How to Conduct a Geotechnical Data Audit

Geotechnical data is used in a lot of places before, during and after a project, from planning, through the investigation, testing, reporting and analysis phases, to create sections and site plans and ground models in BIM before it is finally archived. Inevitably, this journey starts all over again, when another project in the area comes along.

The golden rules for data entry show the power and benefits of only entering data once. Unfortunately, in reality, this is usually far from the truth – data is often entered as much as ten times throughout the data journey, wasting time (and money).

Carrying out a data audit can help pinpoint any sources of inefficiency along the geotechnical data journey and help to identify simple changes that can be made to deliver maximum benefits. At Keynetix, we have developed five easy steps to take our clients through the process.

Step 1: Who is Handling or Creating Geotechnical Data?

The first step in a data audit is to make a list of everyone (by name or job function) that creates or uses data (this can be a surprisingly long list). For example:

  • Planner – defines borehole locations and drilling requirements
  • Driller – records drilling details
  • Field engineer – records drilling details and logs samples
  • Survey team – creates eastings, northings and levels for sample locations
  • Engineer – creates borehole logs, sections, site plans, laboratory schedules, environmental assessments, design calculations and charts
  • Site technician – records in situ test results
  • Geotechnical laboratory – prints worksheets, enters results, creates reports
  • Environmental laboratory – prints worksheets, enters results, creates reports
  • Monitoring team – makes repeated site visits to record observations
  • CAD technician – creates site plans and sections
  • GIS team – creates maps for reports
  • Quantity surveyor – takes off measures for billing purposes.

Creating this list will help to start to identify where the problems are. More people may be added to the list as the audit progresses.

Step 2: Find Out What is Happening With the Geotechnical Data

The next stage is to speak to everyone on the list to understand:

  1. What data they enter into their systems
  2. How long it takes them
  3. What they do with the data
  4. What software or system they use.

Every time someone enters data they did not create, put an X against them on the list. For example, the laboratory manager will receive sample information via schedules from clients (internal or external) and will then re-enter this data into a sample register book (X), write it on laboratory worksheets (X) and add it to numerous Excel report sheets (X).

For every X, ask: “How much time would it save you each week if we could automate data entry?” Write the answer in hours next to each X.

The interview notes should look something like this:

Geotechnical Laboratory Manager

  1. Sample details received from test schedule (in Excel or PDF format). Data entered into sample register (in-house Access database) X Two hours a week
  2. Excel testing worksheets, with project and sample details, created X One hour a week
  3. Laboratory staff write on worksheets and calculate answers manually
  4. Required values copied to report sheet (Excel) X Two hours a week
  5. Data entered (into gINT) for engineers, once test is approved X Two hours a week
  6. Triaxial tests automated using GTech solution. Required values copied from reports produced into report sheet (Excel) X Two hours a week.

These six stages alone are taking the laboratory manager nine hours every week. By carrying this process out with everyone entering or using data, a picture is quickly built up that will give a pretty good estimate of the scale of the inefficiency problem.

Step 3: Explain the Problem and Solution to Decision Makers

A picture paints a thousand words and swim lane diagrams are perfect for illustrating how data moves around the various people and software within an organisation.


Each lane belongs to a single person or job title. Everything a person does is listed in that lane, in the order items are completed. When data moves between lanes (or even between boxes within the same lane) the method of data transfer should be noted. It is useful to colour code the boxes to illustrate how efficient the current process is: red for inefficient, and green for perfect, data transfer.  The above and below examples show how the before and after swim lane diagrams can help decision makers clearly see how the process will improve.

Step 4: Deliver the Quick Wins First

The review of data transactions should highlight those problems that, if solved, will deliver the biggest time savings. However, while it is natural to focus on these, the biggest problems require the biggest solutions and should therefore not be tackled first.

For example, while logging data digitally on site can reduce the amount of re-typing in the office significantly and deliver exceptional return on investment, large amounts of time and effort are needed to reap the benefits. New hardware and software will be needed and it will take many months to get staff buy-in, to train them and to embed the new approach in company processes.

Instead, the first problems to tackle are those that are much easier, faster and cheaper to solve – these should be highlighted on the list created in Step 2.

For example, automating the production of CAD site plans and sections using a tool like the free Geotechnical Module from Autodesk, or HoleBASE Civil 3D Extension will produce immediate results for the CAD team for very little cost.

Step 5: Take Action – Now!

This is the most important step.

When the problems have been identified and the quick wins have been highlighted it is imperative to take action immediately or the whole process will have been a waste of time.

The biggest problem is that everyone is time poor (and, having identified their inefficiencies, it is probably clear why). But it takes time to make time: if time is not given to tackling problems, no progress will be made.

A good place to start is by setting up a data efficiency project that time can be billed against and get a commitment from the management team to spend a number of hours or days each week on it. The alternative – recording time spent on the project as non-billable – can reduce its importance in the eyes of the management team.

Start small so a return on investment can be seen clearly from the very beginning. If a process takes one day to improve but saves someone an hour a week, that is a 14% return on invested time.

Start Your Journey to Geotechnical Data Efficiency

Understandably, there may be reluctance from some members of staff to admit their inefficiency to colleagues.

Fortunately, help and advice are on hand: Keynetix has worked with several consultants who have carried out geotechnical data efficiency audits and we are happy to share our experience with you via a one-to-one call.   We have a lot more information on how to produce effective swim lane diagrams, together with a number of commonly-observed problems and solutions.


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