus business performance, represents a further disruption.
The digital twin is a burning topic within manufacturing industries. While it is often included in lists of today’s most strategic technologies, it has yet to be widely adopted in practice. Matti Kemppainen, Director of Research and Innovation at Konecranes, discusses the implications for manufacturers of the rolling out of digital twins. According to Kemppainen, digital twins are set to be a new standard for industry.
Creative leaders and innovators are thinking about design thinking in more mature ways. Moving away from a sole emphasis on language and learning, they are increasingly focusing on questions of application, ownership, and impact.
Promoting seamless services and data flows for European public administrations. The EIF gives guidance, through a set of recommendations, to public administrations on how to improve governance of their interoperability activities, establish cross-organisational relationships, streamline processes supporting end-to-end digital services, and ensure that existing and new legislation do not compromise interoperability efforts.
Companies may be able to get digital transformations off the ground by separating digital from conventional IT, but that approach is not sustainable. Here’s a better way. Technology organizations are now expected to play a central role in helping companies capitalize on new digital capabilities - connectivity, advanced analytics, and automation, for instance. These capabilities can help them build deeper relationships with customers, launch new business models, make processes more efficient, and make better decisions.
These fundamental guidelines, drawn from experience, can help you reshape your organization to fit your business strategy.
As it is today, many of product lifecycle processes, from design, to process planning and engineering, manufacturing are siloed because different software tools, models and data representations are used, and often by many different teams across different organizations and geographic locations. To achieve the goals of smart manufacturing, these product lifecycle processes and manufacturing functions need to be connected and integrated to increase process automation, responsiveness and efficiency, and to reduce human errors. Furthermore, because of connected smart products, this lifecycle is now being extended beyond the four-wall of the factories, into customers’ operation environment. Digital thread refers to the communication framework for integrating production functions across the product chain and integrating product data for digital models. It does so by enabling data flow and integrated view of the product’s data throughout its lifecycle across different stages, from design, to manufacturing, and now to operation, and even to end-of-life and recycling of the product
Digitization involves standardizing business processes and is associated with cost cutting and operational excellence. In essence, it imposes discipline on business processes that, over the years, were executed by individual heroes in a variety of creative (but not always optimal) ways. SAP, PeopleSoft, and other integrated software packages that burst onto the scene in the 1990s helped lead the way into more digitizing, but it remains a painful process. Today, companies are confronting something new and different: digital. Digital, of course, is an adjective. It refers to a host of powerful, accessible, and potentially game-changing technologies like social, mobile, cloud, analytics, internet of things, cognitive computing, and biometrics. It also refers to the transformation that companies must undergo to take advantage of the opportunities these technologies create. A digital transformation involves rethinking the company’s value proposition, not just its operations. A digital company innovates to deliver enhanced products, services, and customer engagement. Digital is exciting, thrilling — and a bit unnerving!
Achieving change in a world ever more defined by complexity is difficult. We face an array of complex ‘wicked’ problems, from an ageing population to climate change to intergenerational cycles of poverty. It can often seem that these challenges are insurmountable and that we lack the ability to make meaningful change. To find opportunity in challenge will require reimagining the ways that we currently think about innovation and design. The narrative around a ‘fourth industrial revolution’ risks narrowing the focus of innovation to technology which would locate innovation-led growth solely in the outputs of universities and research institutes, or technology clusters like Cambridge’s Silicon Fen. While these are a vital piece of the UK’s innovation jigsaw, they are not the whole picture. Enterprises large and small across sectors and regions need to also be part of the innovation mix. The UK has long been at the forefront of design, a rich heritage that permeates a diverse range of sectors. Design thinking methodologies are deployed in service, policy and governance design across sectors, not merely product design. Harnessing the power of this creative capacity will be crucial to generating the innovative solutions required to tackle pressing social challenges. But design thinking alone will not be enough. The core insight of this paper is that solving our most complex problems will require augmenting design thinking with a systems thinking approach as the basis for action. While design thinking has proved itself to be successful in the realm of creating new products and services, the challenge is how to support innovations to enter and actively shape the complex systems that surround wicked social challenges. Great design doesn’t always generate impact. As we show in this report, innovations attempting to scale and create systemic change often hit barriers to change, sending them catapulting back to square one. We call this the ‘system immune response’. The particular barriers will differ dependent on context, but might be cultural, regulatory, personalitydriven or otherwise. This report argues that innovations for the public good are susceptible to the system immune response because there is a deficit of systems thinking in design methodologies. This report introduces a new RSA model of ‘think like a system, act like an entrepreneur’ as a way of marrying design and systems thinking. At its most simple, this is a method of developing a deep understanding of the system being targeted for impact and then identifying the most promising opportunities to change based on that analysis – the entrepreneurial part. By appreciating factors like power dynamics, competing incentives and cultural norms, innovators can prepare themselves for barriers to change, and find the entrepreneurial routes around them to successfully affect system change.
The developers vs enterprise architects showdown: You shall know us by our trail of diagrams Old McDonald had a server farm, EA, EA, Oh!
Three years ago, demand for enterprise architects — those who focus on building a holistic view of an organization's strategy, processes, information, and IT assets in order to support the most efficient and secure IT environment — was declining. Some were whispering that the days of the architects were over. But this unique skillset has recently staged a major comeback: According to the Harvey Nash/KPMG 2017 CIO Survey, enterprise architecture (EA) has become the fastest-growing, in-demand skillset in technology, up 26% from last year’s report.
The challenges of aligning IT with business triggered the attention towards Enterprise Architecture (EA). Despite the increase interest of academic scholars in EA, there is scarcity of studies that provide an up to date comprehensive research perspective view. The purpose of this study is to examine the research methodologies and theories utilized in EA studies from 2010 to 2016. The study employed Systematic Literature Review (SLR) as method to explore and analyze the literature of EA. The study revealed the research approaches and data collection methods utilized in EA. It shows that case study approach and interviews are the highly used compared to other research approaches and data collection instruments. Furthermore, it pointed out the low employment of theories in EA studies. The study is contributing to the body of knowledge by providing a foundation for novice researchers in the area of EA through detailed discussions of research methodologies and theories which are expected to support them in designing future studies.
The way we interact with business is changing, from online to offline. Organizations are going through fundamental upheaval. At the heart of this change is the business architect. Once considered a niche role, the business architect is now one that most organisations have on the employee headcount, for tackling strategy to leading and shaping transformation. In this paper, authors Mike Clark, founder of Cohesion 360 and Whynde Kuehn, Principal of S2E Consulting Inc., answer some of these core questions, with the aim of laying down a blueprint for the evolution of business architecture and the business architect role for business architecture practitioners, for organisations, and for the business architecture discipline overall.
Sustainability through Innovations Of Enterprise Architecture (EA) in Public Sector’s Management: Issues and Challenges
Innovations through Enterprise Architecture (EA) require a transformation in public sector’s management. EA has been identified as one of the prime initiatives towards public sector transformation. EA implementation is highly recommended to execute efficient and effective public service delivery. However, building upon several public sector agencies that had implemented these initiatives, EA implementation in Malaysian Public Sector (MPS) was reported as unfavourable. This study aims to identify related issues and challenges towards sustainability of EA implementation. A qualitative research approach was employed in this study. Semi structured interview was held involving five EA experts. From the analysis, six related issues such as (i) absence of the mandate from government to implement EA initiatives (ii) improper EA governance leading to difficulty in managing EA implementation; (iii) absence of EA tool to maintain EA document; (iv) lack of EA awareness (v) lack of EA readiness and (vi) limited knowledge and skills on EA among the team were discerned in sustaining EA practices. With regard to the practical implication, this paper can serve as reference in EA implementation in the public sector.
The IoT is already boosting a significant amount of innovation across various industries by providing near real-time insight into rich and contextual environmental data across a wide range of complex scenarios, such as the industrial internet, smart homes and cities, energy management, agriculture, intelligent transport systems, connected health and smart retail. To identify the essential building blocks of IoT architecture, it’s helpful to review the IoT reference architectures that have been created by several bodies and industry consortia.
Artificial intelligence has become one of the biggest technological developments in business in recent years, but the field is still largely shrouded in uncertainty. While expectations run sky-high, what are businesses actually doing now? Anew report by BCG and MIT's Sloan Management Review aims to demystify AI in business and take stock of current industry adoption. The report is based on a global survey of more than 3,000 executives and in-depth interviews with more than 30 technology experts and executives. Its goal is to present a realistic baseline that allows companies to compare their AI efforts and ambitions and to provide guidance for things to come.
Technology has long been used to improve how we learn, but today's digital advances, particularly with social media, have taken learning in powerful new -- and for some -- entirely unexpected directions.
There is no question that artificial intelligence (AI) is presenting huge opportunities for companies to automate business processes. However, as you prepare to insert machine learning applications into your business processes, I’d recommend that you not fantasize about how a computer that can win at Go or poker can surely help you win in the marketplace. A better reference point will be your experience implementing your enterprise resource planning (ERP) or another enterprise system. Yes, effective ERP implementations enhanced the competitiveness of many companies, but a greater number of companies found the experience more of a nightmare. The promised opportunity never came to fruition. Why am I raining on the AI parade? Because, as with enterprise systems, AI inserted into businesses drives value by improving processes through automation. But eventually, the outputs of most automated processes require people to do something. As most managers have learned the hard way, computers can process data just fine, but that processing isn’t worth much if people are feeding them bad data in the first place or don’t know what to do with information or analysis once it’s provided.
The pervasive diffusion of Information and Communication technologies (ICT) and automation technologies are the prerequisite for the preconized fourth industrial revolution: the Industry 4.0 (I4.0). Despite the economical efforts of several governments all over the world, still there are few companies, especially small and medium enterprises (SMEs), that adopt or intend to adopt in the near future I4.0 solutions. This work focus on key issues for implementing the I4.0 solutions in SMEs by using a specific case example as a test bench of an Italian small manufacturing company. Requirements and constraints derived from the field experience are generalised to provide a clear view of the profound potentialities and difficulties of the first industrial revolution announced instead of being historically recognised. A preliminary classification is then provided in view to start conceiving a library of Industry 4.0 formal patterns to identify the maturity of a SME for deploying Industry 4.0 concepts and technologies.
Enterprise architecture (EA) offers ways to steer and guide the design and evolution of the enterprise including its information technology (IT). One of the outputs of EA is improved decision-making about IT. Objective: This study aims to provide EA researchers and practitioners with insights into how IT decision-making actually takes place and what that means for them. Method: A systematic literature review was conducted in order to find and analyze primary studies about IT decision-making. Results: We found that IT investment and prioritization is by far the largest decision category. Money seems much more important than content. The IT decision-making process itself is subject to different variables and factors making every IT decision unique. We also found that both rational and bounded rational approaches are used in IT decision-making. EA has not a prominent role in IT decision-making. Conclusions: IT decision-making is a messy and complex process where money plays a prominent role. We argue that, if enterprise architects want to influence IT decision-making, they should follow the money by combining content with investment planning and prioritization. Further research is required into what distinguishes enterprise architects that are successful in IT decision-making, from those that are less successful.