Smia provides the modeller with powerful mechanisms for dealing with complexity. A business simulator of any size and complexity can have a simple and intuitive surface level capturing the big picture. Using drill-down into structures as well as data, the modelling experts and their colleagues inspecting or using a model can just drill down to unveil more details.
In addition to the structural complexity of the reality, its dynamic complexity must also be considered. Our actions and interventions, intended to create desired effects, take place in an environment of actors with are also active. Therefore, actions are met with reactions. Our activities do not only have effects, they also have side effects. Smia’s built-in support for feedback solves the problem of circular definitions when trying to express dynamics in many other tools, giving the modelling expert a way to create valid representations of the reality, producing realistic forecasts for much longer time horizons than we are used to seeing.
In certain areas, our understanding or knowledge of our reality may be uncertain, or it might be subject to unpredictable forces out of our control. Still, as long as we are able to estimate this uncertainty, we can still construct a model that can calculate possible outcomes and their probabilities. As more stochastic variables are discovered and added, however, this can quickly grow complex. Smia has functions for working with statistical distribution, statistical samples, regression, statistical tests, confidence and correlation. Using stochastic functions such as Monte Carlo simulation, uncertainty distributions can be assigned to variables in a model. Uncertainty will propagate automatically through the dependency chains, and the combined result can be depicted in customisable charts and tables, and displayed for example using percentile bands.
Over time, organisations accumulate historical information that can be essential to developing an accurate model of their world. Real-time data flows from multiple sources and may be stored at varying levels of aggregation across several systems. Metadata can change as the organisation develops. Plugging all of this into a decision model, and keeping it up to date, can be challenging. Smia’s database connectivity solution is SAP certified, and allows the modeller to easily set up connections using drag and drop. For the planner, one click suffices to get the model up to date.
Smia gives a clear picture of the drivers involved in shaping the future development the system you are studying, whether it is the dynamics of your workforce the effects of your business strategy.
The world being uncertain implies that decision-makers ought to take different scenarios into account. With Smia you can explore the likely consequences over the short, medium and long term, depending on which scenario you are studying. The scenario process lets you experience possible futures, and be better prepared to select the best and most robust road forward.
Planning takes place over a given interval, and after that, a new plan must be made. With Smia, rolling your forecast over to the next period is made as easy as possible. Select your new time horizon, and Smia updates all your metadata, including your scenarios. The newly created input areas are ready to be filled in.
When many people must share access to the same tool, challenges appear. A modeller might need to update the model’s structure. An information provider wants to input his data. The planner needs to consolidate and create scenarios, and the decision maker waits for the results. Which version of the model is the latest one? Who is working on it right now? With Smia’s new shared model concept, distributing models to stakeholders and ensuring that they can perform their designated functions has never been easier. Updating and retrieving models takes place entirely within the application itself, and keeps everyone up to date and accessing only what they need to access.
Smia supports the planning process all the way to the boardroom
You may think that modelling and simulation belongs to the toolbox of the experts. This used to be the case, but with Dynaplan Smia, the power of simulation is made available to everybody involved in planning and decision-making.
Whether you are planning your summer vacation, or you are determining the future of your company, the questions asked in a well-formed decision process are always the same:
- Where are we?
- Where can we go?
- Where will we go?
The challenges in answering the questions vary greatly depending on the complexity of the matter you are trying to decide upon. In a business context, it can be hard to establish a valid picture of the current situation (where we are), identify and evaluate alternative routes forward (where we can go), and foresee the real consequences as well as the requirements for success of our choices (where we go).
All too often, complex decisions are based on assumptions that are too simple:
- Where are we?Answer: We are where the previous budget period put us.
- Where can we go?Answer: We can continue with a growth rate below, at, or above the average in our industry, which we believe will be 3%.
- Where will we go?Answer: Let us grow 2% more than competition. Please increase all figures from the previous planning period by 5%, and we have our new budget.
Of course, few serious businesses plan exactly as described above. Still, when planners increase their spreadsheet figures by certain grow factors, isn’t that actually an example of the process described above?
Dynaplan Smia is about creating a better understanding the current state of your business, about identifying risks, challenges and opportunities laying ahead, and about quantifying the requirements to be met in order to implement the targets you set.
On the individual level, or in a small organisation, one individual or a small group of individuals can perform the entire decision-making process. In larger organisations, the planning steps are distributed to different parts of the organisation.
Scenario planning roles
…transform information about the problem domain into a dynamic simulation model.
…feed the model with the latest information and prepares the next planning cycle.
…experiment with what-if scenarios to identify the best options for going forward.
The information needed for strategic workforce planning processes is often distributed among several stakeholders. That is, not all information is available to central planners in the desired quality. Regional planners usually have better knowledge about demand and supply drivers regarding their specific region. However, collecting and consolidating this information is a time-consuming and error-prone process.Read the article
Decision makers using Smia
Using Dynaplan Smia, management can link its strategy to action, analyse different future scenarios, and respond fast and adequately to changes in the business environment.
Benefits of Smia at the management level
When planning figures are driven by a Smia model, management is not limited to studying prepared figures; managers can also test out the effects of new decisions and ideas coming up during a management meeting, a board meeting, or when investigating planning models on their own.
Using Smia, it is just a matter of seconds between modifying inputs, simulating the consequences throughout the value driver tree, and being able to compare the result up against other scenarios.
Planning models in Smia display not only forecasts, but also information about assumptions behind the results. It is straight-forward to drill down into data as well as the logic of the drivers behind each scenario.
Smia diagrams are “boardroom ready” in the sense that they make use of familiar and intuitive, hyper-linked diagrams showing flexible charts and tables for entering inputs and viewing results.
With live connection to the organisation’s business warehouse, planning models will always be equipped with the latest available information.
Adapting plans from one planning period to the next is straight forward, reducing time and effort involved in the planning process.
This gives excellent support for rolling forecast processes and different degrees of “beyond budgeting”.
Therefore, it should be no surprise that leading corporations have introduced Dynaplan Smia at the level of top management. Instead of engaging the organisation to spend days, weeks or months to produce revised figures incorporating new information and changed assumptions, it is now possible for management itself to make the updates live during their meetings.
Whether you use traditional planning or leaner planning approaches, simulation not only gives a more comprehensive foundation for making decisions, it also makes it much faster and easier than before to keep forecasts updated from month to month, quarter to quarter, year to year.
In a global economy where assumptions constantly change, traditional plans suffer from being too difficult and time-consuming to adapt quickly and adequately to new information, changes in markets, changes in technology, currency fluctuations, raw material costs, etc.
We all know that the future cannot be predicted. When something unexpected takes place, this is when the business simulation approach shows one of its main strengths: The ability to quickly incorporate the new information, create revised scenarios, and being a solid foundation for management to identify and validate the best ways to deal with the new situation. Without this tool, managers run a greater risk of overreacting in response to new information or sudden events, and to overemphasize the importance of recent events; or as Kahneman (2011) puts it: WYSIATI (“What you see is all there is”), the built-in tendency of the human mind to neglect the unknown and focus exclusively on what’s in front of you, assuming that represents the full picture. Through simulation, it is simply much easier to see individual facts in their full context, and to derive which levers to move, and how much.
Kahneman, D. (2011). Thinking, fast and slow.
Planners using Smia
Planners play two central roles in an organisation:
- Prepare material for management and the board as a basis for making decisions, and
- Initiate the process of implementing management decisions in the organisation.
Smia business simulation models can improve both the efficiency and effectiveness of the preparation and implementation of plans.
In the preparation phase, it is the task of the planners to keep the planning model and parameters aligned with strategic priorities, feed the model with the most current information, and prepare requested scenarios to the management and the board as a basis decision-making.
In the implementation phase, the quantitative output from the scenario decided on by management is used to set targets for the detailed planning and implementation.
Benefits of Smia to planners
Smia provides an easy and intuitive interface for creating and analysing scenarios.
The forecasts created for each scenario are driven by an advanced simulation engine, which crunches through countless cause-and-effect relationships that have been built into the organisation’s planning model.
Smia provides features for incorporating historical data, statistical analyses, uncertainty (Monte Carlo), currency risk, and optimisation.
Smia has unique features for building quality into planning models. All figures are associated with measurement units. Smia automatically performs unit checks on all equations and whenever transferring data to or from external systems, such as SAP.
Smia has unequalled support for formal review, helping organisations ensure the validity and correctness of the cause-and-effect chains constituting the planning models.
Smia is designed to support the planning workflow.
Once a live connection to SAP/BW is set up, it takes just one button click to bring data and metadata up to date.
The transition from one planning period to the next is supported by Smia’s unique rolling forecast feature.
Planning models in Smia are “boardroom ready”, and can be used directly to present living slides to management and other parts of the organisation. Effort that would otherwise be used to produce static slides can now be spent on more analysis.
Modellers using Smia
To understand the rationales behind the core concepts and features of Smia, it is helpful to know the purpose of the software and the settings where it is used.
In a planning and decision-making process, the simulation model acts as a container for the collective knowledge an organisation has about itself and its environment, and how they interact.
To be effective, model building blocks need to be decoupled from particular fields and disciplines, using mainly concepts from our common knowledge base and concepts that are intuitive and easy to learn. To achieve this, Smia uses a simple graphical representation of models, quite similar to the slides of a PowerPoint presentation, only that the boxes and arrows of the slides represent variables and relationships, and not just static drawings. Equations used to specify cause-and-effect relationships in a model uses a syntax similar to entry-level math, which is much easier to read than spreadsheet formulas.
Benefits of Smia to modellers
The Smia modelling language provides powerful, yet intuitive structuring mechanisms that help modellers create and maintain models of any size. Hierarchies, data arrays, re-usable model components (object orientation), libraries and templates are examples of features that make Smia truly state-of-the art.
The modeller has access to optimized visualisations of structure, influence, and data. Different visualisations can be freely combined to create clear and intuitive views of models at different levels of abstraction.
The unique contents colouring feature makes it fast and easy to identify variables representing different domains, such as labour, resources, and finance.
Smia automatically ensures a consistent mapping between model visualisation and the underlying model equations.
Smia’s modelling language is strongly typed. Smia uses this to perform a number of automatic validation checks, and to ensure correct visualisation and formatting of values.
Smia automatically tracks the review status of every equation in a model, when it was reviewed, and by whom.
Smia is put together based on the needs discovered during 30 years of experience with modelling in a business environment.
The system has features ranging from simple mathematical expressions involving plus, minus, multiply and divide to advanced analyses combining non-linear feedback, stochastic functions and optimisation.
We are very proud to have developed a sustainable customer base over the past years. Have a look at our customers’ testimonials, and get an impression what we have achieved together in the diverse areas of modelling and simulation we and our clients work in.Our testimonials