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Tag: Business Analysis

Progressive PMOs are harnessing the power of Citizen Developers

Written by Paul Oppong on . Posted in Articles.

A few of my colleagues raise eyebrows when I mention that I used to be a programmer back in the days, I am not talking about assembly language, but I could write a few things in Java and C++. Recently I picked up some new skills creating Power Apps, connecting data with Microsoft Dataverse, building Power BI Dashboards, automating processes with Power Automate, and building chatbots with Power Virtual Agents whilst preparing for Microsoft’s Power Platform Fundamentals certification. This is part of a growing trend of what has been termed Citizen Development.

Citizen development is an innovative approach to dealing with application development needs that a lot of Project Management Offices (PMOs) are now adopting. This innovative and inclusive approach to application development addresses the ever-increasing need for PMOs to keep abreast with technological change and the associated demand for user-friendly, hassle-free applications. Enterprise Technology departments are not always best to shoulder all the responsibilities related to digital transformation.

That’s where the inclusive idea of citizen development comes in as a broad-based and innovative solution. It enables project managers and implementers to develop applications on their own and in accordance with the most pressing PMO needs. Of course, they need to have advanced level of digital skills to use the low-code/no-code (LCNC) platforms, but with those skills taken for granted, almost any team member could take a stab at it.

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Citizen development has multiple benefits for the PMO and project management. By project management, I mean its agile and strategic version. Initially, this is far better for the current needs of success-oriented PMOs. Although traditional, waterfall types of project management would also gain. The benefits span many different sectors, whether it be public sector agencies, financial services, or non-governmental organizations. There is growing evidence that citizen development works, and that it works well for both organizations and individual employees. Let us examine what these benefits are and why they are important for the PMO and project management, irrespective of the field.

Cost-Effectiveness

This is an obvious one. With application development demands being extremely taxing on Enterprise Technology departments, LCNC platforms provide substantial cost-saving opportunities to PMOs. PMOs can thus channel the savings to other, under-resourced needs. Experts estimate that by using LCNC resources, applications can be developed 10 times faster when compared with traditional methods.

PMOs can also expect savings on the maintenance of the new applications. Maintenance and application support are normally separate line items in operational budgets. Higher-end products usually require significant inputs to avoid disruptions and breakdown. The maintenance and support cost are minimal for the applications developed by citizen developers. The overall cost to develop and maintain LCNC -based applications is estimated to be 74% lower than the cost of traditional development led by Enterprise Technology resources. In addition, LCNC platforms hosting present sizable cost reductions, as shown by the experience of Aioi Nissay Dowa Insurance. The company was able to save $1.4 million because of creative use of LCNC tools.

Breaking Down Silos

As citizen developers engage in software or application development, coordination with other business units of an organization becomes an absolute must. LCNC platforms do not require expert digital skills to use, but they need citizen developers to ensure that the end products are relevant to the PMO’s needs. From the perspective of effective PMO role, this is a great way of breaking down silos, which exist in all organizations. Improved teamwork and camaraderie are the important by-products of citizen development, which have long-term benefits. Citizen developers cannot go it alone, and it always takes a team effort to ensure that the end-product meets the critical needs of an organization. Importantly, this includes coordination of Enterprise Technology and non- Enterprise Technology resources too.

Agility

Citizen development also has the potential to make the PMO more agile. It expects non- Enterprise Technology resources to demonstrate adaptability and willingness to learn – two key attributes of an agile organization. From the perspective of the PMO, citizen development becomes a new and unconventional way of spurring continuous learning as an iterative and inclusive process.

Innovation and Creativity

By encouraging non-Enterprise Technology department resources to become software and application developers, PMOs can create a workspace conducive to creativity and innovation. As it happens, when people are given space and opportunity to punch above their weight, they usually outdo themselves by coming up with something extraordinary. Citizen development consequently becomes a great approach to egging people on to think outside the box. Agile organizations need to be innovative and creative. Equally, they need to be adaptive and committed to continuous learning.

Digitisation and Organizational Culture

The more employees get involved in citizen development, the better for the PMO and digital transformation. As PMOs take steps to adapt to the needs of digital transformation, citizen development becomes a timely and cost-effective method. It nurtures an organizational culture favourable for project resources and other non-Enterprise Technology resources to embrace change and make it work for themselves and the organization. It is this type of culture that becomes pivotal in weathering the storm of imminent changes and making the most of new opportunities for development.

Relevance and Flexibility

The involvement of PMO resources as citizen developers warrants the relevance of newly developed software and applications. No one could be more intrinsically motivated to ensure that they serve the purpose than the end-users themselves. I’m sure you can recall cases when even very expensive IT products turned out to be missing the mark. When developed in isolation from an organization’s core strategic goals and needs, they become underutilized. With less stringent requirements imposed; citizen developers have more flexibility to adjust as they go. As application development becomes faster, citizen development makes it easier to maintain the end products.

Summary

Citizen development has been winning over an increasing number of progressive PMOs and organizations. There is growing evidence that it leads to substantial cost-savings, encourages innovation, and makes organizations more agile. PMOs use it effectively to ease the workload of Enterprise Technology resources. Such departments are often understaffed or incapable of dealing with an ever-increasing list of requests and demands.

Citizen development makes a valuable contribution to an organizational culture that promotes creativity and initiative. In the current era of digital transformation, it is critical for agile organizations to create opportunities for their employees. This is to test and improve their digital skills. The experience of organizations that have embraced LCNC platforms for their non-Enterprise Technology resources to develop new applications shows that citizen development is definitely worth the effort.

A turning point for prescriptive analytics? Can a technology on the edge go mainstream?

Written by Andrew Usacheff on . Posted in Articles.

Imagine you are the CEO of a major corporation. You’re sitting in a conference room, surrounded by bright people, facing down a strategic decision. You need to know whether your company should make a big investment in an emerging sector or not. So, you turn to your best data analysts, and you ask them what you should do?

If you are a layman, you might imagine that this is a reasonable request. After decades of amassing data on every conceivable aspect of your business and marrying that with the seemingly endless statistics compounded by governments and third parties, an analyst should be able to give you a reasonable answer to a pressing business question. But it doesn’t work that way. While data tends to be extremely good at telling us what might happen in the future, it is largely powerless to tell us what will happen when we make a large, strategic decision.

A recent survey of business leaders, for example, found that although 99% of Fortune 1000 companies are investing in data and AI, only 30% feel they have a well-articulated data strategy.

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In data terms, this is the difference between predictive and prescriptive analytics. The former, which is used by businesses every day, tell you what is likely to happen. It’s important to note that it’s not a perfect crystal ball, but even knowing the future within a range of certainty is incredibly useful. It can tell us which prospects are likely customers, who are likely to buy something, or when your operations might become overloaded. All of that can inform decisions, especially in limited, tactical ways.

However, it doesn’t address the larger questions that many would like answered. Those questions fall into the domain of prescriptive analytics, which seeks to understand the outcome of a particular action. Prescriptive analytics doesn’t merely stop at the likely future, it tries to identify the best actions you can undertake to affect that future. According to Gartner, it answers questions like “what can we do to have this happen” or “What should we do?”

On a small scale, prescriptive analytics is seeing increasingly widespread use. One of the better-known examples is Amazon’s pre-positioning of products based on predictions of demands. You can also find it working well in industrial maintenance. Companies are using it to make decisions about what to do and where to send workers before they are needed. Such anticipation has also been scaled into systems that greatly increase efficiency and reliability.

With anything like prescriptive analytics, however, it’s extremely important to make a distinction between point solutions that resolve specific situations, and strategic solutions, which can answer any unanticipated decisions you have to make. Prescriptive analytics solutions today tend to “ride on rails.” They work very well on a particular task but cannot generalize beyond it.

Of course, the real promise of prescriptive analytics is not to resolve limited difficulties but to be generally useful to the business as a whole. To get there, we will need to resolve to solve at least four outstanding issues:

Relevant data. Right now, prescriptive analytics tends to be effective when it has large amounts of highly relevant and useful data are readily available. For example, geophysicists are currently using it to find the optimal location for dating oil and gas wells. To do so, they employ models that incorporate ocean surveys, seismographic data, capital cost information, as well as unstructured data sources, such as images taken inside test wells. To make a single decision they analyze literally terabytes of data. Of course, such decisions may also save millions of dollars, so it’s important to get them right.

A similar amount of data is also needed for more generalized business decision-making. We need to be able to incorporate everything from demographic databases to videos and social metrics into the pool for analysis. Of course, this is possible today, but it can typically only be done when compiled by a skilled analyst in products like Excel or more sophisticated tools like SAS. Such ad hoc solutions can deliver value, but they require a considerable investment that isn’t available or reasonable for most decisions.

Collections of ready-made models. While we can create prescriptive models for specific purposes, businesses will need to have ready access to a wide range of models that address the wide range of decisions a business needs to make. While no one could ever anticipate all potential use cases, the world has plenty of examples of shared resources used to overcome analogous problems. Today, it is possible to collect a database of relevant, working models that can cover most likely economic conditions and circumstances — especially if a marketplace could be developed for sharing and selling them.

Modeling tools. Something, for the course, will need to bring this together: an analytics platform that can understand both the inputs of investment, the ongoing financial activities of the company, and other inputs needed to understand bottom-line results. Such a platform should standardize and categorize models — as well as make them available in libraries for analysts.

Analytics. Obviously, we would also need a suite of superior analytics tools that could be used for all kinds of simulations that might be required. This is the smallest of the hurdles we need to overcome, as plenty of sophisticated analytics platforms already exist that is able to undertake these tasks.

The simple fact is that if we take the right approach, we are on the brink of a much wider application for prescriptive analytics than currently exists, and one that would greatly facilitate data-driven decision-making. While AI-driven predictive insight has aided businesses in innumerable ways, we are running up against its limitations every day. Perhaps, with the application of new approaches, CEOs will finally get the value they’ve been seeking from the massive amounts of data they’ve been amassing. In that way, when it comes time to make big strategic decisions around the conference table, analysts will be leading the way.

Critical Skills Needed for Project Success – Part 2 Translation

Written by Elizabeth Larson on . Posted in Articles.

This article is part of a series and presents the second critical skill that all project managers (PMs) and business analysts (BAs) need for success. This one is about the importance of being able to translate technical complexity into business language. As the technology in organizations has become not only increasingly important to its success but also more complex, the need for business stakeholders to understand its true value has increased accordingly. Both PMs and BAs need to talk to their stakeholders about technology, its use, its value, and the results it produces. The language they use has to be about both the technology and the business and be stated in terminology that stakeholders understand.

BAs have always been translators. From the early days of business analysis to the present we have translated business requirements into specifications that could be designed, built, tested, and delivered. But translation has never ended there. We take technical designs and specifications and translate them back to the stakeholders to be sure they understand what they’re actually getting. We have been translators as technologies and methodologies have changed. So being a translator is nothing new. What’s new is that with more complex technologies like AI, the importance of translation is being recognized.

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Years ago I started a new job as a PM. The team was full of technical jargon when they talked to me (OK) and in their discussions with stakeholders (not OK). I encouraged them to translate what they were saying into business language. So instead of talking, for example, about DB14 or problems with Joe’s program abends, I encouraged them to translate these issues into business language–to talk about Price information and how to fix the results caused by program errors. At first there was resistance, but gradually there was a focus on the business and not the technology. I’m not sure the team was entirely bought into a business focus. After all it’s cool to be able to talk techie. But I had several sponsors comment on the positive change.

The fact is, the more complex the technology, the greater the need for us to help stakeholders understand our elicitation questions so that they can make good business decisions and understand the ramifications of their decisions.

OK, so BAs have always been translators. What in it for PMs? We PMs spend lots of time with our sponsors and executives. I know how tempting it is to try to impress them with our technical prowess. We can easily fall into the trap of  thinking we’re adding to our credibility by showing how fluent we are in the technical language. But far more impressive is understanding the technical terms and concepts well enough to clearly explain how the technology provides value to the organization.

To be successful translators, we need to understand not only the technology, but the business, including the industry, the organization’s goals and objectives, and the specific business area. But what does “understand” mean? On an AI project, for example, we don’t need to understand the details of model creation, but we do need to know that the algorithms being used further the business objectives. We need to be conversant enough in the technology to formulate our questions as well as answer questions that arise.

3 techniques for effective translation

Visual business models are among the best tools for the translator. Process, data, use case, and prototype models help the technical staff better understand the business requirements. Models abstract detailed information and present it in a way that’s useful to all audiences. Abstraction, of course, is the process of filtering out extraneous information, leaving only the essential details. Most people find models way more useful than requirements written in a lengthy list of “shalls,” which is how we used to document them.

When we translate, we also need confirmation from the business. Visual business models help translate back from the technical to the business stakeholders. The emphasis, of course, is on business models, because we don’t want to hand technical specifications or designs to our stakeholders without translations into business language.

Synthesis. Being able to translate means we need to take in a lot of information at once and almost instantaneously sort through it, discard the extraneous, and present the most important concepts. What helps us is understanding the context of the topic at hand. And we need both business and technical context. This allows us to take disparate facts gotten in previous conversations and put them back together in a framework that helps the business understand what we’re talking about and how they’re going to get value.

Elicitation. In Part 1 I covered elicitation, saying that we ask questions and listen to the responses, and that’s how we learn. There are times during translating when we need elicit information. For example, if we’re providing stakeholders information on AI results based on the algorithm used to create those results, we may want to ask the model creators why that algorithm was used or how it helps the business. Once we have this information, we can be confident that our explanation to the stakeholders is both technically accurate and valuable to the business.

Translation is critical to project success. It’s one of those skills that sounds easy, but which takes knowledge and a mastery of various skills. Translation is part of what distinguishes us from the order-taking BAs and PMs who are less valuable to our organizations.

OKR and Project Management

Written by Giovanny Guillen on . Posted in Articles.

What are OKRs?

OKR stands for Objectives and Key Results. This allows to clearly define the course in a project must be set to achieve the expected result, for this OKRs are established in objectives that can be measured. The OKR method consists, first in establishing qualitative objectives, and second define the strategy to quantify the outcomes and the achievement of these objectives. In addition, it is essential that once the results of the process have been quantified, a retrospective is made to discuss the results obtained (Something that can be associated with the development of agile methodologies).

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One of the main characteristics that enhance the positive impact of OKRs is that they vary between two types of objectives:

  1. Very difficult objectives to achieve. The purpose of these objectives is to motivate the team and exploit their skills to the fullest.
  2. Achievable objectives, which can be developed smoothly by the team.

These two types of objectives must vary and coexist to achieve good outcomes.

What are the differences between OKRs and KPIs?

The main difference between KPIs and OKRs is that KPIs are performance indicators associated with the team and the process with which the results are obtained. OKR is associated with increments to deliver value in an iteration or the final result of an iteration, having a more global reach of the organization.

OKR in Agility

In agility the purpose of each iteration is to add value to the product that is being developed, OKRs can play an important role since they provide support in the efficiency of processes and allow to enhance their value based on organizational goals. In an agile organization, the team needs to define, by themselves, OKRs. This is because there will be no one better at setting the key results than the same team that plans to develop them.

KRs

It is essential to be focused on the KR or key results and this must be differentiated from the tasks.

  1. A key outcome must be geared towards what needs to be achieved.
  2. One task will be how development is proposed.

For this reason, KRs should be prevented from being sorted as a task list.

In order to measure these results, it is necessary to establish a scoring scale:

  1. Between 0 and 1 using decimals
  2. Between 0 and 10 with integers

One of the indicators that must be borne in mind is that the score must be staggered, that is, if we have scores for results that only indicate 0 and 1 or 0 and 10 should be analyzed since they possibly resemble a list of tasks (a situation that has already been described and should be avoided).

The key results for them to be scored should be as least subjective as possible. An example of this can be, for example, if a company has fixed a KR to increase monthly sales considerably, instead of, to fix a KR to increase monthly sales by 10%, the latter will be easier to measure.

A fairly common mistake in the results is that they don’t know how to measure KRs, which could completely divert the development of the activities of a team.

OKRs must always be established at the team level and the work to consolidate them must always be collaborative, it is common that between 4 and 8 KR are established by objectives and that those are evaluated in a period.

The O

The objectives are what guide the development of the KR and are fundamental to know the direction of the project or product that you want to develop. Its fundamental characteristics are:

  1. They must be challenging and inspiring objectives since in this way the team will be motivated to achieve them.
  2. The objective should qualitatively describe what you want to achieve with the result or/and the product.
  3. They must be limited to a period in which they will be developed.

The objectives, unlike the results, can spare with the metrics to be reflected, that is, they do not need a numerical parameter that limits since they are qualitative propositions.

In the objectives there are two key errors that can damage the methodology:

  1. Set impossible objectives; since the people who will develop the activities will be unmotivated under the knowledge that they will not be able to consolidate it. Usually, this happens if the goal is set by a person who doesn´t develop the activities (The principle of self-organized teams is not followed).
  2. Set easy objectives; like the previous one demotivation is generated, in this case, objectives don´t invite to work for them.

OKRs Methodology and Cycle

To implement OKR in your organization or even in your personal life, you have to follow the next steps:

  1. Review or define your annual vision and mission. In the current environment with the changes in the market, laws, economy, and customers preference, it is important to review and validate if these statements are true yet.
  2. Define the strategy to face changes and uncertainty and accomplish with the vision and mission.
  3. Define key objectives that must be aligned to the vision, mission, and strategies. This is a 3- or 4-months cycle. To establish it, follow the next steps:
    1. Define objectives with your team. Each objective must be clear, time achievable, and measurable.
    2. Specify the actions for each objective that can help to achieve it. Each action could represent a project initiative.
    3. Each week, review your progress based on the metrics from every project and analyze if you are in the correct direction.
    4. If you detect deviation improve your OKRs making the changes needed to correct it.
    5. After 3 or 4 months, repeat the cycle with the aim to make changes and improve OKRs again.

Figure 1. OKR Methodology and Cycle

OKRs and Project Management

While OKR is the way to define objectives for a short period, and establish the desirable results, project management, especially agile methodologies, is the way to become those objectives and results into a reality. OKRs allow business and project managers to face uncertain, evaluate risk, and changes in the market to set the direction and to make decisions about what changes are needed in current projects or which projects initiate or cancel.

Figure 2. OKRs and Project Management

The objectives execution through project management allows to gather the information and get the metrics needed to determine if objectives are achieved in a short period, with the aim to execute the OKR cycle again. From objectives, product owners, business analysts, and project managers can organize and plan releases, iterations, and sprints to develop the product.

Figure 3. OKRs and Project Management Alignment

Final Considerations

  1. To develop OKRs one of the keys is consistency in them since it will be useless to start based on them and then never feedback or evaluate them.
  2. It is always good to reference the methodology in already proven models, however, to achieve the maximum potential and understand the development of a specific case it is convenient to study and adapt the OKRs.
  3. OKRs are a very powerful tool, however, it is difficult to strategically guide an organization based on them because:
  • They don’t necessarily have a long-term vision but are set for more limited periods.
  • Lack of management in the evolution of different scenarios and the detection of changes.
  • They only contemplate the results.
  • The processes to achieve results are based on project management.

OKRs can be defined as a tool of the great potential that will allow articulating with other procedures to obtain what would be an organizational strategy.

Top 10 Business Trends To Watch For In 2022

Written by Andrea Brockmeier on . Posted in Articles.

By Andrea Brockmeier, Jason Cassidy, Susan Heidorn, Jose Marcial Portilla, and Mike Stuedemann

While 2021 has been better in many ways than 2020, it doesn’t feel much more predictable. Yet, at Educate 360 we have identified some the biggest trends we are seeing and expect organizations to continue experiencing in Project Management, Business Analysis, Agile, Data Science, and Leadership in the year ahead.

Overall, the theme of working remotely comes through loud and clear and we expect it to impact almost every area that we covered.

Here are our Top 10 trends to watch for in 2022. We’d love to hear your thoughts about our observations and prognostications.

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Project Management

Project Managers as Project Leaders

The recognition that project managers are both leaders and managers is not new, but the need for the leadership aspect of the role has intensified in the last couple of years and will continue to do so in 2022. In fact, we are hearing more organizations using the title project leader as opposed to project manager.

To be sure, the technical aspects of the job such as scheduling, budgeting, and tracking haven’t been eliminated, but the need for skills like influencing, facilitating, communicating and other “soft” skills associated with the PM as leader has become paramount. Project managers as leaders are going to continue to be challenged in 2022 with distributed teams and all the distractions of ever-changing global and work environments. Leading the team and engaging stakeholders to sustain buy-in is going to continue to be job one for effective PMs in 2022.

More Organizations Using Project Management Tools

In 2022, expect to see a continued increase in the use of project management tools beyond the standard Microsoft Office suite. We used to see only the occasional client using a PM application of any kind and it was almost always Microsoft Project. Whether because people are working remotely, tools have become more cost effective, or tools have become more accessible and easier to use, we see more organizations using PM-specific tools and we’re seeing a wider variety of tools, as well.

At first this may seem contradictory to the previous trend of project leadership getting emphasized over project management; tools are not generally used for the leadership aspects of the PM role. Perhaps these trends are mutually reinforcing in that tools like Asana, Wrike, Easy Project, Smartsheet and others help with project management which allows the PM to tend to the demands of project leadership. Whatever the reason, we look ahead to 2022 as a robust year for PM tool implementation.

Business Analysis

Strong Facilitation and Communication Skills for Remote Business Analysts

We have all have heard about the Great Resignation – employees leaving their jobs in record numbers in search of better pay and career opportunities, a healthier work-life balance, a less toxic working environment, and desire to continue to work remotely. As a result, many companies are reducing their carbon footprint as well as costs, so they either have smaller offices, holding a space for meetings or providing “hoteling” spaces when employees need or want to go into the office to work. Organizations are also realizing that they can hire talent around the globe.

So, what does this mean for business analysts? It means we must get better at communicating and facilitating in a virtual environment. We must learn how to build trust when we can’t directly “see” stakeholders daily. We must be able to facilitate virtually to ensure we elicit inclusive requirements and not just those from a few vocal stakeholders. We need to learn to creatively collaborate with our team members, colleagues, and key stakeholders to ensure we have their buy-in.

BAs need to think about communicating and facilitating with more intention. This calls for mindful facilitation as opposed to simply the ability to use Microsoft Teams, Slack, or other communication platforms. We are already starting to see – and we continue to see in 2022 – more BAs focus on learning how to create safe, trust-laden, and collaborative environments within which stakeholders readily share information in a world that has been changed forever.

Digital Transformation Strategy Supported by Business Analysis

Digital transformation has been a trend for some years, and it is still going full steam ahead. Yet, most of these efforts fail. There are many reasons cited for this failure; among the most common include:

  • NOT understanding the business problem, but instead just throwing solutions or technology at the wall to see what sticks.
  • NOT determining success criteria so organizations have no way of knowing if the initiative has been successful because there was not a shared understanding of what success looked like.
  • NOT realizing that digital transformation introduces cultural changes in the organization (which is also one of the reasons many organizations had difficulty adopting agile).

Because of these failures, organizations moving toward digital transformation will rely more on business analysis capabilities to effectively address root causes of the problems above. BAs will be used on digital transformation initiatives to ensure the business problem or opportunity has been fully analyzed and understood, to verify that the organization is ready to adopt the new culture, and to identify overall success measures as well as identifying smaller, incremental success measures that can be measured throughout the project.

These efforts will also require a business analyst’s in-depth knowledge of agile business analysis approaches, tools, and techniques that will be critical as organizations strive to become more agile in their ability to respond to customers and competitors. Look for lots of opportunities in 2022 for BAs to plug in as key strategic resources on digital transformations.

Agile

Teams Continue to be Distributed – By Choice, Not Necessity

It can be argued that the COVID 19 pandemic did more to transform the world of work than any document, framework, certification approach or technology. One of the lasting impacts of the pandemic is that distributed teams are here to stay. Product development team members and their leaders will need to permanently adjust to working in a distributed fashion.

While many still share the perception that all Agile frameworks require co-located teams (see principle 6 associated with the Agile Manifesto), technology has advanced to the point where a team adopting a framework doesn’t need to all be in the same location. Continued discipline, particularly in the area of communication and team working together agreements, will be required as teams shift from distributed work by necessity to distributed work by choice.

Scaling – Addition by Addition or Addition by Subtraction?

The marketplace continues to see the emergence and growth of a number of Agile scaling frameworks. The Scaled Agile Framework (SAFe), Large Scale Scrum (LeSS), Scrum at Scale (S@S) and Disciplined Agile Delivery (DAD) are just a few of the prominent entries in this space. Next year will see organizations continue to adopt these frameworks as they seek to realize the benefits of being more responsive to change at a global level.

Current thoughts are mixed regarding how to achieve this goal. While many of the current frameworks (e.g., SAFe) advocate adding structure and layers, some like LeSS believe that true organizational agility can only be achieved by removing items from the organization that don’t directly contribute to the delivery of customer value. This debate is even more nuanced when the idea that some additional structure might be necessary on a temporary basis while the organization is being transformed. In 2022, we expect to see continued debate as to what steps are actually necessary to achieve agility on a global scale.

Agile Outside of Software

The Agile movement was born in the software development space. After all, it is called the “Manifesto for Agile Software Development”. In recent years, other domains have adopted a number of the values and principles that define the Agile movement in attempt to accrue its benefits. For example, there is currently an Agile Marketing Manifesto as well as efforts to bring an Agile mindset and some of its practices into education.

This trend will accelerate in 2022 as events such as the pandemic, natural disaster, and political and economic shifts remind organizations that the only constant is change.

Data Science

Increasing Application of Artificial Intelligence and Reinforcement Learning

We often hear that Artificial Intelligence is one of the trends that will change the world. This past year certainly validates that sentiment, and 2022 will continue to see evidence of this powerful trend.

But what is actually meant by the term “Artificial Intelligence”? Technically speaking, AI systems typically incorporate a special type of machine learning known as “Reinforcement Learning.” These specialized programs allow a computer to learn the same way a human does, through experience with trial and error.

In 2016, DeepMind (an Alphabet company) made headlines when its computer program AlphaGo beat the world’s best Go player, a feat many previously thought was impossible. The AlphaGo program worked through Reinforcement Learning methods, where the computer played thousands of games against itself, learning the best tactics to win the game of Go.

Fortunately, Reinforcement Learning has applications beyond just board games. In 2021, DeepMind released AlphaFold 2, a computer AI program that can accurately predict protein folding structures, opening up new possibilities in drug discovery and medicine.

The application of AI and reinforcement learning will definitely be a trend to keep an eye on, as the progress has increased exponentially.

Huge Strides to Continue with Natural Language Processing

Natural Language Processing (NLP) is the use of machine learning models to interpret raw text data, such as Wikipedia articles or even code written by humans. Traditionally, NLP technology has been used for classifying text articles into categories or sentiment analysis of reviews. By simply training NLP models on existing text data sets, the models can learn the topic of a new article, or whether a movie review is positive or negative.

Huge strides have recently been made in the capabilities of upcoming NLP technology. In 2020, OpenAI released “Generative Pre-trained Transformed 3,” commonly known as GPT-3, which has the ability to generate text that is nearly indistinguishable from that written by a human. GPT-3 was trained on hundreds of billions of words that were scraped from the internet and is even capable of coding in CSS, JSX, Python, among others.

In 2021, OpenAI further expanded on the idea of an NLP model that can code, by releasing Codex and Github Copilot. These futuristic state-of-the-art models can not only automatically complete large portions of code, but they can also accept a description of what the code should do and produce the corresponding code. Check out this Codex demo launch video.

The future is already here! We are definitely looking for exciting new applications of NLP continue to make headlines in 2022.

Leadership

Attracting & Retaining Talent – But Different Than Before

Attracting and retaining talent is the most prominent topic of conversation we’ve observed in media related to leadership, specifically attracting and retaining talent in a COVID-changed environment. It’s not clear anyone has permanently figured out the solution as the situation is still in flux, so we have listed key points that we hear leaders weighing in with in their decisions related to remote work and its implications for finding quality team members.

Let’s start by making a broad assumption (that certainly can still be refuted) that some jobs cannot be done remotely (e.g., printing and shipping) and some jobs potentially can be done remotely. Below are the key topics of debate that will continue to shape this discussion in 2022:

  • Job Equity: Is it fair to the people whose roles cannot be done remotely and who have to come into the workplace that others can work at home? As this question is discussed topics related to safety, expenses, commute time, flexibility, teamwork, fairness all come into play.
  • Productivity: Even if jobs can be done remotely, what is the level of productivity of remote work versus work in the office? As this question is discussed one hears that people work longer hours at home because they are not commuting, that people are more productive at home because they can focus and not be disturbed. On the other hand, you hear others say that people are less productive at home because they are distracted by non-work items and that people are less productive at home because they are not being watched. You also hear discussion of managers’ ability to manage in-person versus remote team members.
  • Cultural Impact: Even if a job can be done at home, is it better for the organizational culture? As this question is discussed topics related to collaboration, mentoring, camaraderie, organic problem solving and innovation, and work-life balance come into play.

These debates and questions will dominate leadership conversations in the coming year as leaders continue the challenge of finding and hanging on to top talent.

Jason Cassidy, PMP, is CEO of Educate 360, the parent company of Project Management Academy, Watermark Learning, and Pierian Data. – training partners of choice helping organizations improve organizational efficiency and effectiveness, increase cross-functional alignment, and drive results to help meet and exceed business performance goals.

Andrea Brockmeier, PMP, is Director of Project Management at Watermark Learning, an Educate 360 partner company. Dr. Susan Heidorn, PMP, CBAP, BRMP is Director of Business Solutions at Watermark Learning. Jose Marcel Portilla is Head of Data Science at Pierian Data Inc., an Educate 360 partner. Mike Stuedemann, PMP, CST, is a Scrum-Focused, Agile Agnostic Coach and Trainer at AgilityIRL and partners with Watermark Learning for Scrum courses.

Join our webinar on December 10 to hear our contributors talk about these trends and answer questions.