When Stakeholders Collide

Requirements Expedition

Maybe you’ll meet them during the Project Kickoff. Maybe you’ll first hear from them during a biweekly Steering Committee. Or maybe you will first hear from them three months into the project at a quarterly meeting with the CIO and the rest of his portfolio. Maybe you will never hear from them directly.

The politics of requirements gathering and prioritization is a daunting process. I’m not going to drudge up all the stories and categorize them here because it’s a painful process.

Why are some of your milestones in your project plan:

• the milestone exists within someone’s year end evaluation

• the requirements of a milestone are so bipolar, they are bound to fail. Need a project to bucket the requirements to say “we tried”, and we can pin it to a project.

• backing into established project timelines based on expectations set at the highest levels, e.g. regulatory compliance

Legal and Compliance Stakeholders

Global representation of legal and compliance requirements are a dichotomy of legal precedence between jurisdictions.

Agile Product Owner verse Waterfall Stakeholder Committee(s)

Many a project managed using waterfall kept me balancing the needs and wants of Stakeholders from all walks of life, some exuberantly voicing their opinions regardless of their position of power, or lack therein. The Agile Product Owner (PO) is a relief of burden, a single mouthpiece of the business, which dictates backlog priority.

Does Agile make the requirements gathering and prioritization pain go away? Possibly. There are various implementations of Agile, hybrid situations, and there are lots of tools out there to help manage the Product Backlog (requirements). Another exercise, developing User Journeys, working with your Personas / actors to derive their story, that is telling and lots of fun.

Help Wanted: Civil War Reenactment Soldiers to Improve AI Models

I just read an article on Digital PC Magazine, “Human Help Wanted: Why AI Is Terrible at Content Moderation” which started to get my neurons firing.

Problem Statement

Every day, Facebook’s artificial intelligence algorithms tackle the enormous task of finding and removing millions of posts containing spam, hate speech, nudity, violence, and terrorist propaganda. And though the company has access to some of the world’s most coveted talent and technology, it’s struggling to find and remove toxic content fast enough.

Ben Dickson
July 10, 2019 1:36PM EST

I’ve worked at several software companies which leveraged Artifical Intelligence, Machine Learning to recognize patterns, correlations. The larger the data sets, in general, the higher the accuracy of the predictions. The outliers in the data, the noise, “falls out” of the data set. Without quality, large training data, Artificial Intelligence makes more mistakes.

In terms of speech recognition, image classification, and natural language processing (NLP), in general, programs like chatbots, digital assistants, are becoming more accurate because of their sample size, training data sets are large, and there is no shortage of these data types. For example, there are many ways I can ask my digital assistant for something, like “Get the movie times”. Training a digital assistant, at a high level, would be to catalog how many ways can I ask for “something”, achieve my goal. I can go and create that list. I could write a few dozen questions, but still, my sample data set would be too small. Amazon has a crowdsourcing platform, Amazon Mechanical Turk, which I can request they build me the data sets, thousands of questions, and correlated goals.

MTurk enables companies to harness the collective intelligence, skills, and insights from a global workforce to streamline business processes, augment data collection and analysis, and accelerate machine learning development.

Amazon Mechanical Turk: Access a global, on-demand, 24×7 workforce

Video “Scene” Recognition – Annotated Data Sets for a Wide Variety of Scene Themes

In silent films, the plot was conveyed by the use of title cards, written indications of the plot and key dialogue lines. Unfortunately, silent films are not making a comeback. In order to achieve a high rate of successful identification of activities within a given video clip, video libraries of metadata need to be created, that capture:

  • Media / Video Asset, Unique Identifier
  • Scene Clip IN and OUT timecodes
  • Scene Theme(s), similar to Natural language processing (NLP), Goals = Utterances / Sentences
    • E.g. Man drinking water; Woman playing Tennis
  • Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta-tags

Not Enough Data

Here is an example of how Social Media, such as Facebook, attempts to deal with video deemed inappropriate for their platform:

In March, a shooter in New Zealand live-streamed the brutal killing of 51 people in two mosques on Facebook. But the social-media giant’s algorithms failed to detect the gruesome video. It took Facebook an hour to take the video down, and even then, the company was hard-pressed to deal with users who reposted the video.

Ben Dickson
July 10, 2019 1:36PM EST

…in many cases, such as violent content, there aren’t enough examples to train a reliable AI model. “Thankfully, we don’t have a lot of examples of real people shooting other people,” Yann LeCun, Facebook’s chief artificial-intelligence scientist, told Bloomberg.

Ben Dickson
July 10, 2019 1:36PM EST

Opportunities for Actors and Curators of Video Content: Dramatizations

All those thousands of people who perform, creating videos of content that range the gamut from playing video games to “unboxing” collectible items. The actors who perform dramatizations could add tags to their videos indicating as per above, documenting themes for a given skit. If actors post their videos on YouTube or proprietary crowdsourcing platforms, they would be entitled to some revenue for the use of their licensed video.

Disclosure Regarding Flag Controversy

I now realize there are politics around Nike “tipping their hat” toward the Betsy Ross flag. However, when I referenced the flag in this blog post, I was thinking of the American Revolution, and the 13 colonies flag. I didn’t think the title would resonate with readers, “Help Wanted: Amerian Revolutionary war Reenactment Soldiers to Improve AI Models.”, so I took some creative liberty.

Social Media: News Feed verse App InMail

Better Demographic Penetration and Transparency to More Accurately Determine Creative Media Asset Worth

News Media Assets

News Media Assets are created by writers of non-fictional work, coverage of various topics targeted towards the periodical demographic.

Selling Advertising Space

Layered within the news media product, consists of News Media Assets and sold advertisement space. Ad positioning throughout the news media product may have commonality between the product or service being advertised and the news media asset. A goal is the smooth transition between reader of asset and advertisement.

Revenue Models For News Media Assets

  • Deriving revenue from sponsors of news Media Assets
  • Subscription Base of News Media Assets, regular frequency of news media product to subscriber base.

Social Media – News Feeds

The news agencies post to public news feeds a “teaser” headline, a sentence or two describing the news media asset, and a teaser image all to lure prospective readers to clink a link to the news media publisher’s platform. At that point, the publisher sets the “ground rules” for the potential subscriber, e.g. 10 free articles a month, then their digital subscription price of NN goes into effect.

Social Media – InMail (I.e. eMail within the platform)

InMail through the social media platform can come from a variety of sources, for example:

  • Former colleague looking to reconnect
  • Recruiter looking to pitch a potential role
  • Sales / Marketing InMail targeting you as a potential customer of their product or service
The Tools to get the Job Done

As a prior client of LinkedIn Advertising for both ad placement and Sponsored InMail, I found the tools provided and the granularity upon which to refine the demographics impressive, and not lacking in any way.

Personable, Targeted Marketing of News Media Assets, sponsored by 3rd party promoting their product or service.

Delivering News Media Assets to your digital door step, with advertising partners speckled into the asset. Because of the granularity of the InMail advertising controls demographics are at a level of precision. Beyond what a magazine or newspaper, digital or print, can offer.

it’s all about the targeted audience and the granularity of the data collected and then leveraged to meet the desired audience. Much more personal than a link back to the publisher’s platform.

Just like there are expenses to do business in print or traditional digital, the price of doing business with a platform like LinkedIn Sponsored InMail, would be absorbed by the news media agency, net advertisement placement for advertisements.

Although the LinkedIN Social platform was used for reference, other platforms may be leveraged, depending upon the product or services being marketed, such as a Facebook People Magazine article relevant to their demographic, partnership / sponsorship.

Fake News – Not a Problem

Since News Media Agencies will now pair with “sponsors” or commonly know as advertisers, both parties, the news agency and the sponsor have “skin in the game”, it is less likely to be a factitious article.

Free Nights and Weekends Makes a Comeback

Remember when you could make free mobile calls after 9:30 PM weeknights, and all weekend? For awhile the mobile carriers competed on the time when “off-peak” started, from 10 PM to 8:30 PM. A whole hour and a half! These days we have unlimited domestic calling all the time.

So, now we have varying degrees of data plans, such as AT&T Wireless 3 GB, 9 GB, or unlimited per month, but there are caps where after 22 GB data transfer speeds are slowed down.  22 gigs seem like a lot until you have kids using Snapchat and TikTok.

When you think about it, data peak is when you may not be in a hot spot. At night, you’re at home using your own WiFi, or at an establishment with their complimentary WiFi. Weekends and weekdays are a bit scattered. Your work may have WiFi, but weekdays “on peak” are mostly commuting times, the “rush hour(s)”,

Can wireless carriers bring back on and off-peak for data?  The simplest approach:  “turn off the meter” during off-peak data periods.  Maybe on-peak the consumer can elect 5G, when available, and off-peak at 4G LTE? Our Smartphones can identify low consuming bandwidth opportunities, e.g. when the phone is locked, text messages without graphics and email are semi-passive states. Maybe users are able to prioritize their apps data usage? What about those “chatty” apps that you rarely use? Smartphone settings may show you those apps bandwidth consumption as opportunities to prioritize them lower than your priority apps.

Skeptic, and think there are no Peak or Off-Peak periods with data?  Check the business analytics.  I’m sure wireless carriers have a depth of understanding for their own business intelligence (BI).

7 Failures I Needed to Succeed

Here is a list of seven failures from my professional career, how I met those challenges, and in some cases, turned them into opportunities

Underestimate

Eager to please throughout my career, I was burned many times, and in some cases continue to be burned by underestimating the effort required for an activity, or task, which roll up to the delivery of features, or meeting a milestone. In my earlier years, I “shot from the hip” to senior management, and they held me to those commitments. Over the years, I’ve been fortunate enough to document and mitigate risks. In addition I learned additional tools, both process and communication / people skills:

* “Interesting point, let me consider, and get back to you.” You don’t have to provide an answer right away. Consider the scope and impact of the questions you are presented. Unless you are almost certain of the answer, try to defer.

* Planning Poker (Agile) collaborative (blind) estimates make better estimations. Through collaboration, you reach joint commitment. You eliminate the “boss knows best” factor.

Hearing but not Listening

Throughout my personal and professional life, I’ve struggled with this aspect of communication, more so earlier on in my life. Two people have a meeting, and discuss their point of views regarding the same topic. They both leave the room, and have two polar opposite prospectives of what was communicated.

Even in the same language, things get “lost in the translation.“. There are many process tools to better your communications style. You hear what you want to hear. You don’t probe deep enough into another person’s perspective.

Overestimate

Adding too much margin into an estimate, being conservative in your effort estimate at times may not be the best course of action. “Right Sizing” the estimate is typically the desired approach unless otherwise guided by the appropriate stakeholders. There are lots of tools for Effort estimation, poker planning, and fist of five are just two examples.

Army of One – Embrace Opportunity

I was brought into a development team as a Software Quality Assurance manager for a well known Financial Services organization. I was to build a team of QA staff as well as mature their process workflow, e.g. implement software change management.

The department’s QA resources per team dwindled, letting go these resources, and not growing the teams as first advertised during the interviews. I found myself constantly working with the team putting out fires. Best case scenario, I worked “after” hours just to work on the strategic stuff like process improvements, and automation. I stuck to the opportunity to learn as much as possible. Sticking with the job, I built my knowledge and relationships that would wind up propelling my career to later on build and manage a 50 person, global team.

Build it and they will Come…Bull!

I chose to try my own startup at some point in my professional career. I had worked for a startup firm out of college, but that was not the same as my own self startup. There were lots of balls to juggle, decisions to make and prioritize. After a year and a half, I shutdown the company, more money going out than in, and I was also “relatively” self funded.

One of the several ill choices I made was “Build it and They will Come.” At the time it was 2009, and the mobile frenzy was just starting to heat up. Feb 2009, Apple was at 30 USD per share! 30! I built a client/server mobile application for expertise transactions, way ahead of my time. I was almost entirely focused on the development of the solution, I clearly lost sight of the focused requirement of building market share. I did post Press Releases, but I didn’t embrace digital marketing as a core spend and activity for my business.

Needless to say I was “The Best Kept Secret”.

Chasing the Sun

As a software product, startup firm, you need to segment your product to align to a target audience. However, honing in on the target market maybe problematic if the “fish aren’t biting”.

You find yourself reassessing the strategic and tactical goals of your product, pivoting often to eventually find your “pay dirt”. There may be fundamental influences to your ecosystem, such as a shift in a 3rd party product previously seen as complementary now seen as “overlapping”. Sales pitch and marketing approach may need to change along with your product.

Although pivoting often may be the name of the game, you still should recognize the cost in adapting to change. Process flows like being “agile” and Scrum help to smooth the pivot, as these processes revolve around constant development iterations and reflections every few weeks.

Time to Pull the Parachute Cord

I still have trouble with knowing when it’s time to say when. I enjoy troubleshooting problems, business, people, process, and technical. So, how long do you work on problem before you pull the ripcord?

Riddle of the Sphinx: Improving Machine Learning

Data Correlations Require Perspective

As I was going to St. Ives,

I met a man with seven wives,

Each wife had seven sacks,

Each sack had seven cats,

Each cat had seven kits:

Kits, cats, sacks, and wives,

How many were there going to St. Ives?

One.

This short example may confound man and machine. How does a rules engine work, how does it make correlations to derive an answer to this and other riddles?  If AI, a rules engine is wrong trying to solve this riddle, how does it use machine learning to adjust, and tune its “model” to draw an alternate conclusion to this riddle?

Training rules engines using machine learning and complex riddles may require AI to define relationships not previously considered, analogously to how a boy or man consider solving riddles.  Man has more experiences than a boy, widening their model to increase the possible answer sets. But how to conclude the best answer?  Question sentence fragments may differ over a lifetime, hence the man may have more context as to the number of ways the question sentence fragment may be interpreted.

Adding Context: Historical and Pop Culture

There are some riddles thousands of years old.  They may have spawned from another culture in another time and survived and evolved to take on a whole new meaning.  Understanding the context of the riddle may be the clue to solving it.

Layers of historical culture provide context to the riddle, and the significance of a word or phrase in one period of history may wildly differ.  When you think of “periods of history”, you might think of the pinnacle of the Roman empire, or you may compare the 1960s, the 70s, 80s, etc.

Asking a question of an AI, rules engine, such as a chatbot may need contextual elements, such as geographic location, and “period in history”, additional dimensions to a data model.

Many chatbots have no need for additional context, a referential subtext, they simply are “Expert Systems in a box”.  Now digital assistants may face the need for additional dimensions of context, as a general knowledge digital agent spanning expertise without bounds.

 Sophocles: The Sphinx’s riddle

Written in the fifth century B.C., Oedipus the King is one of the most famous pieces of literature of all time, so it makes sense that it gave us one of the most famous riddles of all time.

What goes on four legs in the morning, on two legs at noon, and on three legs in the evening?

A human.

Humans crawl on hands and knees (“four legs”) as a baby, walk on two legs in mid-life (representing “noon”) and use a walking stick or can (“three legs”) in old age.

A modern interpretation of the riddle may not allow for the correlation and solving the riddle.  As such “three legs”, i.e. a cane, may be elusive, as we think of the elderly on four wheels on a wheelchair.

In all sincerity, this article is not about an AI rules engine “firing rules” using a time dimension, such as:

  • Not letting a person gain entry to a building after a certain period of time, or…
  • Providing a time dimension to “Parental Controls” on a Firewall / Router, the Internet is “cut off” after 11 PM.

Adding a date/time dimension to the question may produce an alternate question. The context of the time changes the “nature” of the question, and therefore the answer as well.

IBM didn’t inform people when it used their Flickr photos for facial recognition training – The Verge

The problem is more widespread then highlighted in the article.  It’s not just these high profile companies using “public domain” images to annotate with facial recognition notes and training machine learning (ML) models.  Anyone can scan the Internet for images of people, and build a vast library of faces.  These faces can then be used to train ML models.  In fact, using public domain images from “the Internet” will cut across multiple data sources, not just Flickr, which increases the sample size, and may improve the model.

The rules around the uses of “Public Domain” image licensing may need to be updated, and possibly a simple solution, add a watermark to any images that do not have permission to be used for facial recognition model training.  All image processors may be required to include a preprocessor to detect the watermark in the image, and if found, skip the image from being included in the training of models.

Source: IBM didn’t inform people when it used their Flickr photos for facial recognition training – The Verge

When and How to Create Journey Maps

Journey Maps are excellent as a tool for deriving requirements, as well as better understanding the customer.  Similar to a paper-based, use case process to understand an “Actor” on their business workflow, journey maps visualize the customer/user experiences.  The article below is a primer to the creation and usage of a Journey Map.

Summary: Journey maps combine two powerful instruments—storytelling and visualization—in order to help teams understand and address customer needs. While maps take a wide variety of forms depending on context and business goals, certain elements are generally included, and there are underlying guidelines to follow that help them be the most successful.

What Is a Customer Journey Map?
In its most basic form, journey mapping starts by compiling a series of user goals and actions into a timeline skeleton. Next, the skeleton is fleshed out with user thoughts and emotions in order to create a narrative. Finally, that narrative is condensed into a visualization used to communicate insights that will inform design processes.

Source: When and How to Create Customer Journey Maps

Microsoft’s Azure DevOps – Planning Poker Estimation Tool

Although I’ve been a huge fan of PlanningPoker.com since 2011, my Scrum Product team consisted of more than five members, and their Free Membership allows up to 5 users. The team I was working with had just started their agile transformation and was trying out aspects of Agile / Scrum they wanted to adopt. They weren’t about to make the investment in Planning Poker for estimations quite yet, so I stumbled across an estimation tool as a free add-on to Azure DevOps.

Microsoft’s Azure DevOps solution is both a code and requirements repository in one. Requirements are managed from an Agile perspective, through a Product Backlog of user stories. The user story backlog item type contains a field called “Story Points”, or sometimes configured as “Effort”.

Ground Rules – 50k Overview

All team members select from a predetermined relative effort scale, such as Tee Shirt Sizes (XS, S, M, L, XL) or Fibonacci sequence (0, 1/2, 1, 2, 3, 5, 8, 13, 21, 34…) All selections of team members are hidden until the facilitator decides to expose/flip all team selections at once. Flipping at once should help to remove natural biases, such as selecting the same value as the team tech lead’s selection. After that, there’s a team discussion to normalize the value into an agreed selection, such as the average value.

Estimate New Session

Integration with Azure DevOps

The interesting thing about this estimation tool is you can explicitly select stories to perform the effort estimation process right from the backlog, and in turn, once the team agrees upon a value, it can be committed to the User Story in the Backlog. No jumping between user stories, updating and saving field values. All performed from the effort estimation tool.

Agile Mind Games – the Psychology of Scrum

Team Effort Estimations Are Critical to Accurate Velocity, Maximum Productivity, and Team Building.

The team tech lead may provide an effort estimation with little or no input from the developers and/or testers doing the work.

If the tech lead vocalizes his/her effort estimation…

  • BEFORE the developer who will be doing the work, the developer may feel pressured to agree with the tech lead’s estimate.
  • lower than the developer’s guestimate, who will be doing the work, this might create social friction and inaccurate velocity.
  • WITHOUT a collaborative approach, a comprehensive estimation may be ruled out, such as consideration for not only dev. and test., but infra (configuration management, i.e. build & deploy) and other effort costs.

Using tools like Planning Poker, where all estimations are revealed at once helps the team appear to not contradict one another. The negotiation process occurs after all teammates flip their cards at once. Derives better estimates with more perspectives not factored in based on a single Tech lead providing the estimation.

Transparency and Scrutiny

Many “hands-on” project/product stakeholders want maximum transparency into the current state of the product regardless of the duration of the sprint (e.g. 2-week sprints),   Typically, a pulse on the product at two-week increments satisfy most.

Some of the agile, change management tools such as Microsoft Azure DevOps offer dynamic graphing and reporting.  Product stakeholders may be provided dynamic dashboards, that include Burn Down, and Burn Up charts based on the sum of effort from user stories (i.e. product backlog items).  At any given time charts can predict velocity, and based upon the outstanding, total effort estimation, can chart a course to the next release.

Meaningful burn up and burn down charts rely not just on accurate effort estimations, but the people who are assigned these user stories constantly update the status of these stories, e.g. New; In-Progress; In-Review; Done. Countless times I’ve seen team members update the user story status the day before the sprint close/demo, from New -> Done.  This habit gives any product stakeholders a false view of the product within a sprint.

Another challenge and opportunity with Transparency and Scrutiny within a given sprint, is making sure each user story has one or more (child) tasks.  Defining tasks provides a wealth of opportunity, such as naming all of the tasks to complete for the story, e.g. database tasks, UI tasks, etc.  If the tasks are itemized, they may also be assigned to multiple team resources, and show a delineation of labor.

Sticking with the Azure DevOps tool, Tasks have a default field, “Remaining Work”.  This field may express task work in hours or days, the unit of measure. In the beginning, tasks are populated with the total task guesstimate of hours. Each day the person assigned the story task may draw down on the task to incrementally show progress within the task and correlating story.

Task, Work Remaining field must be relentlessly updated across the Backlog in play or else it will create more harm than good. At this level of scrutiny on tasks are amorphous and will be challenging to garnish any projected value.

The Abominable Blocker

What, you can’t figure it out on your own?

The dreaded blocker has the ability to stop a Scrum team in its tracks. The term Impediment used synonymously with the word Blocker, has an innocuous sounding sentiment. Your Scrum team may use either, perhaps a less severe issue merits an Impediment?

The Kanban / Scrum board may have a column in the workflow called Blocker, which should fixate your team on helping to remediate that Blocker. Our Daily Scrum of 15 min may focus on Blockers as they have been isolated in our workflows.

Conquer the blocker before it conquers you!

Applause, Applause

Closing and Demo for Sprints should follow healthy applause from the team, including Stakeholders and Product Owner. Positive reinforcement of a job well done. We’ve completed what we committed to complete, should be followed by applause. We should take a moment to soak in the feedback.

Pass the Mic

For those of us on the Scrum team who are introverts and actively look for ways of dodging opportunities to speak, this one is for you. During Daily Scrum, pass the facilitation mic around where everyone gets an opportunity to facilitate per stand up.

Allow all people within the team an opportunity to demo the “Done” user stories on sprint close. It’s not to break folks out of their shell, it’s to impart a sense of pride in the work accomplished, and truly resonate the one team mentality.

Disclosure: the opinions provided are my own and do not reflect that of my clients, or anyone I represent.

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