Why a business’ unique data is its most valuable asset

When Caesar’s Entertainment Group went into bankruptcy in 2015, creditors did not evaluate the luxurious business’s unique data (or the multiple properties and land the group owned) as the most valuable asset of the business. It was Caesar’s customer loyalty program which was instead deemed the most valuable asset at $1B USD.

Why business’s unique data like loyalty programs can be so valuable

Many people were surprised.

Like any loyalty program, all it really did was reward customers with points that were often redeemed for a free meal or room upgrade. What the creditors actually saw was the value in the loyalty program’s 45 million users, and more precisely, the enormous amount of data those users generated.

From data such as personal interests to purchase history, Caeser’s used this unique data in targeted marketing campaigns that kept people playing at their tables. They often say the house always wins, and in this case, the use of data generated revenue by locking in a highly engaged customer base.

Furthermore, the scale of the business’s unique data had the most value, by providing insight to the behaviours and predispositions of roughly 15% of the US population in 2015. Like Caesar’s, what many businesses are increasingly finding is that their unique data has become their most important and valuable asset.

Getting the most out of your data

Many businesses, in some form, are now digital, where each business is producing unique data from their customers, transactions, products and even staff. However in our experience, some organisations do not make the most use of their data, be it because of the scale of data being generated, or being hindered by siloed data and the reliability of the data they collect.

Many companies are also in the process of transitioning their decision-making mindset from being heuristics or market driven to being data and insights driven. These factors are affecting the ability of businesses to maximise the value of their data. Our research has found that many are looking to make data an integral component of their business and IT strategy, in order to build the capabilities necessary to be successful in an increasingly data driven world.

Creating a data driven culture

To do this, businesses need to account for some core principles in developing and executing an effective data strategy.

At a recent conference and from the experience of our clients, for all the talk about technology, analytics and artificial intelligence, there are still some core components that consistently come up each time.

  1. You not only need data, but you need to use the right data

Many organisations fail here, either analysing too much data from a multitude of sources, or using unreliable or disorganised data.

  1. Have a data governance framework to ensure data quality and establish trust in data

Have the processes, model and ownership in place to manage data. Much of this requires a shift in culture to value data.

  1. Data must be accessible

Eliminate data silos, share data across the organisation, and centralise access to data through data integration.

  1. Data is well understood

This isn’t necessarily about people understanding what data is, but having a common understanding of what your data means. The simple one we often hear is, ‘what is a customer or a client?’. It is amazing how many definitions of this we find at any one place.

  1. Data must be secure

It is also important to have data security platforms in place to ensure that data is well protected.

Make data part of your business strategy

There are always going to be barriers to change in any business, such as organisational capability and the desire to transform a business’s data practices. There is a need for buy-in from top to bottom across the organisation, with leadership advocating and supporting data driven processes to ensure successful execution of the data strategy. The data strategy must also align with the drivers of the business. Data is important but it has lesser value when it is not analysed with a worthwhile aim. Lastly, there is a need to have competency and the right expertise and talent to enable the adoption of a data strategy by a business.


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