Tasks, Tools, Timelines

Strategy

Workflows

Budget planning

My takeaway from five years experience in checking budgets: Without proper templates things get messy. Bugeting a project is not at all rocket science but there are some things one has to take into consideration: First, in academia researchers create the budget theirselves. This is certainly sensible since only they know how many people, consumables, travel expenses, or investments they will need in order to conduct their respective projects successfully. But researchers are very rarely excel wizards nor do they hold a Bachelors degree in financial controlling. Furthermore, they spend far more time and energy on the substantive part of a research proposal and seem to regard the formal requirements attached to proposal writing as rather tedious accessories. Most of the time, the people who check the budget are far more knowledgable about the do's and dont's. In consequence, the budgets the involved administrative units are confronted with differ greatly, are often hard to read, and are rarely comprehensible. Sometimes it takes many emails and a couple of phone calls to make heads or tail of them. And pray their isn't a mistake in the calculation somewhere. Then your are in for paperchase that can take days. Second, a budget must be ckecked not only to meet the requirements set by the funding authority but also to prevent unintended funding committments by the host institution. In collaborative research settings some things one can apply for could be considered as basic equipment or infrastructure of an research institution. So also a project might be funded, some of the requested funding items might has to be provided by the host institution. Third, the tables a funding authorities demands are not always identical to the information required by internal decision-makers of the host institution. The basic data might be the same but how the data is compiled and presented varies. In effect, you are confronted with the problem that you will have to create many "products" during the proposal phase that are all based on the initial budget plan but are very different in appearence and included content. In my work environment next to the tables within the actual proposal, I have counted at least 5 different products based on the budget sheets that need to be prepared before a proposal can be submitted (information for the involved deans, decision papers for the Vice President of Research and Innovation, the Chancellor, the President, a presentation slide for the Vice President of Research and Innovation). If the budget is not detailed enough and only gueared to satisfy the level of abstraction demanded by the funding authority, you reiterate the process of budget preparation 5 more times.  

Here is an example of a simple template I created in the context of the Clusters of Excellence proposal preparation a couple of years ago (the file is in xlsx format so some features do not work. A xlsm version with macros is available upon request). 

Direct download link here 

Selected projects and tasks in the last 5 years

Below you can find a sample of projects I participated in during my time at the Technical University of Municht and the functions and tasks I performed within these projects.

Workflows and Artificial Intelligence

The specific steps in a project may vary depending on the project and the client, but generally, the process can be broken down into simple steps such as preparation, data collection and analysis, solution development, implementation, evaluation, and close-out. AI can augment each of the steps.

1. Preparation: Before the project begins, consultants (e.g. BCG - knwon for strategy consulting, Mckinsey - mainly operations improvement, Bain) will conduct research and analysis to gain a deep understanding of the client's industry, market, and specific problem or opportunity. They will also define the project scope, objectives, and deliverables.

2. Data Collection and Analysis: BCG consultants will collect and analyze data from a variety of sources, such as interviews with industry experts, surveys, and financial reports. AI can automate the process of collecting and analyzing large amounts of data from various sources. This can save time and increase the accuracy of data analysis, which can lead to better identify key trends, challenges, and opportunities which, in turn, will lead to more informed recommendations and solutions.

3. Solution Development: Using the insights gained from the data analysis, BCG consultants will develop a set of recommendations and solutions to address the client's specific problem or opportunity. These solutions are often presented in the form of a detailed report or presentation. AI is helpful to identify patterns and insights in data that may not be immediately apparent to humans. 

4. Implementation: McKinsey has a strong emphasis on implementation. While BCG consultants leave the implementation to the client's team, McKinsey consultant provide extensive support throughout the process, including training, and working closely with the client's teams to ensure the recommendations are implemented effectively. This may include developing an implementation plan, providing training, and supporting the client in making necessary changes to their organization. AI can be used to automate repetitive or time-consuming tasks, such as data entry and report generation, which can free up time for consultants to focus on more complex and strategic tasks. AI-powered systems can also be used to monitor and track the progress of implementation and provide feedback to the client in real-time. 

5. Evaluation: The consultant will evaluate the results of the implementation to ensure the proposed solutions have met the objectives and deliverables, and provide recommendations for further improvements if necessary. AI can be used to continuously monitor and analyze data, providing ongoing feedback and insights to the client, which can help to identify areas for improvement and track progress over time. 

6. Close-Out: The consultant will document the process and results of the project, including all the deliverables, and close the project formally.

The question is: Can AI replace the human skills of critical thinking, creativity, and problem-solving? Will consultants still be important in interpreting and applying the insights generated by AI for the foreseeable future? This is very likely.