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Through a preliminary study or analysis conducted by Sim Logistics, the customer receives a review and clear summary of the situation in the current business. Many times, data is combined and compiled in a new way for the customer. The results can give the customer better knowledge of their activities, strengthen them in their opinion or give them new approaches.

Sim Logistics gets a better perception and knowledge of the business, which enables us to:

- Identify where improvement potential exists.

- Provide concrete suggestions for long-term and short-term improvement measures.

- If necessary, recommend deeper analyzes in any area.

Below are two examples with detailed descriptions of what can be included in a preliminary study, for those who want to know more.

Example 1:
Analysis of business data
(Internal logistics)


Common to the vast majority of the assignments undertaken by Sim Logistics is that they contain an early part with some form of collection and analysis of logistic business data.


As each customer, business and mission is unique, the generally applicable experience and knowledge we possess needs to be supplemented with mission-specific knowledge regarding the customer's internal logistics. This is done through visits to the customer's business, interviews with responsible personnel as well as collection and analysis of internal logistic business data.


Logistics consultant - Sim Logistics - Forklift aisle with conventional pallet racking at warehouse tour during pre study.
Logistics consultant - Sim Logistics - Counter balanced forklift with extra low mast for unloading and loading of waggons and containers.

Data analysis is rarely performed as a standalone service but is usually included in the needs analysis in e.g. the following types of assignments:

- Dimensioning and design of warehouse and layout.

- Evaluation of warehouse buildings and layouts.

- Efficiency in existing internal logistics.

- Flow simulation through stock and / or production.

- Evaluation of investment in e.g. material handling or automation equipment.

Reasons for data analysis

The reasons for us to acquire better knowledge of the customer's internal logistic data are often several:

- to get the required and detailed insight into the business in order to continue the work towards giving value adding advice and recommendations.

- Verify oral data collected. The customer's opinion may be based on inaccurate data or in the worst case be incorrect.

- obtaining pure facts and statistics e.g. regarding capacity requirements that can be used in the design of solutions.

- through the results, provide the customer with greater knowledge and understanding of his internal logistics to enable the best possible decisions.


Logistics consultant - Sim Logistics - Goods receiving area in warehouse with racks, forklifts and pallets.
Competence of the customer and access to data

The availability of requested basic data can differ greatly between different customer assignments. In some cases, large amounts of data are spread in a large number of Excel files or have to be collected from one or some of the staff. In other cases, input data and compiled data are readily available in an advanced warehouse management system (WMS). Of course Sim Logistics' work effort to obtain the requested data differs a lot in these two examples.

Sometimes the customer has a very good control and has high knowledge about his internal logistics and sometimes less well, perhaps because he has not previously prioritized this area. It is more common for Sim Logistics to work on the latter example as these customers are more often seeking help and it is easier for us to contribute with our experience and expertise. However, we also work with very competent customers, as we can also add value in these cases. For example, through the use of advanced visualization and simulation tools in analyzes, tools that customers rarely have access to and expertise in.

Examples of results from data analysis

What data is it that we want to have and why? This is obviously different between different assignments, but some common examples are:

- Max and average stock level and its variation over time. Used in layout design for selecting the appropriate storage type and layout solution as well as in dimensioning storage capacity.


Logistics consultant - Sim Logistics - Results from pre study and business data analysis are carefully examined.

- Frequency class and goods flow. Sales history is used for frequency analysis and for calculating goods flows. Frequency class combined with stock balance helps us dimension and place zones for goods that are handled differently. The flow of goods is used in selecting the appropriate solution, design of layout and calculation and simulation of appropriate handling capacity.

- Cover time/Time until empty. Based on the average stock balance and sales history, the cover period is analyzed per article. Together with the last and possibly first sales date, items with unnecessarily high balances can be identified. The safety stock and purchase levels for these items can be decreased and some or all of the stock might be scrapped.

- Number of arrivals and departures per unit of time such as lorries or train sets with freight wagons as well as unloading and loading times. Used to dimension, for example, loading docks, number of gates, goods tracks and yard areas. Combined with estimated goods flow, surfaces for un-/ loading can be dimensioned.

- Existing storage capacity. Number of storage spaces per storage and location type.


Logistics consultant - Sim Logistics - Many docks and white truck at a warehouse.
Basic data that may be required

In order to obtain the requested data as above, all or part of the following basic data is required:

- Article register containing, for example:
Item number
Item description
Weight and dimensions (length, width, height) per sales and / or load unit
Number per load carrier
Load type (eg high / low; pallet / half pallet / box etc.)
Item group
Special requirements / features such as dangerous goods, extra heavy, theft-proof etc.)
Status (active, output, resting, etc.)

- Sales history in the form of order lines 1 year back or other suitable period of time:

Item number
Customer number
Customer name
Quantity ordered
Delivery Date


Logistics consultant - Sim Logistics - Collecting, calculating and compiling business data during pre study and analysis.

- Sales forecast. How is sales of articles expected to increase or decrease until the projected scenario year. If required, differentiated by product range or other suitable classification.

- Stock balance history, such as a current balance on the last day of each month, one year back or another appropriate time period.

- Stock turnover rate (STR). If the customer has sales history and STR per article but not the balance history, the average stock level can be calculated instead. STR can also be used to foresee the impact on future storage needs based on changed STR.

- Logged operator assignments. In cases where the customer uses an advanced warehouse management system (WMS) the history of performed missions can be used for analysis and provide a detailed view of internal goods flows and activities in the warehouse.

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