In Most companies today are talking about managing humongous amounts of data. Sectors like BFSI, telecom and retail particularly, deal with massive amounts of information that will be used to evaluate and plan business strategy. To be able to make quick and informed decisions, data needs to reside in such a manner that different teams can use it seamlessly across marketing, finance, product development and sales, for example, and not create a situation where each team has to reinvent the wheel. Given this backdrop, industrialisation of data has become a necessity, and CIOs across the board have recognised this and are exploring ways of making it available across the organisation. The CIOs need to find ways to unlock the potential of the data and utilise it more effectively to drive better efficiency.
Give the Freedom, Share Data
CIOs have increasingly realised the importance of decoupling data from applications to deliver greater flexibility, but many of them are discovering that a further step is being demanded of themfreeing data to be easily moved, shared, analysed, or integrated.
The demand is already there, and is growing rapidly as firms realise the value of data. But CIOs need to cater this demand by industrialising the sharing of data. In return, this will help firms extract new value from their data. However, it can be observed that the earlier data sharing activities are ad hoc. Newer data management techniques are required to unlock their potential and to be used for better innovation.
Consider the data currently held within a sales teams CRM system. The same information has value for the marketing team, who could use it to map out customer loyalty trends. A product team may see the possibility of creating a new offering from it. Some financial services firms are already fusing customer, finance and risk data to help spur the development of new products.
Industrialise to Share Data
Most enterprises have started recognising that their data has value beyond its original purpose. More companies are beginning to engage in richer data sharing as analytics increases their appetite for more data and drives them to better utilise existing data.
To put it in simpler terms, by shifting to a model where data sharing is industrialised, any part of the business could tap into whatever data is required, generating more and more value. Right now, however, most data sharing efforts are ad hoc, leaving a patchwork quilt of integration systems.
Data management needs to shift from being an IT capability buried within application support, to becoming a collaborative effort that enables data to be used far beyond the original application it was intended for.
Doing so is now possible because of advances in the technologies used to manage, process, and store data. Web pioneers such as Amazon, Facebook, Yahoo, and Netflix that have solutions for their own data-management challenges, have developed many of these.
Amazon Chief Executive Jeff Bezos has noted that his companys advances in data management have helped provide the necessary architecture to develop its cloud storage and data management services and the flexibility to respond rapidly to new ideas.
IT Heads Need a Change in Thinking
It has always been difficult to provide business users with the data they need to make effective decisions. At every stage, the siloed nature of data tied directly to applications has thwarted ITs efforts to manage data consistently across the organisations. To streamline these newer models of data management, efforts must be duplicated for each silo, driving the cost up and RoI down. A data sharing model, by its nature, will accelerate companies towards the notion of centralised data management. By creating an abstraction layer between data and applications, IT has the opportunity to standardise and industrialise data management.
However, for getting to this kind of transition, the CIOs need to rethink several issues, starting with how data ownership and responsibility is handled and the skills required within the team for sharing the structured and right data.
There are a few key aspects that the CIOs should keep in mind before industrialising data:
Rethinking data ownership: Industrialised data sharing demands new ways of centralising processes and tools for data management. At the same time, the notion of data ownership must become more distributed. This involves upending the traditional world of data management, which views data as a structured asset and a cost centre. Instead, data management in a services-led world requires IT leaders to think how best to enable the business to easily share and reuse any data they have.
Rethinking data responsibilities: It also raises questions about data responsibility. With business units from all over the enterprise creating, consuming, combining, and sharing data, who takes responsibility for it all? CIOs will have to look at working with individual business units to coordinate data responsibility from creation to distribution.
Rethinking data skills: Making this transition demands new skills too, with roles such as data curators, data scientists, and data stewards emerging. At a higher level, CIOs will need to consider whether to institute a chief data officer role.
Rethinking data valuations: From a business perspective, before data is shared it is important for it to be properly valued, and this concept is changing too. Today, CIOs often think about the value of data in terms of what is required to store it. In the future, the value of data will be determined by its use and business impact.
For example, a retailer can use CRM data to improve market share, or an electrical utility can use electrical consumption data to propose usage-based deals for customers. New uses for data mean new values for data. However, what is most valuable is that sharing data generates far more value from it, from enriching product development to strengthening customer loyalty and the ability to respond far faster to data-driven opportunities.
The shared model essentially results in the creation of a data supply chain. It will be up to the CIO to start working with business units to coordinate data responsibility from creation to distribution, more as if they were managing the end-to-end manufacture of a bicycle than a workflow of electronic ones and zeros.
Gavin Michael is Chief Technology Innovation Officer at Accenture.
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