Data & Analytics

Data is growing – every 2 days we create as much information as we did from the beginning of time until 2003.  Over 90% of all the data in the world was created in the past 2 years.

As technology progresses, the format in which data comes in is also evolving; every minute we send 204 million emails, generate 1.8 million Facebook likes and send 278 thousand Tweets.

Data should be a business priority and if used in the correct manner, unlocks the potential for enormous opportunities for business improvement.

What is the benefit of data without analysis?

In short, there is no benefit – this is where SpringTide step in.

A business can have masses of data, but it is useless without meaningful analysis to tell a story.

Through analysis, a business can reap many benefits –

Benefits of Data Analysis
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So what do we do?

The four basics of analytics are to Collect, Clean, Sort and Store.

  • Collect – data comes to us in varying formats, whether it be a scan of a delivery note, a PDF document, manually keyed information or a data dump from a database. We have even received photocopies of a transport planner’s diary before now! Different sources of data give different levels of information; a sales invoice gives us information that varies to a delivery note for example.  This stage is important as we need to ensure from the outset that we have the most appropriate data source.
  • Clean – as data comes to us in a raw format, it is an analyst’s duty to transform it into a usable document. This can involve tedious tasks such as ensuring all cells are formatted in the same way. At a glance you may not think there is much difference in a post code being written as WS12 2DA, WS122DA or Ws12 2DA, but an analyst will, as not amending this during the cleaning stage could result in 3 differing locations being shown at a later stage in the analysis.
  • Sort – This leads on from cleaning; an analyst needs to extract from within their raw data what they deem to be key information and what is superfluous. A recent data set arrived to us with 339 columns, when in actual fact only 8 needed to be used. This initial cleaning and sorting exercise can take some time to complete, but these are extremely invaluable steps to take in order to ensure the data is consistent and therefore makes the analysis more meaningful.
  • Store – As many of our Clients are not on site it is imperative that we store their final analysis in a manner in which they have access to it. This can involve using cloud based technology. In terms of storing, version control is also very important, as the smallest amendment or previously undiscovered fact can have a huge impact on a piece of analysis.

SpringTide then present the data back to the client in the form of a data dashboard.  This is done to validate our understanding and assumptions of their data, ensuring measures such as their customer profile, weekly/monthly volumes and seasonal trends are reflected accurately.  We’ll also talk to the people in the know – the transport planners and site managers – to find out exactly how the site operates and all those individual requirements that are crucial to how the business runs on a daily basis.

Data Set for Validation

A Director of HR analytics for an entertainment company sums it up; “Basically, analytics is about making good business decisions.  Just giving reports with numbers doesn’t help. We must provide information in a way that best suits our decision-makers.”

Whereas data analytics is about what we are physically looking at within the data, so for example, volumes, delivery destinations and load sizes, modelling is the next step. Modelling is important in bringing all these individual elements together and enables us to start optimizing.  Why not take a look here at how SpringTide do this?

To talk to us about analytical solutions resulting in cost reduction for your business, call us on +44 (0) 7973 445297 or you can fill in this form to discuss how we can help you.