Perspectives

Generating value from data capture

In an ever-expanding landscape of new and untapped data sources, a practical question for business is how can we unlock the value of information to gain competitive advantage? Analytics provides the answer.

What is analytics?
Analytics is the practice of using data to enhance business performance, actively incorporating fact-based insights into business processes and making more effective decisions.

Analytics techniques are used across all industries to extract greater value from existing data, generating new perspectives, or using predictive techniques to plan for the future. Visualising data in new ways can provide valuable insights, but critically, these must be incorporated back into business practices in order to convert insight into value.

The key trends outlined below are driving the adoption of new approaches to business analytics:

  • Data Volumes & Technology Capacity – Global data volumes continue to grow exponentially. Luckily today’s analytical computing capacity and analytical tools can meet the challenge. Developments such as cloud computing and open source data analysis tools reduce the cost to both store and analyse data.
  • Profitable Growth - The need to remain competitive compels investments in analytics infrastructure and tools to improve insight into financial, economic, environmental and market information. The goal? More informed and responsive decisions.
  • New Signals - The wide range of data sources available from social networks manufacturing facilities that are sensor enabled and even till receipts can be analysed to provide insight for more effective decision-making.
  • Hidden Insight - The growing complexity of business has raised the stakes at all levels of decision-making. Facing more information than humans can possibly process, decision makers need more powerful tools to uncover hidden patterns that may go undetected and identify opportunities for business growth.

Deloitte is helping clients solve complex business challenges through the application of Analytics in a range of areas:

Customers and growth
Generate and protect revenues through deep understanding of the customer, product and channel to:

  • Identify your most valuable customer relationships
  • Optimise demand for products/services
  • Deliver profitable growth across multiple channels

Workforce optimisation
Improve performance, retention and workforce productivity by:

  • Optimising shift patterns
  • Resource demand planning
  • Identifying and analysing indicators of high performers

Operations and supply chain
Optimise operational processes and resources through analysis of activities, risks, costs, tax and value-add by:

  • Identifying where costs can be reduced in the supply chain
  • Determining how logistics can be organised more effectively
  • Detecting which process inefficiencies have the most impact

Risk and regulation
Identify and proactively manage financial, operational, regulatory and security risk:

  • Quantify how much you are losing to fraud
  • Determine your exposure to market and credit risk
  • Ensure compliance with financial sanctions

Finance
Forecast, plan and monitor financial budgets & transactions by analysing & predicting:

  • Financial performance next year
  • Overall performance across divisions
  • Financial impact of structural changes
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Application to SMEs

While SMEs typically gather less data than large global organisations, there are significant benefits to be gained from developing an analytics strategy that can mature with an organisation’s data management and analysis experience. Having developed an understanding of how and where analytics can help an organisation meet their strategic goals, an essential next step is ensuring that processes are in place to manage the quality of the data being gathered.  In order to enable any form of insight to be derived from data, organisations need to make sure that it is of a high quality. Where issues are found the business and IT need to work together to address them through process and system change.

Visual exploration of data through software that makes complex data accessible and understandable is a critical capability for organizations of virtually every shape and size. For example, location based public data sets can be used to visualise and interrogate relationships between geographical areas for use in areas such as micro-market analysis, fraud detection and customer analytics.  Tracking sentiment over time through social media feeds, such as Twitter, on specific topics can provide a real-time view on changing sentiment, and trigger analysis on the root cause of this change. Conversely the impact of marketing actions can be tracked for overall effectiveness.

Further along the maturity curve, an organization may employ advanced analytic techniques, using historical client information to predict future behavior such as the likelihood of customers lapsing for example. Coupling this with estimated customer lifetime value allows for concentrated and effective retention efforts to be deployed.

Analytics provides opportunities for significant competitive advantage to be gained in a wide range of areas. As business confidence grows, investment in analytics in the SME sector is set to be a key differentiator.

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