devops

http://newrelic.com/devops/lifecycle

http://newrelic.com/devops/toolset

bimodel it

http://www.gartner.com/newsroom/id/3036017

STAMFORD, Conn., April 23, 2015View All Press Releases

Gartner Says Bimodal IT Projects Require New Project Management Styles

An Outcome-Centered Approach Will Bridge the Gap Between 'Slow' and 'Fast' IT

Analysts Will Explore Bimodal Projects at the Gartner PPM & IT Governance Summits 2015 in Grapevine, Texas on June 1-3 and in London, U.K. on June 8-9

Organizations struggling with bimodal IT projects should adopt a more outcome-centered approach to project management, according to Gartner, Inc. This will help them manage the different requirements of "slow" (Mode 1) and "fast" (Mode 2) IT most effectively.

"Enterprise project management organization (PMO) and application management leaders are struggling to adapt governance processes to handle new, agile Mode 2 efforts that don't conform to traditional project management structures," said Donna Fitzgerald, research vice president at Gartner. "A focus on business outcome and value will bridge the gap between Mode 1 and Mode 2 projects."

Gartner has identified three best practices to enable PMOs to better manage any type of IT project or program within the portfolio:

Use a Simple Approach to Determine Which Mode Makes Sense for a Project

Determining what Mode to use on a project often has more to do with company culture than anything else.

"While Mode 2 can theoretically be applied to any new project, Gartner recommends a simple construct: consider Mode 1 for systems of record and Mode 2 for systems of differentiation and systems of innovation," said Ms Fitzgerald.

A system of record is a core system that an organization uses to run its business, such as finance applications or email provision. While a system of record is vital to the operations of the company, it provides no competitive advantage. Systems of record are classically Mode 1. These projects tend to be more knowable both in clear outcomes and clear approaches to achieving these outcomes, which ultimately amounts to doing the process as well as any competitor. Once this is achieved, there is little incentive to improve further or change the process unless conditions or regulations change.

Systems of differentiation are generally Mode 2 projects, because their value resides in providing capabilities that competitors don't have. Since the nature of competition is that competitors will copy successful innovations, these capabilities need to constantly improve. The project will likely have a long-term goal that is achieved through several iterative steps that build on one another as success is demonstrated. The exploratory nature of Mode 2 projects is important to their long-term success.

A system of innovation is essentially an experiment. It needs a Mode 2 approach because it is a brand-new idea and there is no established way to plan the details of what will be done.

Define the Intended Business Outcome as the Measure of Project Success

Part of the problem with determining how to measure the value of a Mode 2 project lies in the way we currently measure Mode 1 projects. With a typical Mode 1 project, for example, the sales organization might submit a request and a business case for implementing a customer relationship management system, with a stated benefit of ultimately delivering increased revenue. If the business case were approved, IT would work with the sales team to establish exactly what aspects of the vendor-provided system offered the core critical capabilities, to ensure the system was configured correctly.

Mode 2 projects, however, are explorative and may not have an obvious list of capabilities by which to define their success from the outset. Instead, Gartner recommends identifying a specific business outcome, such as, "Improve lead conversion by X percent based on better segmentation of marketing campaigns," and agreeing on this while building the business case — all before the project starts. "This scenario works well across both Modes of projects because the outcome defines the scope, and fulfillment of the scope determines completion, rather than just depending on completing a list of requirements," said Ms Fitzgerald.

Clearly Separate Portfolio and Project Governance for Easier Bimodal Governance

The final area where many PMOs struggle is how to ensure that they maintain a consistent approach toward governing the project once it has begun. "Place responsibility for the project with the people who can practically make things happen," said Ms Fitzgerald. "Place responsibility for the investment portfolio with the people who have the authority to make decisions across the entire portfolio."

"Regardless of the Mode, the PMO supports governance through reporting on progress toward successful delivery," said Ms Fitzgerald. "This criterion remains the same whether the project is replacing a core financial system of record, or building a mobile app that enables consumers to purchase goods from the company. It ensures a consistent approach across Mode 1 and Mode 2 projects."

More detailed analysis is available in the Gartner report "Effective Governance of Bimodal IT Projects Requires Adopting a More Outcome-Centered Approach."

Analysts will explore how to manage bimodal IT projects at the Gartner PPM & IT Governance Summits 2015 inGrapevine, Texas on June 1-3 and in London, U.K. on June 8-9. You can find more content and updates around these events on Twitter using the hashtag #GartnerPPM.

Contacts

• Rob van der Meulen
• Gartner
• rob.vandermeulen@gartner.com

• Janessa Rivera
• Gartner
• janessa.rivera@gartner.com

Devops metrics

http://www.theserverside.com/tip/Tracking-DevOps-metrics-can-increase-business-agility

1. Track DevOps metrics

Peter Drucker, the famous management consultant, educator and author of Innovation and Entrepreneurship, once said, "What gets measured gets managed." According to Drucker, as soon as you start monitoring something, you magically see improvement in that area.

Inform your team and start tracking a few key DevOps metrics. You'll get Drucker's magical performance boost and establish a baseline for assessing to what extent any additional steps you take impact your organization's agility.

Devops.com contributors Payal Chakravarty and David Shackelford recommend the following DevOps metrics:

• Lead time to develop an application: Helps you understand how quickly you develop applications
• Percentage of failed deployments: Tells you whether they deploy successfully
• Customer ticket volume: Indicates how many issues crop up
• Mean time to recovery: Shows how long it takes to recover from an application bug or failure
• User volume: Indicates how useful your users find your applications

These metrics might appear to contain self-defeating trade-offs (e.g., the faster you develop, the more likely you are to make a mistake), but DevOps makes it possible to score well on all five agility metrics.

2. Tackle new projects using 'Mode 2'

Coined by Gartner, "bimodal IT" is an IT strategy that simultaneously embraces traditional IT ("Mode 1"), which emphasizes reliability and accuracy, and modern IT ("Mode 2"), which emphasizes speed and agility. In other words, with a bimodal IT approach, you don't need to abandon your existing Mode 1 applications and infrastructure to gain the benefits of Mode 2.

But how do you decide which projects should use Mode 1 versus 2? The bimodal IT best practices from Gartnerrecommend Mode 1 for systems of record and Mode 2 for systems of differentiation and innovation.

Over time, as you find opportunities to employ Mode 2, your business's ability to respond quickly to market dynamics should improve.

3. Explore DevOps-friendly PaaS technology

Now that you're completing some of your organization's projects with greater speed and agility, you should consider platform-as-a-service (PaaS), which further facilitates a DevOps approach.

PaaS is a cloud-based platform that makes it easier for developers and IT operations to build, deploy and manage applications and avoid many infrastructure-related challenges and expenses. IT also can use PaaS technology to collaborate and iterate more tightly with line-of-business managers.

Tracking DevOps metrics, using Mode 2 for new projects and exploring PaaS implementation are effective entry-level steps you can take to increase agility. Act today and soon your organization should find itself better positioned to compete and thrive in today's rapidly changing world.

Inventory Management

Excellent article: http://www.ibmwcs.com/2013/07/atp-inventory-concepts-order-management.html

search engines

Memex from Arpa
DeepDive from Stanford
TJBATCHEXTRACTOR Carnegie Mellon
Hyperion gray 

Flip the Script

Patty’s Parting Questions

 “Have we made any decisions in the room today, and (if we have) how are we going to communicate them?”
Source: https://www.linkedin.com/pulse/how-do-you-end-meeting-netflixs-hr-rebel-asks-two-simple-bob-sutton

What is Duration-Driven Project Management?

Source: http://pm-alliance.com/

Duration-Driven Project Management

In his ground-breaking book, The Mythical Man-Month (1975), Frederick Phillips Brooks identified the importance of duration-based planning to achieve successful projects. He observed that: “Our duration estimations confuse effort with progress; hiding the wrong assumption that men and months are interchangeable”. At PMAlliance we have expanded this observation into three key principles that form the foundation of our Duration-Driven® methodology. Principle 1: Time Matters Almost all projects have deadline dates and if those deadline dates are missed the project will not be a success and along the way budget and quality will most likely be sacrificed. The core of Duration-Driven® methodology is based on the idea that, the time dimension of projects must be managed to achieve success. Principle 2: Duration-Based Estimates In order to manage the time dimension of projects, we must have duration-based estimates from team members; this includes estimates to perform their future activities within a specified duration and estimates to finish their in-progress activities by a specific date. There are decades of anecdotal data demonstrating that obtaining team member commitment is the key to project success. Therefore, we must also have a process that drives team member commitment to the duration-based estimates used in the project plan. Principle 3: Appropriate Tools Many popular project management tools and methodologies can actually impair a team’s ability to create the types of commitments necessary for success. For example, communication of “hours of effort” does not represent a commitment on the part of a team member to complete an activity within a specified amount of time; sophisticated calculations of activity durations by project management software tools do not drive accountability on the part of the team members; and ambiguous estimates of percent complete do not represent a promise on the part of a team member to finish by a certain date. Summary Duration-Driven® Methodology allows project teams to obtain time-based commitments from team members, incorporates those commitments into a dynamic, network-based project plan with a calculated critical path, creates a framework for compressing project durations to meet deadline dates in a way that maintains team member commitment, and then tracks progress over the life of the project and continually reconfirms team member commitment towards meeting the project deadline date. Through Duration-Driven® Methodology, team members operate in a project environment that is more likely to result in success. Want to know more? we have included some case studies you may find useful as well as some general info about our methodology and onboarding process. Please call our toll free number if you would like a faster response. Thank you. P: (866) 808-3735 E: info@pm-alliance.com

60% of Big Data project will fail

Source: http://www.wsj.com/articles/the-joys-and-hype-of-software-called-hadoop-1418777627

“The dirty secret is that a significant majority of big-data projects aren’t producing any valuable, actionable results,” said Michael Walker, a partner at Rose Business Technologies, which helps enterprises build big-data systems. According to a recent report from the research firm Gartner Inc., “through 2017, 60% of big-data projects will fail to go beyond piloting and experimentation and will be abandoned.”

Google descriptions

https://support.google.com/webmasters/answer/35624?rd=1

Prevent search engines from displaying DMOZ data in search results for your site

One source Google uses to generate snippets is the Open Directory Project. You can direct us not to use this as a source by adding a meta tag to your pages.

Create good meta descriptions

The description attribute within the <meta> tag is a good way to provide a concise, human-readable summary of each page’s content. Google will sometimes use the meta description of a page in search results snippets, if we think it gives users a more accurate description than would be possible purely from the on-page content. Accurate meta descriptions can help improve your clickthrough; here are some guidelines for properly using the meta description.

• Make sure that every page on your site has a meta description. The HTML suggestions page in Webmaster Tools lists pages where Google has detected missing or problematic meta descriptions.


• Differentiate the descriptions for different pages. Identical or similar descriptions on every page of a site aren't helpful when individual pages appear in the web results. In these cases we're less likely to display the boilerplate text. Wherever possible, create descriptions that accurately describe the specific page. Use site-level descriptions on the main home page or other aggregation pages, and use page-level descriptions everywhere else. If you don't have time to create a description for every single page, try to prioritize your content: At the very least, create a description for the critical URLs like your home page and popular pages.


• Include clearly tagged facts in the description. The meta description doesn't just have to be in sentence format; it's also a great place to include structured data about the page. For example, news or blog postings can list the author, date of publication, or byline information. This can give potential visitors very relevant information that might not be displayed in the snippet otherwise. Similarly, product pages might have the key bits of information—price, age, manufacturer—scattered throughout a page. A good meta description can bring all this data together. For example, the following meta description provides detailed information about a book.

  <meta name="Description" content="Author: A.N. Author, 
  Illustrator: P. Picture, Category: Books, Price: $17.99, 
  Length: 784 pages">

  In this example, information is clearly tagged and separated.


• Programmatically generate descriptions. For some sites, like news media sources, generating an accurate and unique description for each page is easy: since each article is hand-written, it takes minimal effort to also add a one-sentence description. For larger database-driven sites, like product aggregators, hand-written descriptions can be impossible. In the latter case, however, programmatic generation of the descriptions can be appropriate and are encouraged. Good descriptions are human-readable and diverse, as we talked about in the first point above. The page-specific data we mentioned in the second point is a good candidate for programmatic generation. Keep in mind that meta descriptions comprised of long strings of keywords don't give users a clear idea of the page's content, and are less likely to be displayed in place of a regular snippet.


• Use quality descriptions. Finally, make sure your descriptions are truly descriptive. Because the meta descriptions aren't displayed in the pages the user sees, it's easy to let this content slide. But high-quality descriptions can be displayed in Google's search results, and can go a long way to improving the quality and quantity of your search tr

13th year of High School

http://www.slate.com/articles/life/education/2014/10/high_schools_offer_a_fifth_year_of_high_school_13th_grade_is_a_great_idea.html

Actually, using state high school funding for a 5th year of high school at a community college and receive their high school diploma after the community college and get collage credit

Grit

http://news.nationalgeographic.com/news/2014/10/141015-angela-duckworth-success-grit-psychology-self-control-science-nginnovators/

Grit scales:

https://sites.sas.upenn.edu/duckworth/pages/research

"We validated it," Angela says. "We showed it predicted objective measures like graduating West Point's first summer [cadet basic training] and winning the National Spelling Bee. And then in all the studies we measured IQ and consistently found that IQ really is something else." Being a hardworking or self-controlled kid is not the same as being a smart kid. Angela and her team had parents rate their kids, had teachers rate their kids, and had kids take two different questionnaires and a delayed-gratification test ("Do you want a dollar today or two dollars in a week?"). They had them do a hypothetical delayed-gratification test with a large number of choices (two dollars today, seven in three months).

"When you average across all of those things, we found you can predict things like their grade point average startlingly well—much better, in fact, than IQ does—as well as changes in grades," Angela says, a finding described by like-minded Stanford colleague Carol Dweck, whom Angela thinks of as a role model, as "a landmark piece of work."

Decision Fatigue

http://www.slate.com/articles/business/productivity/2014/10/decision_fatigue_ego_depletion_how_to_make_better_decisions.2.html

Next, decrease your range of options. This may seem counterintuitive, since it requires making even more decisions. For instance, if you’re picking a restaurant for an important lunch meeting, first deciding on a certain part of town or type of cuisine can narrow your options. Like the participants in the jams study, you’re less likely to be paralyzed by choice if you have few options instead of dozens.

Once you’ve arrived at a decision, stick with it. Ignore the naysaying voice in your head asking if this is the mutual fund that will make you the most money in 15 years or if the route your GPS gave you is the most gas-efficient. Just accept that no decision is ever completely perfect, and remind yourself that it is the best you can do with the tools you have in the moment. Second-guessing yourself only requires making more decisions, which further depletes your cognitive resources. You might also end up happier; researchers have found that people who “satisfice, “or pick an option that meets requirements, are more content with their choices than people who try to pick the best option.

Changing your beliefs may actually make you more productive, too. Someresearchers believe that the notion of ego depletion is all in your head, and that rejecting the idea of self-control as a muscle can combat its effects. People who instead believe that self-control is an infinite resource are less likely to show effects of ego depletion—they actually show increased performance on self-control tests after completing boring, ego-draining tasks like crossing out e’s from a document. Even weirder, how you feel about free will also affects your productivity: The more strongly you believe in it, the more likely you are to enjoy making decisions and to be happy with your choices. My apologies, readers, but your best bet at boosting your productivity may actually be to disregard what you’ve learned in this article.

Source: http://www.computerworld.com/article/2691607/one-in-three-jobs-will-be-taken-by-software-or-robots-by-2025.html?google_editors_picks=true

 Gartner sees things like robots and drones replacing a third of all workers by 2025, and whether you want to believe it or not, is entirely your business.

Smart machines are an emerging "super class" of technologies that perform a wide variety of work, both the physical and the intellectual kind, said Sondergaard. Machines, for instance, have been grading multiple choice for years, but now they are grading essays and unstructured text.

This cognitive capability in software will extend to other areas, including financial analysis, medical diagnostics and data analytic jobs of all sorts, says Gartner.

Following the Process

Following the process can be perceived as a negative phrase - more red tape.  Without well defined processes, a company will loose value through duplication of efforts (two similar processes that were created to achieve the same goal, duplicating the same power point presentation, etc), low quality (high variability), and wasted efforts (efforts which are considered waste in lean methodologies).  The Art is knowing when the situation does not fit the process.

Future of enterprise search

Rebecca Hawkes posted a link to Stephen E. Arnold's summery of "Enterprise Search: 14 Industry Experts Predict the Future of Search" by Cóbhan Phillipson


A few of the quotes
"Effective enterprise search represents one of the most challenging areas in business today"

"In my opinion the enterprise search market today has little appetite for more sophisticated products the likes of which we have seen come and go in recent years."

"Why should you have to ask first?: Search has been traditionally driven by the searcher (duh), but interesting projects that allow for integrated understanding of where/what the user is doing allows for proactive intervention."

"Buzzwords like “federated search” and “enterprise search” place too much focus on “search”, and not enough on getting the right information, transparently and rapidly to the consumer."

"Search will continue to become more implicit, connecting users to knowledge transparently. Users do not want to “search”, they want to get information. We are trying to collapse the “time to information”, and this is not just about extremely fast search of vast amounts of data. It is also about not wasting time searching and presenting irrelevant information, and about creating results that are fine-grained. People are accustomed to doing a search and getting say 10 best results, each one a document, and then sifting through the documents. We are trying to improve that by returning finer grained results that are not documents, but the exact sentence, the exact spreadsheet cell, or exact information the user is looking for."

"The global enterprise search market reaped revenues of more than $1.47 billion in 2012. That figure is forecast to be $4.68 billion by 2019."

"In the future enterprise search will become more personal. With users being able to add and delete their own search sources. True federation will come in to play, and the ‘super index’ will start to take a back seat to ‘Click-Time’ information access. This change will mean that users gain power to control their own results, Bringing in cloud stores, internal applications, such as CRM and Doc management, as well as pulling in external non-corporate content from web sites, such as Linked-In, Facebook and other social networks. This will then give the user a 100% view of their data and information points."

Stephen Arnold's summary:
Several observations occurred to me as I worked through the compilation of expert opinions in “Enterprise Search: 14 Industry Experts Predict the Future of Search”.

First, the confusion about what enterprise search is characterizes the experts’ approach to findability. A knowledge management professional would set about gathering other writings by these individuals and attempting to provide a context for their “information” and opinions. Without a knowledge framework, the collection of opinions is confusing.

Second, the selection of companies represented provides a wide spectrum of starting points. The inclusion of search engine optimization experts mixed with vendors of primary systems and component vendors provides a surprising consensus. Automation is likely to be more important with each passing day. Also, users want to be relieved of the burden of formulating a query or will be given systems that reduce the user’s dependence on keywords and formal queries. The approach is likely to be given considerable attention because automation reduces some of the costs associated with finding information. Will automated search provide knowledge management systems with appropriate inputs? If not, perhaps the discontinuity between enterprise search and knowledge management becomes another challenge for both disciplines to resolve.

Third, the vendors, with the sole exception of LTU in Paris, focus on text. The data about the volume of content by file type is not definitive. The need to be able to search audio, images and video within an organization is increasing. Videos posted on YouTube, Vimeo or other file sharing systems are proliferating. IBM creates big data podcasts each week, distributing them via Apple iTunes. Videos about search, content processing and analytics systems are key parts of the marketing efforts of Attensity, MarkLogic, Oracle and other firms. The future of enterprise search is more than text. The Docurated analysis makes clear that enterprise search vendors and experts may be their own worst enemy.

There may be some challenges for enterprise search in the organizations of tomorrow. Without innovation, enterprise search is likely to find itself marginalized as enterprise knowledge management solutions proliferate. Search without search may be shorthand for who needs old-fashioned search?

Engagement and Tests in Education

The purpose of this study is to examine the relationship between student 
engagement (behavioral, cognitive, and emotional) and the standardized test scores of 
eighth grade students in three Wakta middle schools. A quantitative survey was used to 
access 8th graders‘ perception of their behavioral, cognitive, and emotional engagement. 
The engagement data was correlated to standardized test scores and demographic data for 
each student.  Further analysis revealed increased engagement has a direct correlation to 

increased academic achievement.

In Wakta, emotional engagement and behavioral engagement were shown to have a mitigating impact on the predictability of ethnicity on student achievement scores.

Source: http://conservancy.umn.edu/bitstream/143657/1/Scheidler_umn_0130E_13207.pdf

Research shows that student engagement is highly predictive of student outcomes, including higher test scores, lower dropout rates, and increased likelihood of pursuing a higher education.
Source: http://www.naviance.com/blog/measure-what-matters-why-student-engagement-matters-as-much-as-grades-and-test-scores#.U-u82PldUTA

The results suggest that the lowest-ability students benefit more from engagement than classmates, first-year students and seniors convert different forms of engagement into academic achievement, and certain institutions more effectively convert student engagement into higher performance on critical thinking tests. College Students, although most of the 
relationships were weak in strength
Source: http://nsse.iub.edu/pdf/research_papers/testing_linkages.pdf


The Elements of Discord: 

The Sine Qua Non of Education 
Gregory Kerr
Source: http://maritain.nd.edu/ama/McInerny/McInerny07.pdf

How Silos in the Marketing Organization Thwart Alignment with IT

According to a global survey of marketing professionals by Teradata, 74 percent of the respondents said that marketing and IT are not strategic partners in their companies

Data is an asset that should be shared across the organization to discover patterns of behavior and pinpoint areas of opportunity to be leveraged by sales, marketing and customer service. While data collection has historically occurred most often within the IT organization, the analysis of that data is often the responsibility of customer insights managers or data scientists, who must work cross-functionally with both marketing and IT. Greater collaboration and partnership between the worlds of marketing and IT power deep, actionable understanding of the customer—and companies who drive their businesses with customer data are best positioned to win.

However, using all the data together is what drives a great customer experience, and according to a McKinsey study, 70 percent of customers buy based on how they are treated. As for how IT can assist, it is truly about collaboration between marketing and IT, or between CMO and CIO, and the broader strategy of the company being driven by the C-suite. You might point readers to a post written earlier this year by our company president about why this need is so critical.

http://www.itbusinessedge.com/blogs/from-under-the-rug/how-silos-in-the-marketing-organization-thwart-alignment-with-it.html

Doherty Threshold

Update: The original version of this post incorrectly stated that the Doherty Threshold was not a real thing. That was incorrect. Here's the Doherty Threshold, listed on the IBM website, as described by author Walter J. Doherty in 1982. As shown in this episode of Halt and Catch Fire, it is when a computer has a response time of less than half a second:

When a computer and its users interact at a pace that ensures that neither has to wait on the other, productivity soars, the cost of the work done on the computer tumbles, employees get more satisfaction from their work, and its quality tends to improve. Few online computer systems are this well balanced; few executives are aware that such a balance is economically and technically feasible. In fact, at one time it was thought that a relatively slow response, up to two seconds, was acceptable because the person was thinking about the next task. Research on rapid response time now indicates that this earlier theory is not borne out by the facts: productivity increases in more than direct proportion to a decrease in response time.

Source: http://gizmodo.com/halt-and-catch-fire-episode-four-donna-is-here-to-solv-1594879529


The Economic Value of Rapid Response Time

A transaction consists of a user command from a terminal and the system's reply. It is the fundamental unit of work for online system users. It can be divided into two time sequences (Figure 1):
User Response Time. This is the time span between the moment a user receives a complete reply to one command and enters the next command. People often refer to this as think time.
System Response Time. This is the time span between the moment the user enters a command and the moment a complete response is displayed on the terminal. System response time can be further divided into:

• Computer response time, the time the computer actually spends processing and servicing the user's command
• Communication time, the transit time for a command to go to the computer and the time for the reply to come back

...
He and Richard P. Kelisky, Director of Computing Systems for IBM's Research Division, wrote about their observations in 1979, "...each second of system response degradation leads to a similar degradation added to the user's time for the following [command]. This phenomenon seems to be related to an individual's attention span. The traditional model of a person thinking after each system response appears to be inaccurate. Instead, people seem to have a sequence of actions in mind, contained in a short-term mental memory buffer. Increases in SRT [system response time] seem to disrupt the thought processes, and this may result in having to rethink the sequence of actions to be continued." 
...

But, bring system response time down to 0.3 seconds and the number of transactions the programmer can execute in an hour jumps to 371, an increase of 106 percent. Put another way, a reduction of 2.7 seconds in system response saves 10.3 seconds of the user's time (Figure 3). This seemingly insignificant time saving is the springboard for sizable increases in productivity.
...

Cost/Benefit Illustration

To bring the potential benefits of rapid system response into perspective, consider an illustration. Based on the data Thadhani published (Figure 2), the average user can complete 180 transactions per hour at three second response time (Figure 9). For simplicity, then, assume a task that involves 180 transactions and takes an hour to complete. Any one user can complete eight such tasks in a day. Further, assume the burdened value of the user's time is $35 per hour. These numbers will be held constant for the purposes of this illustration.
 

*  Based on Thadani's data (Figure 3) 

Figure 9. Computation of the Time a User Saves in a Day as System Response Time Improved from 3.0 Seconds to 0.3 Seconds

System Response Time (Seconds)	Transactions per Hour*	Task Time (Minutes)	Time Saved per Task (Minutes)	Time Saved per Day (Minutes)
3.0	180	60.0	-	-
2.0	208	51.9	8.1	64.8
1.0	252	42.9	17.1	136.8
0.6	279	37.7	22.3	178.4
0.3	371	29.1	30.9	247.2

As system response time improves, the time required to complete a task drops from the original 60 minutes to only 29.1 minutes. Since the average user completes eight such tasks in a day, the maximum amount of time that can be saved is 247.2 minutes, or 4.1 hours. In a month of 21 work days, the value of these saved minutes is $3,028. 

The number of simultaneous users an online system supports varies from organization to organization as does the amount of improvement in response time which is needed. But, in all cases in this illustration (Figure 10), the financial incentive for bringing system response time from three seconds into the subsecond range is substantial, ranging from $150,000 per month when only 50 people use a system at any one time to $908,000 when 300 people use the system simultaneously.

Source: http://www.vm.ibm.com/devpages/jelliott/evrrt.html

Architecture sketching

Three types of Architecture:

Application Architecture: Th internal structure of an application (classes, components, design patters)
System Architecture: High-level structure of a software components/services)
Enterprise Architecture: Structure and strategy across people, process and technology

Simon Brown considers software architecture as both Application and System Architecture

Architecture represents the significant decisions, where significance is measured by cost of change.

The C4 model (static structure):
System Context: The system plus users and system dependencies

Containers: the overall shape of the architecture and technology choices

Components: Logical components and their interactions within a container

Classes: component or pattern implementation details

A common set of abstractions is more important than a common notation

Tips:

Keep audience in mind when developing diagrams: non-technical, semi-technical, technical


Checklist for an effective sketch (diagram):

1. I can see the solution from multiple levels of abstraction
2. I understand teh big picture (context)
3. I understand the logical containers
4. I understand the major cmponents used to satisfy the important user stories/features
5. I understand the notation, colour coding, etc used on the diagrams
6. I can see the traceability between diagrams
7. I understand the major technology decisions
8. I understand the implementations strategy (frameworks, libaries, API's, etc)

"Sketches are Maps"

Just enough up front design to create firm foundations for the software product and its delivery:

From: https://skillsmatter.com/skillscasts/5109-simple-sketches-for-diagramming-your-software-architecture