Tag Archives: risc

TCL, Total Cost of Loss, a new business perspective

‘Total cost of Loss’ (TCL) was launched at the World Premiere of the Standard Edition Round Table during the OUGF Harmony 2014 annual user conference.

Doing nothing does not mean it costs nothing

Joel J. Goodman, Finland 2014

“TCL.” Abbreviations.com. STANDS4 LLC, 2014. Web. 15 Jun 2014. <http://www.abbreviations.com/term/1519392>.

Total Cost of Loss is the representation of the cost for an organization when data is lost. Experience learns that this is the hardest exercise in business continuity to figure out and the most neglected threat to an organization.

Next to the two best known terms RTO & RPO and the less well known term RTDA (‘Recover Time to Data Availability’), TCL is aimed at providing the business with an extra ratio to conduct BCP.

To correctly evaluate investments that have to be done to create a sufficient RTO time frame or RPO granularity, there has to be an understanding of the magnitude of the (financial) importance of the underlaying (data)system. TCL is aimed at calculating this figure where this figure is valid per specific data system.

The following components have currently been identified as being part of TCL:

  1. Collection price per granule of data*
  2. Present value per granule of data
  3. Business value per granule of data
  4. Added value in a dataset combination

* a granule of data is the smallest possible set of variables comprising a usable piece of information.

1. Collection price per granule of data:
The amount of effort (time, computing power, etc.) which is required to assemble and record the granule of data in the data-structure.

For example: 1) the time it takes to pick up an item and scan it’s bar-code with a bar-code scanner and put the item back, or 2) the time it takes to enter somebodies name and address at admittance inclusive of possible preparation and filing.

2. Present value per granule of data:
The current amount of effort (if possible) which is required to reassemble and record the granule of data in the datastructure. This entity is taking into account that historical data could be easy to collect at the historic point in time (#1) but would take an unequal effort to collect at present.

For example: 1) establishing if the item was on stock at the given moment, what it’s bar-code would have read at that time and possibly who scanned it at what location, or 2) finding out what person came to be admitted at that specific date and retracing what the date would have been that was entered at that specific moment and possibly by whom.

3. Business value per granule of data:
The value of the single entity of data for the operational business after the moment of measurement. During data lifetime, the value of a specific granule of data can change. Most often it will become less valuable, making it possible to archive or even cumulate** the data in multi teer storage solutions, but, when called upon, it could be this specific granule of data could be of vital importance!

For example: 1) knowing how many of a specific item is in stock, or 2) having identified a specific person within the clientgroup.

4. Added value in a dataset combination:
It can very well be and most probably is, that any granule of data is of key importance to a dataset combination, where several bits of data of different datasets of data-systems combined create information which is vital to any specific action within an organization.

For example: 1) knowing how many of a specific item is in stock to support a JIT-delivery system to keep a production line uninterruptedly going, or 2) delivering the right treatment to any specific person and being able to bill them accordingly.

** Cumulation of data can destroy a recovery path for retrieving any specific granule of data.

Creating a formula to calculate any TCL will be relatively easy.

Creating a model to extract or calculate or even guesstimate the values for the different variables of the formula will be the challenge.
A challenge that needs to be met because of the ever increasing volume of data and the ever increasing importance of certain realms, like healthcare, public services, transportation, etc., within this data mass.

Please step on board and help define TCL as it could prove to be a critical factor when push comes to shove!