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With the radio humming in the background, my attention was caught by three words that do not belong to my mother tongue: inspecto, cognitio, curatio.
Curious, I turned up the volume. The radio host was asking his distinguished guest about advances in medicine, and how new technology influences the role of being a medical doctor.
— Technology extends our possibilities to observe (inspecto) and to treat (curatio). But technology can never replace cognitio.
Our doctor, who turned out to be a renowned psychiatrist, went on to explain cognitio as the holistic evaluation of possible diagnoses and treatments together with their respective prognoses, effects, and side-effects. Active involvement of the patient both in choice and delivery of the health service further increases the chance of success. Finally, closing the loop is often necessary, since no two patients respond identically to any given curatio, and full recovery may require changes in the level and nature of care over time.
I finished my coffee, realizing that I had just learned something important about our own field, strategic planning.
But before we go further into details about solutions and technology, we here at Dynaplan want to wish our customers and partners a good summer time, both on the private and professional level. We already look forward to seeing you all at our next Dynaplan Convention, which will be held in Munich, 14 November. Before that, there will be Practice Group activities, new product releases, and opportunities to work together on new as well as established planning activities for your organisation.
At the end of this newsletter you can read more about the learnings from medicine:
What is the right process and the right use of (new) technologies to create and maintain a successful business in a world of change?
Your Dynaplan team
Save the date for our next Dynaplan Convention on 14 November in Munich, at Stadtwerke München.
Read about gamification to empower your SWP initiative, the launch of the free KMU-Planungsrechner, and a case study from BMW.
Smia 1.5: New data upload/download for shared models, and a new version of the Smia App.
It is a pleasure to announce our next Dynaplan Convention, this year in Munich at Stadtwerke München on 14 November: Mind over chip — Shaping the future workforce for business success.
Together, we will share and discuss the latest developments in the area of strategic workforce management, the interface to competence management, and people analytics. As always, we have reserved enough time for best practice sharing, as well as an early bird session for newcomers in the field.
Please save the date, and thanks a lot to our host, Stadtwerke München. Further details will follow.
On 9 May, twenty planning experts from thirteen companies met in Frankfurt to discuss and further develop the toolset and methodology around strategic workforce planning. The overarching topic was to better understand how strategic change can be grasped for our planning purposes, especially when it goes beyond the scope of existing planning dimensions such as jobfamilies, and into more qualitative aspects such as competencies.
Several best-practice approaches were presented by different customers, and a group work about integration of skill management shed some further light on the respective possibilities. Also, an ongoing master thesis supported by Dynaplan was presented, with the goal of isolating the success factors of a sustainable ongoing planning process. Finally, the new features available with Smia 1.5 were shortly discussed, and further topics collected for the next practice group gathering on 15 November at Stadtwerke München.
After the official event, our host took us on a tour to their impressive Commerzbank tower, and the evening ended well in a traditional Frankfurt restaurant. Big thanks to Commerzbank for making this possible for our community.
As a result of the project Strategic Workforce Planning for small and medium-sized enterprises (SMEs), a basic simulation model has now been made publicly available in Germany. Under the name KMU-Planungsrechner, the model provides a nice step-by-step introduction to SWP, and allows simulations covering up to 250 FTEs.
The project was sponsored by the Ministry of Labour and Social Affairs (Germany) in the context of INQA (Initiative of New Quality of Work).
The launch of the KMU-Planungsrechner, based on Dynaplan Smia, was celebrated on the 2nd innovation conference of TÜV Rheinland on 4 May in Cologne, with a welcome speech by Andrea Nahles, the Federal minister for Labour and Social Affairs.
The KMU-Planungsrechner is provided exclusively for Germany. Dynaplan will soon release an independent SWP solution for the international SME community.
Screenshot from the KMU-Planungsrechner.
Gamification is about introducing game-like elements to activities that are usually not thought of as games. Gamification can reduce the friction and increase the engagement in activities across the SWP process, such as introducing the methodology to project participants, enabling collaborators to use simulations, and creating shared knowledge about the challenges and opportunities collected from simulations.
Gamification has the twofold goal of being fun, as well as serving a professional purpose. We label it serious play, and it involves the following key principles: the game must be highly interactive, focus on a specific, yet critical issue, have clear goals, be calibrated to a balanced level of difficulty, and involve intuitive and attractive toys to play with. At Dynaplan, we believe simulation games are uniquely positioned as the best-in-class toys when it comes to planning.
Together with our customers, we are innovating in the use of games to get the most of their SWP initiatives. As a result, you can expect higher engagement from participants, shared understanding of key messages, and last, but not least: fun.
The BMW Group, together with internal stakeholders and business partners, have developed a Strategic Workforce Planning (SWP) process which since 2012 has been essentially supported by Dynaplan.
HR always supports other business areas in the company. To successfully accomplish this task, it is necessary that HR is directly involved in the strategy process. This is a key success factor. It is only through early involvement that the right people can be placed in the right positions, at the right time.
At BMW, SWP is conducted for the next twelve years, with yearly rolling updates. In the automotive industry, the product cycles are long. For example, spare parts must be provided for many years after production of a vehicle has ceased. The production planning of vehicle models and their derivatives is the basis for the quantitative and qualitative SWP.
Future quantitative as well as qualitative workforce requirements are systematically derived and recorded in a competence catalogue, together with information about the current workforce, enabling quantitative simulation of supply and demand, and analysis of gaps. 90% of the worldwide SWP in BMW Group is conducted this way in Dynaplan Smia. Simulation results are broken down into:
The results of the SWP are reported to relevant stakeholders, and provide an important feedback into the strategy process of the company. The long-term SWP also serves as the basis for short-term adjustments within the yearly budget planning. The quantitative results are crucial information for recruiting activities and education programmes. Click the button below to see the table of contents of the case description, published by Martin Starringer and Christoph Löser.Strategic Workforce Planning at BMW
With shared models, introduced in Smia 1.4, we aimed to improve the way you cooperate and communicate. Our next step is to further assist you in collaborating, by creating a way for you to work in parallel on different areas of the same model.
Previously, when collecting input for a shared model, only one stakeholder could edit the file at a time. When done, the file was uploaded before the next stakeholder could start to fill in data. Alternatively, the person responsible for collating the inputs had to solicit Excel sheets from each stakeholder, and then copy the results in, making sure everything went in the right place, and ultimately having to validate all the data themselves.
Smia 1.5, released in May, contains the new data upload/download feature, with which the person in charge of consolidation can assign areas of the model accessible to each input provider, and they can then each download the model, gaining write-access to only their relevant areas, and upload their data as a compressed, encrypted package. The consolidator can then download these, and Smia will automatically insert them where they belong in the model. This way, all the input providers can work in parallel, while keeping the whole process inside Smia ensures that all data is properly validated, as well as inserted in the right place.
To read more about Smia 1.5, please visit the release blog. Note: When saving files, Smia 1.5 does not include enough information to be able to restore scenarios. Fortunately, we were able to quickly publish service release 1.5.1 which automatically solves the problem.
While working on Smia 1.5 for desktop, we’ve put any relevant improvements into a new version of the Smia App. In addition, we have been focusing on two major areas of improvement. Firstly, the speed and smoothness of panning and zooming on the diagrams. Secondly, immediate, visual feedback for the user when large models unavoidably causes noticeable recalculation times after toggling a checkmark, adjusting a slider, and so on. The control now reflects the change immediately, and an activity indicator by the simulation bar shows you that Smia is processing your input.
Maybe you too have experienced the excitement of being able to transfer knowledge from one field into an entirely different field? In the introduction, we created a causal loop diagram based on the story told by an experienced psychiatrist. It only takes some renaming to turn the doctor’s diagram into a structure that is highly relevant for individuals and organisations who strive towards a successful future.
No business is better than its operation — curatio — which is where products and services are designed, produced, and delivered. Operation is undergoing fundamental changes, gradually moving from labour towards technology and automation. Access to more data, greater computing power, and better software has added more layers to the analytics maturity pyramid, such as machine learning and predictive analytics, which are closely related.
Machine learning is accelerating the automation process, as well as bringing it into new areas; areas that have until now been served by people. Predictive analytics does not – and can never – change the fact that the future remains volatile, uncertain, and ambiguous.
In fact, predictive analytics rarely addresses predictions about the future. How can we then call it predictive?
The answer is that through a large and rapidly growing set of data about individuals, and the access to mind-blowing computing power, statistics is taken to a level where the likely behaviour, preferences, etc. of individuals can be predicted from information that is available about the individual itself, as well as large numbers of others who share some common traits. Thus, predictive analytics can be used to make operational processes more targeted, for example in marketing and recruiting.
Now, let us have a look at the third necessary element for continuously shaping and re-shaping our business to fulfil its purpose in an environment of on-going internal and external change. It is our thinking, problem solving, strategizing, and planning activities — our cognitio — that is responsible for taking actions today that will contribute to shaping our short, medium, and long-term future.
We know from our statistics classes that data-centred analyses give reliable forecasts only if the future is driven by the same forces as in the past. In times of structural change, however, the rules of the game are changing. This can lead to a significantly different future than the one we are able to read out of any data-centred analysis, no matter how advanced.
In light of this rather disturbing fact, one might ask:
— Is it at all possible to support the forward-looking nature of strategy and planning with technology?
The answer is to use model-centred technology, where the core is the cause-and-effect relationships that day by day create the changes we define as “history” when looking back. Model-centred technology is driven by understanding, rather than dated facts. While data-centred technology resembles sensory organs (vision and hearing), model-centred technology resembles thinking. Into models we can enter the new rules of the game, and in return receive as output future consequences at high speed.
Just like in the case with the doctor and his patients, success depends on a tight coupling of observation, strategy, and operation. A potential pitfall is to go blind by the peak in the machine learning “Hype Circle” (Gartner 2016), and treat analytics as an objective in itself, instead of seeing it as a resource for strategy and operation.
Another piece of advice is to limit the use of rigid, backward-looking, black-box technologies (e.g., ERP, statistics, and spreadsheets) when shaping the future. Planners must be prepared for rapid changes. More than ever, agile planning, agile planning tools – and agile planners – are called for.
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