Big data, advanced analytics and AI are changing the basis of competition in many industries and offer compelling ways to increase profitability and competitive advantage. Many business leaders recognise that they are behind in developing a smart data and analytical strategy.
While data has always been important to business, the difference today is that the ability to collect, store and analyse digital data has never been easier or less expensive. Fast-moving competitors can harness the digital data that swirls around them to build strong market differentiation.
The confluence of fast-falling costs for sensors and computing, a renaissance in the application of mathematical and statistical tools in business, together with innovative software to harness them, is generating a powerful new opportunity for competitive advantage in data-driven decision making.
Sexy examples of increased profitability, such as calculating on-the-fly optimal individual price offers based on actual consumer buying behavior gain widespread attention. Sorting through billions of unstructured particles of “Big Data” to drive better business outcomes, while elusive for most firms, has a tantalising appeal.
How can we define analytics? The hierarchy of competitive advantage from analytics may be split into descriptive analytics, predictive analytics and prescriptive analytics.
Descriptive analytics begins with basic standard reports, which explain, “what happened”, includes query capability to determine the problem, scorecards to describe what information really matters and concludes with alerts, which may require action.
Predictive analytics, by contrast, begins with statistical models, which help to explain causes and effects, includes randomised testing to consider what might happen with a new approach, and predictive modelling, which helps to consider what may happen next. At this stage of the hierarchy, a firm may be described as an “analytical company”.
Predictive analytics may also help to provide an understanding of the probability of possible future outcomes, based on past trends. This would likely be validated and supplemented by a business leaders’ own knowledge of future likely outcomes of key variables.
The final hierarchical stage of analytical capability, or Holy Grail, is prescriptive analytics, or optimisation, which helps to determine the best actions that can be taken to maximise an objective, such as the value of the firm.
Optimisation requires a firm’s resources and opportunities to be modelled effectively. Naturally, any model is an abstract of reality and can never fully model all of the real world complexities that impact on a firm.
One example of optimisation is to select investments from a range of options. An optimisation algorithm, or mathematical process, calculates the best choices to maximise the value of the firm. This is known as a deterministic solution, which is a single outcome for a specific set of assumptions. It does not take into account risk.
The gold-standard analytical tool to address future uncertainty or risk is Monte Carlo simulation. Probability distributions for key variables are combined to generate values to feed into the optimisation model. With enough scenarios run, an overall probability distribution of optimised firm values is generated. In this case, the optimal investment choices are determined while explicitly considering future uncertainty, given the limitations of the modelling.
Big Data and Analytics
The data you already have today is one of your most valuable, and appreciating, assets. The challenge for many organisations is in harnessing that data into structured and useful information.
The power and affordability of cloud computing now enables organisations of all sizes to cost-effectively ingest masses of data, process it and extract valuable insights, even in real time.
OneNet has worked with organisations to help them extract information from disparate systems, homogenise data into useable formats and present that data in a form that allows for actionable insights.
OneNet is a pioneer in using data to drive business decisions. Today, we leverage that expertise and experience to help you deliver better customer experiences and make better business decisions by analysing your data. OneNet is well positioned to help you gain the information you need to deliver actionable insight to improve customer engagement, increase profitability, and lower costs. Several elements of a potential solution follow:
- Database consolidation – Integrationof your on-premise datawith cloud storage, allows a thereby cost effective scale-up of your legacy data storage capacity. Synchronisation of your on-premise and cloud-based storage provides unlimited data repositories for data analysis, without needing to add any further on-premise storage
- Big Data, BI and analytics – Disparate sources of your data may be homogenised, stored, and analysed in highly scalable and cost-effective cloud storage. Once data your data is prepared for the purpose, analytics performed on that data will help you unlock the latent potential in your data to make meaningful insights securely and quickly
- Data visualisation and reporting - OneNet utilises Microsoft’s Power BI technology to help you to display and report on analytical outcomes to help you to gain insight from your data
There are many potential business benefits to be derived from harnessing big data, including the following:
- Delivering a more personalised experience to your customers
- Creating a more cost-effective supply chain
- Increasing your competitive advantage
- Improving your customer experience
- Helping your organisation innovate faster
- Increasing your profitability
OneNet employs Microsoft’s cloud-based data analysis platform, called Power BI. This solution may be used for reporting and data analysis, working with a wide range of data sources.
Power BI is simple and user-friendly so that your business analysts and power users can readily realise the potential benefits. The Power BI platform also has advanced capabilities that enable you to create customised dashboards with powerful visualisations and drill-down capabilities.
As the solution is relatively easy to use and quick to deploy, Power BI can reduce your dependency on IT resources.
Consulting and Integration
The adoption of a data-driven culture and capability is a multi-period journey. OneNet is well qualified to contribute to your big data and analytics team, as a lead partner or member of your analytics team. A no-commitment discussion to identify how OneNet’s strengths may be employed in your analytics journey is a good starting point.
A consulting and integration assignment may be an appropriate second step.