Data science is all about bringing the power of algorithms, statistics and machine learning together with an organisation’s data, to test hypotheses, extract insights and build innovative products. Data science methods can inform decision-making by generating sensible predictions, creating products through machine learning and automation, and helping your organisation be more efficient. In this article we’ll discuss 5 ways data science can benefit your organisation.
1. Get the most out of your data infrastructure and business intelligence solutions
Data science solutions are most effective when built on solid data engineering infrastructure and business intelligence solutions. Data quality and quantity is the limiting factor in any data science project, so collecting the right data and storing it in an appropriate database infrastructure is essential for deploying a successful data science solution at scale. Any organisation working in a data driven way should also be using business intelligence to monitor KPIs and understand how they relate to the measurable inputs and outputs of their organisation. Cloud platforms, such as Microsoft Azure, make building and maintaining data infrastructure streamlined and cost effective; Azure also provides excellent tools for integrating this infrastructure with data science solutions, and deploying them to endpoints such as Power BI reports and web applications. From this foundation of cloud infrastructure and BI awareness, data science solutions can be deployed at scale and used to maximum effect. By training machine learning models with plentiful and relevant data, they can generate useful predictions and use statistics to test business hypotheses with great success.
2. Optimise your processes and accomplish more
Data science can help you be a more efficient organisation by cutting costs and maximising the impact of spent resources; this goal of optimisation is a common feature of data science solutions. Statistical models of historic advert conversion rates can be used to maximise return of marketing spend across different platforms. Process mining offers tools for understanding bottlenecks in your business processes, helping minimise lead times. Through supply, demand, and price forecasting, organisations can plan how to prepare for or benefit from predictable trends and seasonal variation.
3. Better understand your customers and improve sales
One of the most effective applications of data science is in customer profiling and retail analytics; understanding who your customer is, what they buy, at what time and what marketing they respond to. Using customer segmentation, market basket analysis and demand forecasting, you can maximise sales through targeted advertising. By mining datasets of interventions and outcomes, organisations can understand relationships between patterns of customer contact and sales or churn, helping you retain customers for longer and maximising your customer lifetime value. Using recency frequency monetary value analysis, you can identify the most valuable customer profiles and prioritise them, with personalised offers and marketing.
4. Build innovative products and stay competitive
Data science methods enable you to convert your organisation’s data into innovative products, to improve services, automate processes and stay competitive. AI chat bots and recommendation engines leverage machine learning to automate the management of your customer relationships, helping cut costs and serve your customers more effectively. Modern natural language processing algorithms allow you to extract sentiment information from customer feedback and rapidly scan areas for improvement. In recent times, machine learning algorithms and the ubiquity of compute enable predictive models like these to be deployed at scale and across various platforms, offering countless opportunities to deploy innovative products, driving competitive advantage.
5. Reap the benefits of data driven decision making
Data science methods offer powerful tools for data driven decision making and planning; such as attribution modelling for understanding where to spend marketing resources, to demand forecasting for staff or inventory planning, and visualisations which show key influencers and relationships in business processes. Data driven organisations, who strategise in terms of quantifiable goals and act on insights derived from data, outperform the competition and data science tools facilitate this. [1]
Conclusion
Organisations who invest in their data infrastructure, collect quality data and ask in-depth data science questions will be at a significant competitive advantage well into the future. Simpson Associates can help your organisation take advantage of the benefits data science can bring and move into the world of data driven decision making and innovation.
If you have any question about data science, machine learning, or any of the tools mentioned in this article, please feel free to speak to us using our live chat, where one of our experts will be happy to speak with you in more detail.
Blog Author
Dr Robert Constable, Senior Consultant, Simpson Associates
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References
[1] https://online.hbs.edu/blog/post/data-driven-decision-making
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