Henning Zeumer - Henning Zeumer Projektmanagement

4 Alternatives to rescue a Project in Trouble

When projects get into crisis situations, several factors are usually responsible in an ominous mélange. This makes it difficult to “spot” these root causes and then address them in a targeted manner.

After more than 30 years of project experience and now over 20 years of practice as the Project Doctor, I have a certain amount of practice in this, especially an eye for where things are stuck. And that’s why I’m quite quick to find suitable countermeasures. My analysis rarely takes longer than 3-4 weeks.

According to this, there are 4 different scenarios for how my clients can deal with my stabilization and improvement suggestions:

1. Take note of my analysis with gratitude and continue as before

My audit results do not always “taste” to everyone involved. They are independent and impartial, but also mercilessly honest. No one person is “to blame” for the crisis alone, but sometimes some have a more or less large share in it. And then a corresponding part of the work with the restructuring measures comes to them. Not everyone always likes to go along. Especially if one of them even benefits from the imbalance.

Project Management Recovery Albert Einstein

If the steering committee cannot agree to follow my recommendations, then that’s it. But that is not really an option that will lead to the stabilization of the project. Because it is not possible to get out of the problems that led to it with the same methods (to paraphrase Albert Einstein).

2. Give my to-do list to the internal project manager for implementation

This can work and reduces my consulting costs like Alternative 1 to the crisis analysis. In this case, however, the internal project manager must also be given the competence to demand and maintain what is necessary to carry out the recovery measures. And he must be up to the crisis job, methodically, practically and with the necessary conflict resolution and leadership qualities.

In fact, internal colleagues keep confirming to me that I receive things in a timely manner that they have been fighting for months without success because they are supposedly too expensive. The prophet counts for nothing in his own country, that is well known, but if my analysis brings about such insights and concessions to effective problem solving among the decision-makers, then I have a good feeling, provided that they have a competent internal project manager.

3. Let me coach the internal project manager to success

In more than half of my restructuring mandates, this is the option of choice. There are several reasons for this: What you have least in a recovery is time. The internal project manager knows the project, the team, the objectives and tasks, the stakeholders and the “situation mix”, which I would have to familiarize myself with for some time. I can take this time during coaching, and we still achieve sufficient effectiveness in problem solving right from the start.

As a coach, I can fill existing project management gaps, am a sparring partner and advisor, support the internal colleague vis-à-vis stakeholders and the executing organization, and am an eye and ear for risks and side effects. However, I do not take on any direct project accountability, distribute homework and keep or adjust it. As a result, my effort is usually limited and my costs for the customer are lower, without any loss of quality or effectiveness.

Positive side effect: The internal colleague and, if necessary, the executing organization also learn from me to become more mature in its project management and thus more crisis-proof.

4. Replace the internal project manager with me

Sometimes, however, it also happens that the internal project manager has been lost or needs to be replaced. This is unfortunate insofar as the time advantages of option 3 do not come into play and my engagement requires a higher commitment, at least in the first weeks and months, sometimes 24/7, until the project runs in more stable waters again.

The project and the advised company receive my full support for this from the very beginning; I take over the operational responsibility and only hand it over when an internal project manager has been found who can successfully complete the project. Even then, I will be happy to continue to be available as a coach in an advisory role.

Conclusion:

Of the 4 alternatives, only the last 3 are really an option to save projects in distress or even emergencies. But these are always significantly cheaper than Alternative 1, which usually only continues, and in the end potentially even writes off the ongoing, too high costs without any prospect of improvement. It’s as if you haven’t taken advantage of any restructuring advice in the first place.

All 3 other options successively save the opportunity costs and, on top of that, secure the business benefit for which the project was once set up.

Please also visit my corresponding Project Recovery offering

Consolidation = Time to relax ? Project Recovery !

You could think that in times of economic uncertainty, every CxO, VP, division or department manager would not only be careful with their investments and budgets, but also seek to solve problems and imbalances in their ongoing projects. Project Recovery? Turnaround Management? Many put (not only such) projects “on hold”, thus freeing up scarce resources and consolidating them. A pretty good approach, but only one side of the medal.

Because the problems don’t disappear from that. They are only postponed to “better times” or written off expensively and without the hoped-for benefit. Often, they simply continue in the few remaining projects, where they become new “bottomless barrels”. Why? Because the majority of the problems are only symptoms, but the causes are not eliminated. Therefore, no reason to relax !

My lessons learned

in many years of project recovery and turnaround: It is usually not because of scarce or missing resources that projects are not completed as planned. A good project manager can deal with this if he plans realistically and controls effectively. It is much more often due to weak project management – internally in the project and externally into the implementing organization. More than half of the troubles in projects arise from inadequate embedding in and coordination with the organization, the line departments, the customers, and the management. And they can only be solved there, not in the project itself.

A good project manager leads internally and externally. If an internal employee does not succeed as a project manager (or is not able due to the organizational and corporate cultural conditions), an external specialist must be called in for support. He has no blinkers on, can neutrally assess and judge, and does not have to worry about his career if he openly addresses truths. And he brings know-how with him that apparently does not exist in the company. This allows him to quickly and effectively break and resolve problem and cost spirals and is thus much cheaper than if you continue to try with the (already failed) own funds.

The bottom line:

Smart CxOs, VPs, division or department heads are well advised, especially in times of crisis, not only to consolidate, but to get to the root causes of their problems with external help. And this also and especially applies to their troubled projects. Hardly any investment, even if “good money” is taken into hand once more to save “bad money”, is more worthwhile than the turnaround and still achieved business benefits from a distressed project !

Learn more about the Business Case of Project Recovery here…

Digital Transformation: 7 strategic Success Factors

Successful digitalization is an ambitious transformation endeavor. It presupposes a comprehensive transformation of companies, both internally and externally, which requires much more than the implementation of new technologies. The following factors need to be considered: business model, the entire organization with its employees, all operational processes and customer relationships. Digital transformation means exploiting and exploiting the possibilities of digitalization “end-to-end”.

What worked in the first phase of upheaval – competing with digital products and services while leaving the organization largely analogue – will no longer be a viable option in the future. The era of digitalization asymmetries is coming to an end, because they mean inefficient media disruptions in the new, digital processes. The range of solutions and possible solutions differ depending on the industry. Following seven starting points are part of a goal-oriented approach:

1. Systematic review and adaptation of the business model.

It is promising to carry out a “digital due diligence” on one’s own behalf, so to speak – i.e. to check the digital value creation and growth potential in the same way that a buyer would check an envisaged target company. The focus should be on discovering and occupying digital fields of the future on the one hand, and developing a strategy to be a decisive step ahead of competitors in the digital race on the other.

2. Develop fundamental skills in data analysis and use.

Digits - Digital Transformation, Program Management

In increasingly digital markets, those companies that recognize and leverage the value of internal and external data at an early stage will have a head start. Anyone who thinks of sales alone when it comes to monetizing data falls far short of the point. In the broadest sense, companies must generate an economic benefit from it. This can also be to use data to accelerate product (further) development or to optimize processes along the value chain.

This also includes the revision of all previous regulations and rules that may have been necessary for analogous processing. Extensive process analysis and consequent optimization is the basis of digitizing transformation projects.

3. Expansion and further development of the IT and data architecture.

LAN - Digital Transformation, Program Management

The rapid implementation of the aforementioned digital future strategies and optimizations can only succeed on the basis of a suitable technical infrastructure and with capable and powerful teams. The head of a company’s IT department is not necessarily to be promoted the head of digital transformation but should be its powerhouse. Ideally, data, IT and digital transformation should be designed from a single source, but should not be implemented as large-scale projects, but in an agile manner and in manageable sprints, with an overarching, strategic thinking Program Management.

4. Use of software robots and intelligent automation.

To achieve rapid digitalization successes without complex and time-consuming changes to the existing IT infrastructure, robot-assisted process automation (RPA) and technologically more advanced intelligent automation are increasingly coming into focus.

Increasingly, classic RPA applications are being combined with AI solutions, which enables the automation of manual and repetitive activities such as invoice verification or reporting with potential savings of up to 30 percent especially in administration – with a payback period of just a few months. Intelligent automation represents an important lever for companies to enter the AI age and achieve direct and measurable benefits.

5. Seamless integration of new technologies.

Data Network - Digital Transformation, Program Management

Even though the use of artificial intelligence (AI) is currently on everyone’s lips, the portfolio of disruptive tools and applications has reached a much broader spectrum. Web 3.0 as decentralized information transmission, data economy via blockchain or peer-to-peer organizations are constantly conquering more industries and areas. With Metaverse, the internet is evolving into a three-dimensional space. Tokenization, i.e. the digital mapping of assets, is also rapidly gaining momentum beyond the insurance and financial sectors – after all, from a technological point of view, industrial plants, power plants and patents can also be virtually broken down and “tokenized”.

Tokenization and the evolution to Web 3.0 will rearrange the economic balance of power. The result is a market that the state should help to promote through regulation and incentive programs. The race for global hubs is currently entering its second round.

6. Breaking down departmental silos to increase digital innovation.

As much as the IT department may be driving the digital transformation in an excellent technical way, if the other departments remain in their usual hierarchies and processes, the company is going full throttle in neutral gear, so to speak. In order to leverage the organization’s inherent innovation potential, especially in the digitalization phase, the company absolutely needs cross-departmental processes and tools as well as explicit responsible persons who monitor, motivate and incentivize.

7. Initiating a cultural change in the workforce.

Finally, the transformation task also requires an adaptation in culture and leadership. This is important to get employees on board and get them excited about change.

A key success factor is the narrative, even if this sometimes seems overused. Management must explain to employees the advantages and benefits associated with a digital transformation, for the company, but specifically for the individual employee. It is important to build optimism, but also to address risks and challenges transparently and to take risks in a controlled manner.

AI Concerns - Digital Transformation, Program Management

The latter leads to the exciting and emotionally charged question of the macroeconomic effects on the labor market as a result of digitalization accelerated by AI tools. The first estimates are on the market and are attracting a great deal of attention – also in the media. Researchers at the start-up OpenAI, together with scientists from the University of Pennsylvania, have determined that AI applications affect up to 80 percent of all jobs in the United States. For them, at least some of the activities can be done by an AI tool. Almost one-fifth of employees work in jobs where up to half of their activities can be carried out by AI. In another study, investment bank Goldman Sachs estimates that approximately 300 million full-time jobs worldwide can be automated with generative AI.

The labor market debate can be classified with two basic points. First, the end of work and a new era of mass unemployment have been proclaimed by critics in previous periods of automation – but in fact they have never happened. Secondly, the boost in the wake of demographic change probably comes at just the right time for a location like Germany. In the end, with our labor shortage that has long since occurred, we will be happy if AI fills job gaps in the future. Germany also needs a welcoming culture when it comes to the introduction of digital technologies.

Qualifying and re-assignment instead of firing.

There is also a third aspect: Repetitive work is mostly found in administration, where fixed fact-to-consequence relationships and decision-making rules can be digitally automated very easily. It is even conceivable that processes will be further developed and optimized by self-learning AI. Here, human intervention will only be necessary in the form of plausibility and quality checks. An immense rationalization and increase in cost efficiency are possible. On the other hand, as the market becomes more transparent, it requires more customer-oriented services in sales, customer service and after-sales, depending on the business model. As a result, more skilled workers are needed here. Thus, further training and re-assignment of the existing, now released back-office staff, who are often already largely familiar with the processes “at the front” anyway, with job enrichment.

Source in excerpts: Handelsblatt Research Institute, Roland Berger, 2023: State of the Nation – Transformation as a Success Factor

Learn more about the topics Digital Transformation and Program Management …

Program Governance with cascading Meetings and Reports

In the realm of Program Management, as initiatives grow in size and complexity, so does the distribution of information and governance. While adept project managers can readily navigate the intricacies at the project level, scaling introduces a surge in stakeholders, communication channels, and the imperative to tailor information appropriately. To prevent meetings and reporting from devolving into burdensome overhead, but still serve their purpose adequately, structured and strategic communication becomes paramount for programs and large projects. In my experience, cascading structures have proven to be effective for this purpose.

Management Levels of an Organization

To understand this, let’s examine the distinct management levels within an organization, division, or department:

PPM-PgM-P - Program Management, Governance

Portfolio
Oversight of all programs and projects of a Business Unit.
Program
combination of 2 or more projects sharing the same customer, product, or cultural background.
Project
individual customer-oriented project to fulfil one (1) customer contract.

Communication and control within projects

Within the projects, coordination between the teams and sub-projects is essential. This occurs through internal meetings (e.g., daily stand-ups) and interdisciplinary gatherings (e.g., weekly meetings), supplemented by succinct reports to higher level. Project managers collate management information and project status reports for dissemination to steering committees, possibly alongside other relevant bodies such as the Program Management and Portfolio, and the executive Management.

This also follows the premise that the majority of operational decisions should be made at the work and project level, as this is where the technical expertise and granular insight is available. Higher levels are usually not as deeply involved in the subject matter and are chiefly concerned with more tactical and strategic decision-making. In addition, in the case of problems that cannot be solved within the project, they are the escalation level to be invoked.

Communication and Governance beyond projects

At this “superior” level, routine project reviews (e.g. monthly at the committee meetings) facilitate in-depth discussions on status, risks, issues, decisions, and any necessary, further escalations are discussed in detail.

Cascading Governance - Program Management, Governance

If the program or portfolio includes diverse projects, such as customer and product development initiatives, these are aligned and coordinated with each other at this level, complementing continuous efforts at the working level.

The higher-level management is stringently informed about its development and customer projects and can in turn make well informed decisions. Issues can also be escalated cascaded, and resolved.

Prerequisites for efficient communication and Governance

It is important for a functioning distribution of information that does not cause too much additional work

a lean, transparent, end-to-end reporting system.
short, fast escalation and decision-making paths.

At the working level, the number of participants and the lead should be streamlined, agenda and content should be prepared (offline) and results should be tracked.

The reporting is standardized and can be aggregated to the next level throughout. The focus is on control, overview, escalations, and decisions.

Additional communication and information

In addition, accompanying periodic (e.g. bi-monthly) leadership meetings can take place, in which an extended management team regularly informs about strategic development, finances, operational and organizational topics of the industrial business. These sessions may include focused presentations by a predetermined speaker. This is where it’s important to get feedback from the extended team with questions and answers. The results will then also be reflected, if necessary, in corresponding meetings at the Program Management and working level, in order to also take the employees in the teams along on the cross-functional and cross-regional as well as the strategic and operational topics.

Conclusion: Communication, information, and control are critical to success

Communication is repeatedly cited as a particularly critical factor for success in projects and programs. The structured governance approach outlined herein provides program managers with a blueprint to navigate these challenges adeptly, ensuring initiatives progress smoothly and achieve desired outcomes.

Learn more about the topic Program Management …

Think Big: Strategic Program Management

Some time ago, I was called to work for a large electrical company to develop my expertise in program management for a business unit. I wasn’t surprised at first, because large companies also do large, complex projects for which normal project management is not sufficient. I had already experienced this in other engagements, actually even as a cause of project imbalances. The group had already cultivated extensive (multi-)project management, but the methodology for program management was still largely immature.

From Theory into Practice

We started with some workshops on the theory and how program management differs from project management. In essence, in addition to the sheer dimension of the initiatives, this is about all the strategic orientation of programs, often only based on a vision or mission, in the context of which the necessary “tactical” projects as well as operational components are then developed.

By assigning the division’s business activities to this point of view, the structures became recognizable as programs. We then developed suitable governance structures from the working level to the management level and subsequently implemented them in the business unit. Because we can already speak of the implementation of strategy into operational management at the divisional level, I would like to refer to this as “operational” program management in this context.

Program Management taken to the next level

Because in the further development we came across an objective that should go far beyond that. What if the internal objectives of the programs were extended “far beyond the borders” to include complete business relationships with key customers?! In other words, we broadened our strategic view on our customers. Growing our customers’ businesses became our mission – and we would grow with them as a supplier of important components “in tow”…

To illustrate: a plant manufacturer works closely with a petrochemical customer, developing oil and gas fields with them and supplying the equipment required for oil and gas extraction as an equipment partner, possibly even as a general contractor for several or even all of the customer’s sites.

Complete rethinking. This meant that we would think deeply into the business model of our customers, support their activities towards their goals and by the way cover their needs for equipment, systems, etc. for implementation from our production as a “preferred supplier”. At the same time, our expertise (not least in program management!) and closely intertwined support (and dependence of customers) would also grow into a strategic partnership that would be designed for the long term.

Strategic Program Management – The Result

An interesting thought, isn’t it? We have implemented it with two of our “top tiers” and thus multiplied sales and profits with them – compared to other customers for whom we have “only” remained a supplier. I’m not allowed to disclose more here 😉.

Of course, such a strategic partnership requires very deep, mutual trust. The client needs to understand the benefit that comes from our program management expertise and get involved in letting us do a lot of the governance. Not everyone is ready for such cross-company collaboration.

Learn more about the topic Program Management …

Why Project Managers and CEOs are very Similar

These days, as a Project Manager, I had the opportunity to listen to a presentation by real professionals. The management consultancy McKinsey lectured about the role of the CEO in the company, about his important tasks, his contribution to the company’s success, and also about why he receives an appropriate salary for it.

I had to smile. Because I often discuss exactly the same things with CEOs, managing directors, division heads and other decision-makers in management when it comes to the appropriate staffing and thus also payment of their projects with a project manager.

That’s why I exemplary took an original slide from the presentation with the roles and tasks of a CEO at McKinsey and added those of a project manager to compare. Of course, this could be extended as desired. But I think it’s enough to show that the two roles and their responsibilities actually only differ in “altitude” and budget.

Perhaps this is food for thought for the future staffing of your projects: Project Management is not a commodity but a management job. Recruiting does not belong in purchasing, and price should not be the decisive criterion…

What can Artificial Intelligence do in Project Management?

ChatGPT & Co. are on everyone’s lips. Many people are thinking about how to make use of Artificial Intelligence (AI) or how to prevent its use – for fear of no longer being able to distinguish between contributions from humans and AI. There are also already some application proposals for the project management profession.

Options for KI application

Matrix - Project Management, Artificial Intelligence, AI

Artificial Intelligence has the potential to significantly support project managers in various ways, both now and in the future. Here are some key ways AI can enhance project management:

1. Data Analysis and Predictive Analytics:

Artificial Intelligence can analyze vast amounts of project data to identify patterns, trends, and potential risks. This allows project managers to make more informed decisions based on data-driven insights.

Predictive analytics can help anticipate potential issues, delays, or resource constraints, enabling proactive management and risk mitigation.

2. Automated Task Management:

AI-powered tools can automate routine and repetitive tasks, such as scheduling, resource allocation, and progress tracking. This allows project managers to focus on more strategic aspects of project management.

Task automation can improve efficiency and reduce the likelihood of human errors in routine project activities.

3. Natural Language Processing (NLP) for Communication:

AI-driven chatbots or virtual assistants equipped with natural language processing capabilities can enhance communication within project teams. They can answer queries, provide updates, and facilitate better collaboration.

NLP can be used for sentiment analysis to gauge team morale and identify potential issues early.

4. Resource Optimization:

eXcellence - Project Management, Artificial Intelligence, AI

AI algorithms can help optimize resource allocation by considering factors such as team members’ skills, availability, and project requirements. This ensures that resources are used efficiently.

Machine learning models can adapt and learn from past projects to improve future resource allocation decisions.

5. Risk Management:

Artificial Intelligence can analyze historical project data to identify patterns associated with project success or failure, helping project managers assess and manage risks more effectively.

Advanced risk prediction models can provide early warnings about potential project risks, allowing for timely interventions.

6. Project Scheduling and Planning:

AI tools can assist in creating realistic project schedules by taking into account various factors, including resource availability, dependencies, and historical performance data.

Dynamic scheduling tools can adapt to changes in real-time, optimizing project plans as new information becomes available.

7. Decision Support:

MonteCarlo - Project Management, Artificial Intelligence, AI

Artificial Intelligence can provide decision support by analyzing complex project scenarios and suggesting optimal courses of action. This helps project managers make more informed decisions aligned with project goals.

AI-driven decision support systems can consider a wide range of factors and variables that may be challenging for humans to process comprehensively.

8. Continuous Learning and Improvement:

Artificial Intelligence can facilitate continuous learning within project teams by analyzing project outcomes, identifying areas for improvement, and providing insights for future projects.

Machine learning models can evolve and adapt based on the feedback and performance data from various projects.

How and what I use Artificial Intelligence for, and what I don’t

Gladly: Recording and evaluating

For me, it makes sense to use AI to collect and evaluate data. This requires that the data can be digitized and prompted. An example of this is taking minutes and then summarizing conversations, meetings, retrospectives, etc.

The evaluation of quantity data for analyses can also be an area of application for AI. Not for calculating any results from the raw data – spreadsheet programs such as Microsoft Excel are sufficient for that, and knowing which formulas were used to calculate and what the results say. But extracting new insights from these results, such as correlations, anomalies, etc., can be exciting and, above all, faster with the help of AI.

With caution: Reporting

I’m already becoming more cautious when creating reports. Of course, the aforementioned data can be perfectly processed into information and decorated with graphics and other bells and whistles, automated, of course. This would be a good way to simplify the day-to-day work of a project manager or PMO. But this often results in technical nonsense.

So, I still have to check the AI result and if necessary. until I can pass it on to my addressees. Sometimes I am faced with the question of actually saving time and simplifying my work, especially if I can fall back on fixed (reporting) formats, where I only have to enter the current content.

Difficult: Decisions

Button - Project Management, Artificial Intelligence, AI

Where I can’t get used to Artificial Intelligence at all – at least at the moment – are the topics of decision-making and leadership. An AI-supported decision based on deep evaluations and information is fine, but the important things are not decided exclusively on the basis of numbers, data and facts, but with experience, empathy, diplomacy and other skills that a machine cannot have and will not have in the long term.

Finally, for the topics of leadership, motivation, conflict resolution, stakeholder management, etc., good human project management will always be needed. And even many people who call themselves project managers or executives are already overwhelmed.

My conclusion for AI today

In my many years of practice as a project manager and project renovator, I have often experienced that problems arise from an over-belief in processes and regulations, which are the basis for AI. Maybe I don’t (yet) have enough imagination for all the great things that AI can do for me in the future.

But I always think of the saying “Don’t trust any statistics that you haven’t created yourself”. So, if an AI comes to results that I can’t comprehend, I prefer to stick to my last and provide statements that I can take responsibility for.

As AI technologies continue to advance, project managers can leverage these capabilities to enhance their decision-making, improve project outcomes, and streamline various aspects of project management. It’s essential for project managers to stay informed about emerging AI tools and methodologies to harness their full potential.

Read more articles in ProjektMagazin Blog Parade 2024 …

Different Styles – same Objective

Today’s Project Management Lessons Learned originally come from IT, but I’ve found that they can easily be transferred to most other development projects as well: My project teams include a wide variety of people, characters, pragmatists, nerds, team players – all of them great specialists in their respective fields. We all have the same goal, which is to deliver our project as well and quickly as possible. But everyone has a different story about how they got to where they are today, what role models they had and what they drew from them. So, everyone has their own style of doing their job.

A project manager has to deal with this and integrate each individual with his services. And/or consistently demand the things that threaten to fall behind individually. The best example is the high aversion to documentation among developers. Developers want to develop, tinker, create great results. But the paperwork is boring and time-consuming, and besides: “You can see it all from the code or the drawing !” It is strange, then, that even the “producers” without a clear task and development documentation usually find it difficult to define usable test criteria and test cases. And this causes increased effort for the testers and test engineers at the latest – at the expense of the project budget.

Regardless of this, the project manager must always make sure that the project results are comprehensible and representable. So that others who later (perhaps in a completely different project) work on it again and possibly have to change something, can find their way around and go to work without major problems of understanding.

After all, the goal should not only be to ensure that project results work, but also that they can be used in the long term.

Legosteine - Project Management Lessons Learned