Why Do Data Initiatives Fail?

Alex Coleman
Data Strategy

Gartner reported in 2017 that 85% of data initiatives failed, but with 99% of respondents in Big Data organisations investing in data analytics, Big Data and AI, and 96% receiving measurable value from these initiatives, why are so many data initiatives failing?

NewVantage Partners reported that only a quarter of organisations have successfully made a shift towards a data-driven culture, leaving the remaining three quarters to suffer from the symptoms of low data maturity.

Low data maturity is often associated with a lack of trust in and a limited use of data: this toxic mix inevitably leads to a competitive disadvantage.

In contrast, high levels of data maturity come hand-in-hand with informed decision making, trust and transparency, and ultimately, long-term success.

However, climbing the data maturity curve is no longer about leading the pack, but rather, surviving in an increasingly data-driven world. But for organisations to become data mature, they must have an effective data strategy that is integrated within the culture.

Put simply, data strategy is the approach that an organisation takes to manage and use its data to create a sustainable competitive advantage and support its goals. A good data strategy, therefore, leverages an organisation’s digital assets and ensures data initiatives are focused.

Only with an effective data strategy, can an organisation climb the data maturity ladder and reap the rewards of digital transformation. And yet, despite unanimously agreeing that data strategies are a top priority, only 30% of CDOs have data strategies in-place at their organisation.

Here, may lie the answer for avoiding low data maturity and the disturbingly high rate of failing data initiatives.

Below, we look at two organisations who have utilised or are using two different data strategies to increase their data maturity. They too, like many others, realised that with data maturity, comes great rewards.

Carnival Corporation: data analysis with the end-goal in mind

Back in 2015, Carnival Corporation, which includes some of the world’s most widely recognised cruise brands such as Princess Cruises, P&O and Carnival Cruise Line to name a few, had a simple goal: how do we get each of our customers to spend an additional $1 aboard?

They identified that they had control over the passenger’s experience from the moment they boarded and disembarked a ship, and designed an operation-focused strategy to refine links in the chain. Considering Carnival Corp.’s 100-strong ship fleet supported 80 million passengers, seemingly small tweaks can quickly total large revenues.

With the end-goal in mind, Carnival Corp. began to delve into the wealth of passenger data at its fingertips and invested in analytics to manage its data, but also identify and prioritise areas for price optimisation.

For example, they changed the number of reserved beds in different cities during voyages on a daily basis based on geographic demand. In 2015, these ideas were largely pipe dreams and their strategy would not be considered a success until much later on.

Just a year later, Carnival Corp.’s revenue totalled $16.4 billion, placing it in the top 200 of the Fortune 500 list and number 311 on the Forbes Global 2000 list of the world’s largest, most powerful companies.

In 2018, Carnival Corp. is still reaping the rewards of strategy with data at its heart and an increased data maturity; Carnival Corp. now supports 12.1 million passengers, on 103 ships and is the only group in the world to be included in both the S&P 500 and FTSE 100 and achieved almost $2 billion additional annual revenue compared to 2015.

Now Carnival Corp. has begun its digital transformation, newer, focused strategies can be put in place to further leverage their digital assets, make informed decisions and achieve greater returns.

Walmart: increasing trust and transparency to stay at the top

Walmart has had a long-term, successful history of good strategies to remain as the largest retailer in the world. The majority of these strategies have concentrated on developing a highly structured and advanced supply chain management system to offer everyday low prices.

For example: reducing the number of links in the supply chain, identifying stock oversights and increasing strategic vendor partnerships. However, with Amazon’s purchase of Whole Foods, Walmart is looking to stay one step ahead by improving its data fitness, and produce personalised experiences for its customers.

Doug McMillon, the President and CEO of Walmart, recently told attendees at its investor conference “We use data to improve in-stock and replenish. We don’t use data to personalise.” but that could all be about to change.

Walmart’s One Version of Truth, a programme to provide supply chain partners with a consistent view of the market to measure performance and generate mutual growth across Walmart while building trust and loyalty, was announced at the end of 2017.

Data trust and loyalty across the organisation is a key component of data maturity and clearly, Walmart is looking to sustain a competitive advantage. Walmart is looking to not just manage its data, but also make informed decisions.

The end-goal, as with any good strategy, is at the forefront of Walmart’s mind and is informed by data analysis. Crucially, this vision isn’t for the weeks and months ahead but instead, the decade.

Walmart’s CEO acknowledged that it would take years to organise Walmart’s data before it can be used for personalisation. Yet Walmart clearly understands that to succeed and stay ahead of its peers, then they too, must climb the data maturity ladder.

One part of Walmart’s strategy to achieve data maturity is to build the world’s largest cloud-based database. However, to manage and effectively use the information from 20,000 separate stores and 28 countries, these data need to be brought under one roof. By doing so, Walmart hopes to make very fast decisions and devise effective strategies leveraged on real-time data.

Considering that 90% of the data available today has been created in the last two years, data maturity has never been more important. Clearly then, to achieve high levels of data maturity, effective data strategies must be implemented.

These strategies must be designed with the end-goal in mind, leverage an organisation’s data assets and become adopted by the culture to sustain a competitive advantage. If not, your next data initiative may join the 85% that fail.

At Anmut, we help organisations understand the value of data and its strategic significance. Contact us, if you are interested in learning more about what we do.