Marketers have, for many years, sought to better target and increase the relevance of their products, services and communications. Differentiation through service in an increasingly commoditised world underpins many customer centric strategies. Insight from customer data is the fuel driving the marketing engine to deliver personalised relevance and service differentiation.
The explosion in the volume of data organisations are capturing about their customers, intermediaries, suppliers, employees and operations, directly and via the millions of sensors embedded in the physical world, can generate tremendous insight. In their 2011 study (Big data: The next frontier for innovation, competition and productivity), the McKinsey Global Institute identified potential benefits across many sectors; from billions of dollars per annum benefits for health care and public sector administrations and increases of up to 60% in operating margins for retailers. The report suggests that, “Forward-thinking leaders can begin to aggressively build their organisations’ big data capabilities.” It goes on to state that if they fail to do so, their competitors will leave them behind.
The opportunity sounds compelling and increasing an organisation’s ability to utilise this data undoubtedly will increase their ability to win, keep and develop customers and better manage costs. However, years of advising organisations across most sectors on how to increase profitability through improved customer management suggests achieving this will not be easy. Conclusions drawn from assessing customer management capabilities in hundreds of organisations are that few have even nearly optimised the value they can create from the customer data they already have, let alone the enterprise wide, and wider, data that McKinsey talk about.
Activities to win more and better customers, keep them longer, develop and manage their value and manage the costs of sale, service and failure all rely on an enabling business system of customer management. Balanced capability improvement across the entire model is more likely to lead to sustainable business performance. Disproportionate focus in any one area creates a risk to return on investment, as other parts of the business system are unable to utilise the enhanced capability fully. More often than not, the introduction of new technology outpaces the ability of the organisation to use it. This is the risk if pursuing the ability to use big data is technology led.
We would suggest that organisations first look at the entire customer management model and understand all the gaps in their abilities to use customer data today and aggressively address them first. What might those gaps be?
-
Do leaders understand and measure customer value and do they appreciate the value of customer data as a strategic asset?
-
Is the environment one in which data driven decisions can flourish?
-
McKinsey’s study identified skills gaps in both deep analytical talent (140-190,000 more individuals needed) and in managers who can understand big data outputs and make decisions based on them (1.5m shortage in the US alone). Does the organisation have the skills to capitalise on data?
-
Even if this talent gap is closed, organisations still need a customer culture. Is the business organised around the customer, colleagues motivated and the sharing and use of customer insight encouraged?
-
The need for a robust customer information plan increases in line with volume of data available. The cost of continuing to capture and store everything possible is increasing. The confusion caused by extraneous data will increase. Has the organisation clearly defined the information wanted, for what purpose, where it will come from, how it adds value and how to manage it?
-
Managing customer concerns over the personal data organisations are storing increases in importance. Are the policies and practices in place not just to comply with privacy legislation and regulation, but also to maintain customer trust?
-
Data only adds value if it can be used. Delivery in a timely and usable format to users is essential. Has the organisation understood and overcome the difficulties integrating existing systems to provide a single customer view before considering adding additional sources?
-
Is the organisation collecting all the important customer data and do colleagues understand the importance of accuracy, frequency and completeness of data they collect?
-
Do measures (of functions, colleagues and activities) encourage customer centric behaviours, the capture and care of data as an asset and the application of customer insight?
In summary, we would suggest that significant competitive advantage is achievable through better use of customer data, but that initially this does not have to include big data. Organisations should first focus first on closing the capability gaps to better use the customer data they already have. Future planning is obviously prudent, but let the demand drive the technical investment.
[1] Big data is a term applied to data sets whose size is beyond the ability of commonly used databases and software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.
