A Common Scenario

With every passing milestone Stakeholders’ confidence declines each time their expectations aren’t met. Underwhelmed by the lack of quantifiable benefits, a Stakeholder’s original optimism starts to transition into a series of micro concerns. As these micro concerns gather momentum, a two track schedule starts to form.

While the core schedule remains the key focus of the initiative team, it’s not uncommon for a small number of critical resources to be diverted away to carryout some spot-analysis tasked with dealing with Stakeholder queries and questions. The parallel schedule that emerges inevitably impacts the original schedule, and expands the next iteration deliverables as they absorb the new activities designed to course correct.

Current Agile Coaching & Consulting Practices

Whilst it might not always be possible to spot decreasing levels of confidence amongst an initiatives Stakeholder’s community, there are a number of potential triggers, which are more visible. If any of these surface the initiative team should be ready to take action to mitigate the risks they present in the short, mid and long-term. And most importantly, the entire initiative organisation, including, stakeholders, core team, contributors and customers must be prepared to make an ‘inflight’ transition from a activity-based to an value-based way of working.

Six opportunities for an AI Agent

1. Unable to measure the real-time return on investment 

2. Increased hesitation to making further investment

3. Implementation is in a constant state of change

4. Lack access to subject matter expertise

5. Time consuming project and governance management  

6. Infrequent assessment of the original business case

MONETICAL guidance on how to ….

Unable to measure the real-time return on investment 

If after several months into the schedule the team is unable to articulate (demonstrate to the Stakeholders/Clients) the value that has been created for the costs incurred so far? return on investment: expenses increase on a daily basis (e.g. staffing, facilities and T&L) against operational or commercial savings, or income; due to the lack of any released or deployed features, the organisation has no tangible benefits to speak of.

Activity-based initiatives (i.e. waterfall) typically suffer from this scenario. Whilst the initiative team is focused on the planning and the completion of activities, stakeholders are focused on value created.

Opportunity of an AI Agent

As investment (costs) increases daily without any formal mechanism to accurately carryout a time-based ‘return on investment’, the inevitable outcome is a big-bang, single release.

The software develop life cycle (SDLC) typically results in an irrational order of work. Must Have capabilities are not released until other lower value capabilities are also available. This delays the moment any true value is derived from the investment. The investment costs balloon because they include many non-value added activities, e.g., handovers and complex and regular planning, all take a portion of the investment, but without the need to demonstrate where value materialises.

Increased hesitation to making further investment

Stakeholders are constantly seeking re-assurance from the initiative team. Does it have the right competencies, has it truly understood the needs of the customer. As initiatives become more complex as a consequence of an ever-enlarging technology foot-print due to its expansion across the organisation; showing further returns for the increased investment creates multiple challenges as a result of the current function by function structure. These structures introduce additional complexity because the ‘definition of value’ is varied. operation focus on efficiency/speed, customer services focus on call volume, marketing focus on campaign success.

Opportunity of an AI Agent

The deployment of an AI Agent that can accurately measure the complexity of the current value chain, which the initiative is aiming to serve.

But understanding the characteristics of the initiative business objectives and key results, through to inderstanding the profile of the initiative teams, the AI Agent is capable of surfacing skills and knowledge limitations and their impact on the progress of the implementation.

OKRs - Features - Competencies - Job spec - Individuals - Resumes

Implementation is in a constant state of change

Is the current implementation phase undergoing an unusually high number of change requests?

Initiative complexity leads to unplanned internal and external factors that drive change. Change can be driven by unusual levels of independencies, changing customer needs and the general uncertainties of software and technology. While the adoption of Agile ways of working seeks to break down monolithic deliverables into more manageable units of business value (i.e. atomisation), which are then delivered via a series of tightly controlled time-boxes (iterations), understanding both the contribution to current operational efficiency and the emerging risk profile becomes an expensive data management effort.

Opportunity of an AI Agent

With the completion of each iteration, the AI Agent captures a wealth of information pertaining to all aspects of this mini project (iterations), the quality of teh deliverable, the team and the competencies involved, the level of direct customer/user iteration, the value of measurable value created and the location of the both the team and stakeholders, all provide a comprehensive picture of inferences.

With such a wealth of operational and commercial information available the AI Agent - it has the capacity to identify performance inference (positive and negative factors) and using appropriate analytical capabilities provide real-time capability and risk reports, complete with the appropriate consulting advice.

Lack access to subject matter expertise

From time to time implementation teams discover certain subject matter expertise haven’t been identified or scheduled to engaged on the initiative, the lack of their engagement is causing delays?

Although many initiatives create and maintain a detailed delivery schedule with an associated resource plan (engaging SME), the complex nature of these initiatives results in a lot of volatility and changes to the order of activities. If these are not managed tightly, initiatives may find they’re ready to complete a particular task, i.e. the requirements are clearly defined, technical perquisites have been met and any associates risks or decisions have all been completed; however, critical resources are not available to take advantage of the recently emerged opportunity. 

Opportunity of an AI Agent

The opportunity to discover what key competencies are required to successfully complete the implementation of a Feature, based on an analysis of the contents of the requirements (user stories), is a very powerful resource management capability.

These powerful resource management capability can be extended to include creating an upskilling strategy or outsourcing, should the AI Agent discover the competencies that are required are currently not contained within the Initiative Teams job profile or skills record.

Understanding how current needs and wants are to be met by current and future capabilities and availabilities is one of the many emerging initiative optimisation opportunities, which MONETICAL intends to provide a dedicated consulting self-service initiative program for.

Time consuming governance management  

Current project performance reporting (generation, analysis and presentation) and governance model (alignment, decision-making, and risk management) are extremely time consuming. In many situations, events are moving so fast that the appropriateness of the information, plans and actions has deteriorated by the time is complete.

With so many activities simultaneously underway, monitoring, analysis and reporting on their status requires significant effort. Regular weekly meeting have been establishing involving an ever-growing array of representatives, which calls for the hiring of a full-time project manager (PM). The PM has sole responsibility to gather the data necessary from all engaged parties and systems to develop a clear picture of what is happening at any given moment and chairing the meetings.

Opportunity of an AI Agent

The fifth AI Agent MONETICAL initiative program provides step-by-step guidance on - how to design, development and validate (testing & release), will reduce, if not eradicate many of the prepeative project management and governance activities.

Consulting self-service advice empowers the appoint development to efficiently create a product backlog describing the core features for these two use cases (project management reporting & governance alignment, decision-making effectiveness & risk management).

Consulting advice incorporates designing the necessary data model, use cases (use journeys), data repositories and RAG (Retrieval-Augmented Generation) the a architecture that combines an information retrieval system with a (LLM) to produce contextually relevant responses.

Infrequent assessment of the original business case

Organisations are operating in an ever-increasingly complex and volatile environment. Combined with internal factors such as resource changes, ongoing project performance and financial matters, results in an erosion of the accuracy, suitability and confidence level of individual business 3, 6, or 12month from when they were first approved.

Upon approving the business case and the subsequent allocation of funds, these single polarised perspective that captured in a moment in-time, business cases are typically confined to the bottom draw and rarely referred again.

As a consequence of such a static approach business case governance, it’s not uncommon for incremental changes are made to the objectives and key resulst that were developed from the original business case have been revised, possibly multiple times as aprt of a quarterly business review cycle; however, some of the core principles and aims (goals) described in the business base have been overlooked.

Opportunity of an AI Agent

The opportunity to efficiently evaluate (benchmark) the context of a business case, its associated business objetcive and key results, against the current Feature roadmap (i.e. schedule when business value is intended to materialise) is a powerful proposition.

Having a constantly alive business case, which in all intense and purpose if a hypothetical statements of what the business leaders how will happen, that is suject to a rapid evaluation and verification process represented both highly valuable technical & commercial opportunities.

The consulting self-service initiative program guides the initiative team through the stages and activities necessary to develop such an AI Agent. And AI Agent that has the capability to constantly inspect and adapt the business cases, analysing the inference of external (marketing, competitor and technology developments), to deteremine its current accuracy, the internal (financial capability, resource competencies and internal priorities), all against the current implementation schedule for alignment.

Consulting Self-service Initiative Program

The business value that these AI Agents promise is extremely high. However, to produce them in a cost, efficient and technically competent manner requires a wealth of know-how. Know-how that includes, the following……

This is advice and guidance the MONETICAL Consulting Self-service Initiative Program provides.