Optimize your Big Data investments, decision making, and performance.

When we look at an organization as a whole and ask ourselves where we can make the biggest improvement, it’s probably not in the development process. If the developers are using Agile, they have already made gains simply by adopting the time box. There are certainly things that can be improved, but I would argue that the real opportunity for improvement lies in the remainder of the organization that is often operating with little or no observable process at all.

In our experience, one of the most important attributes in the success of top-performing organizations is a collective mindset that differentiates them through a deeper understanding of their customers.

Architecture is an organization function, just like the many other functions. And, it therefore needs to deal with many of the same issues that, say, finance, needs to deal with. Many of these issues are readily apparent if we get in touch with the intrinsic nature of organizations and what they consist of. Sometimes, this “dust” isn’t as visible because it is often swept under the wide rug of “architecture leadership.” This would be okay as long as there is a clear understanding of what architecture leadership is, but if it becomes just an amorphous catchall, it may end up hiding important organizational behaviors and patterns that lie unaddressed and untapped.

Designers are working feverishly to add connectivity to products, weighing the potential value to users, as well as risks. For example, the capability exists today to make toilets smart, but is there really a need for a toilet that can be flushed remotely? On the other hand, a smart oven can be triggered remotely to heat up by the time you return from work. It could be a great time saver, but is it a fire risk? As designers grapple with these questions, there are also a host of design issues that they must keep in mind while moving toward IoT capabilities. In this Executive Update, we explore the top 10 design considerations.

A value archetype is a basic model for value creation based on digital data streams (DDS). Archetypes are not exclusive classes of value creation, meaning you can adopt one for a specific set of customers and another for a different set. In classifying companies, consider the five value archetypes described in this Advisor.

In my experience, I've found that IT executives operate, understandably, on a diet of logic, rationality, and the search for the "right" way. This reliance on finding and applying the one and only answer — the "truth" — prevails despite numerous technical advances over the years that have disproved previously held IT "truths." In contrast, business leaders are beginning to realize that today's complex world means that there is perhaps no single truth, no one easy strategy to achieve competitive advantage and add value.

Having an Agile organization attracts a different type of employee, guarantees Agile market behavior, and is fun to work in. It is a sufficient precondition to resilience and fast market reaction, but not a necessary one.

While there are many ways to represent a business pattern, there is also value in having a more formal or consistent model. At the other extreme, it would be a mistake to be too rigorous by only ever applying one modeling approach. As a general principle, any model must be suitable for the use to which it is applied.

Cognitive computing is beginning to impact a range of industries due to its ability to ingest, analyze, and summarize massive data sets and facilitate self-service analytics, intelligent decision support, and smart advisory systems via the application of natural language processing (NLP), machine learning (ML), and intelligent reasoning capabilities. 

Everyone loves to negotiate from a position of power. It is satisfying, easy, and fun to play the game when you hold all the aces in your hand. It is much more challenging to try and negotiate effectively when you have a disadvantage in power, when the other party is bigger, better funded, and more experienced or has access to information that you cannot obtain. In such circumstances, it is easy to be intimidated by your relative lack of power and give up on trying to meet your objectives in the negotiation, effectively surrendering the little power you still have to the other side. This Executive Report begins by looking at how power perceptions can affect the outcome. The report then details the factors that affect your actual negotiating power position. It concludes by presenting six principles you can use to exert more influence on the matter and meet your interests more effectively.

Everyone loves to negotiate from a position of power. It is satisfying, easy, and fun to play the game when you hold all the aces in your hand. It is much more challenging to try and negotiate effectively when you have a disadvantage in power, when the other party is bigger, better funded, and more experienced or has access to information that you cannot obtain. In such circumstances, it is easy to be intimidated by your relative lack of power and give up on trying to meet your objectives in the negotiation, effectively surrendering the little power you still have to the other side. The accompanying Executive Report begins by looking at how power perceptions can affect the outcome. The report then details the factors that affect your actual negotiating power position. It concludes by presenting six principles you can use to exert more influence on the matter and meet your interests more effectively.

Cutter Consortium offers Executive Education days — singly or in a series — designed to move your entire team up the Digital Transformation learning curve.

Are there opportunities you’re missing to mine your organization’s data, to create value from the real-time flow of big data? Can you achieve improved customer experience through increased, data-based experimentation?

Are there opportunities you’re missing to mine your organization’s data, to create value from the real-time flow of big data? Can you achieve improved customer experience through increased, data-based experimentation?

Corporate information security can be challenging due to the numerous avenues that an attacker can traverse. All companies need methods to secure the hardware, software, and communication channels of mobile systems, internal networks, email traffic, and so on. Before developing a method, managers should engage technical and nontechnical staff to answer the following question: “How do we store, process, and transmit data in a secure manner?” As we explore in this Executive Update, to answer this question effectively, you’ll need a teamwork process in place that engages many people who are not thought of as security experts. 

What you need to drive your digital transformation is a realistic stakeholders’ consensus about the purpose, expected results (for your customers and your organization), and a roadmap of actions to deliver those results. Such a consensus requires you to create a shared understanding about the nature of the digital business economic environment.

The most common pressures driving Agile data analytics investments are data stored in silos and poor data quality impacting decision making. Both complaints betray the burden of legacy business systems and analytics. Data in back-end IT systems is very often difficult to access, difficult to integrate, difficult to normalize, and therefore difficult to harness to answer the questions posed by the business. Mired in these inflexible and out-of-date sources of data, the efforts to create front-end tools and reports will have limited success.

By leveraging business architecture as the mechanism to connect across business areas and drive toward a collective intent, IT will be in a better position to plan its strategy and roadmaps. What comes down the pipe from the business should be self-consistent and offer a holistic picture of the collective intent of the organization.

Where in security practice do we turn for inspiration when it comes to protecting our well-being and health from cyberattacks?

In this Summit 2016 keynote presentation, Federico Pigni demonstrates both strategic and tactical opportunities made possible by DDS.

Research and discovery are big application areas for applying cognitive techniques, including for financial market analysis, marketing, and product development. Several versions of IBM’s Watson technology, in the form of focused applications, are now being utilized by banking and financial companies in these roles. In addition, commercial cognitive solutions such as Kenshoo, targeted specifically at supporting financial market research, are also available.

The transformation to an Agile culture starts with an understanding of what we mean by culture.

Rather than having a team of testers manually testing the code for defects, invest in writing good auto­mated tests that can validate that each feature works as expected. When this happens, testers won’t scramble to keep up with developers, and developers won’t be waiting on testers.

Robert Ogilvie takes a broader look at some of the themes already developed and considers the likely role of cognitive computing in the near future. He suggests that automation has gone through three phases: a robotic phase, in which computers performed rote tasks; a social phase, in which computers have facilitated communication and collaboration; and a cognitive phase, in which computers are learning to use knowledge to solve intellectual problems. He alludes that most of the new cognitive systems will interact with and aid human performers. Rather than replace human managers, Ogilvie implies, cognitive computing applications will make existing managers more knowledgeable and better able to respond to a broader range of challenges. He goes on to offer an inspiring vision of cognitive computing applications that help individuals and teams focus their attention on the challenging ­problems that are really worthy of consideration.