Organisations seeking to drive decisions with data first need a data and analytics (D&A) strategy and operating model able to conceive data-driven business opportunities.

Those opportunities include identifying and prioritising decisions to improve through applying decision intelligence practices, such as decision modelling, and using technologies like data fabric, analytics, and artificial intelligence (AI). But to optimise decision-making processes and the D&A ecosystem that enables them, you’ll need to establish a clear connection between D&A and business value creation.

You can’t succeed if you treat D&A as supportive and secondary to business initiatives.

Gartner predicts that by 2024, not only will organisations have placed data and analytics at the centre of their business but 75% of organisations will have established a data & analytics centre of excellence to support federated data & analytics initiatives to prevent enterprise failure.

Prioritising D&A initiatives around business value can be challenging in practice. An effective data-driven enterprise has a vision that relates D&A to the organisation’s business purpose, preferably expressed in terms of customer value.
This vision serves as a focal point for the development of an effective data-driven enterprise strategy that once realised will confer competitive advantage through lower costs, quicker time to market, increased revenue, improved customer satisfaction, and greater differentiation. A recent survey found that 43% of companies that have grown during the pandemic have had a full-fledged data strategy.

Let me unpack each of these facts below.

1. Availability of Data for Utility

Data and analytics should be instantly available to all, for all purposes. A single source of truth is crucial, with no duplication of effort and no confusion over which source is correct. The measure in which it will be available can correlate to the following questions:

• What is the availability of the platform?
• Is it quick and easy to access the available data, for a variety of purposes?
• How long does it take to add a new data source or data access API?

All these measures will help you identify if your data is available for effective use.

2. Data as an Enabler

Data should be used for decision making to improve customer experience, increase sales or improve operations. This can mean anything from predicting what customers are likely to buy next or how long it will take them to complete a purchase through personalising marketing messages based on previous purchases or online behaviour. Even identifying where production wastage is and where business processes could be improved.
The measure that points to data as an effective enabler relate to business KPIs, such as:

• How much did the conversion rate improve after implementing a new campaign management analytics tool?
• How much money are we saving because of Internet of Things (IoT) data and analytics?
• How much money are we saving because of improved fraud detection algorithms?

3. Data as a Business Driver

Data helps us identify opportunities where others do not see them because they are not looking at all the right places or asking questions with enough depth or frequency. This is especially important in today’s dynamic environment where competitors can change quickly based on their own experimentation with new business models or products/services offerings etc., so we must react quickly as well if we want to stay ahead of them!
In order to ensure your business is successfully measuring how well data is used as a driver(innovator), you need to answer the following questions:

• What is the split between discovery exercises that lead to new insights, that lead to optimisation insights and that lead to transformative insights?
• How much new revenue (through new D&A-enabled products and services) is being generated by D&A initiatives?
• How many discovery exercises for a specific business function are follow-up or repeat activities, instead of one-off exercises?

We advise that you use insights from your model to refine your data and analytics strategy and operating model with specific priorities and dependencies to address the identified gaps. This will increase the likelihood of successfully delivering the intended business value, for example initiatives designed to reengineer business decisions.

The main aim of this successful D&A strategy is to optimise the combination of D&A initiatives to ensure the portfolio delivers the highest net business value spent for your strategic business focus and for a given investment level. Something we can certainly help you realise as we have done for my clients in the past.

For more information about our Data and Analytics products:

Decision Inc. Pursuit of Progress

Decision Inc. helps organisations develop and deliver the Technology and Digital Operating Model to support their strategy. We create the capability for clients to innovate and compete by connecting the technologies, platforms and data they need to thrive in the Modern Era.

Decision Inc. brings a deep business and technology understanding and provides functional insights, embedded in the technology platforms of the industry, to help clients make an impact. We help the best businesses in the world to power their business, enable their people and accelerate digital progress.