20 Feb 2020
Written by Mike Snape, Partner at Oliver Wight EAME
Exploring ‘Big Tech’ capabilities is essential if an organisation aims to overcome the challenges of an increasingly competitive market. The ability to tap into deep consumer insights through advanced analytics, AI and IoT can provide companies with an invaluable perspective on customer demand. This wealth of data contributes to the development of integrated strategies which enhance consumer experience and grant the opportunity to predict future outcomes, and an assessment of internal processes if required.
New technologies offer the potential to add value through the minimisation of costs and maximised profits. Leading global organisations have started to recognise the instant benefits of adopting new technology and have optimised internal processes to offer outstanding service to customers. One of many ways new technologies allow us to analyse consumers’ engagement with products and services is digital retargeting. Such strategies allow companies to drive purchases by engaging with customers who may have abandoned online transactions after placing items in online shopping baskets.
At Oliver Wight, we employ improvement techniques and advise companies on data validation, with an evaluation of the level of accuracy. What we often discover is that the accuracy of their data ranges between five per cent to 15 per cent with significant gaps in information. In some situations, the quality of data renders it unusable. This is referred to as ‘dirty data’. Although some systems providers claim that such data can be cleaned and repurposed effectively using machine-learning, this isn’t always the case. The use of incorrect data can later result in adverse consequences for organisations who choose to implement the use of ‘dirty data’.
Before trends and positive correlations can be identified, appropriate management of data is vital, especially when the intention is to satisfy consumer demand and shape product portfolios. Unless organisations invest time in determining what information they hope to retrieve through these technological developments, analytics will serve little purpose when proposing improved strategies for the future. A major confectionary manufacturer we worked with, steered its marketing activity towards a “buy one get one free” strategy to encourage customers to purchase products more often. This decision was only possible following thorough observation data regarding customer responses to an increase in the frequency of shopping events.
As the number of ‘conscious consumers’ continues to grow, there is an increasing demand for transparency. Consumers have taken on greater social responsibility and now have a desire to understand the manufacturing process of products before they make purchases. Billion-dollar organisations are investing in blockchain to increase the visibility of product production, as it grants customers the ability to trace the origin of the products they purchase. For example, a consumer may be able to trace the origins of their favourite pair of jeans and seek to support the original creator of the design.
Big technology is now an indispensable commodity, which boosts efficiency within many organisations. Obtaining the right data drives and increases potential sales, in line with consumer demand, while the ability to predict forthcoming trends ensures that production lines are always prepared for future outcomes. In Part 2, we’ll take a closer look at the many ways that data can be used to address underlying issues within supply chains.
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