Getting the most out of your Business Intelligence projects
Businesses are facing more sophisticated competition in the market every day and the race is on to constantly deliver higher levels of customer service. Delivering better customer service first requires a greater insight into customers’ preferences and behaviours. Social media is a good source of additional behavioural data, as is the data hidden in your internal CRM, PoS and call centre recordings. This is a sound basis to develop a strategy for retaining those customers who are best suited to the organisation, while “incentivising” those customers not suited to the business, to switch to the competition.
Finding and using the data
While many organisations do not know where to start gathering information about their customers, others know exactly where this information resides- hidden in the company’s systems and call centre stores and locked in sales and marketing databases, on social media sites and in back-end financial systems.
The irony is that while many organisations possess this information, it is often not usable. Companies that attempt to use this information in its ‘tangled’ format soon give up, pleading ‘data-overload’. Big data and Business intelligence (BI) gives organisations the ability to unravel the hidden knowledge in this knotted data and deliver actionable insights to the decision makers.
Big Data strategy
But implementing a Big Data strategy is not a simple task of acquiring some software, pointing it at the relevant stores of data and expecting answers to begin rolling out. In order to achieve success with a BI project a company needs to consider its key business goals and the actions that it needs to take to deliver on these objectives efficiently and effectively. BI provides the bridge between the goals and the performance. For example, it delivers the insights required to enhance customer relationships through effective interactions with customers in terms of both content and medium, it streamlines the distribution of goods and services through demand forecasting, or it can reduce risk by predicting fraud or identifying consumer attacks on your brand.
With a clear understanding of how BI will underpin the business’ delivery goals over the long-term, an organisation must ensure that the supporting data has a high level of relevance and integrity and that it is intimately understood. This will ensure that it will be effectively and efficiently interrogated so as to deliver meaningful insights that can be actioned across the organisation, with the resultant outcomes being tracked and measured over time.
The most important part of moving to a data-driven business strategy is robust change management.
Change Management
Change Management in data-driven strategies has multiple aspects:
- Alignment with the overall organisational strategy; this may mean that the use of data insights actually changes the business strategy.
- Evangelism and examples of how data-driven strategies have increased revenue and productivity around the world.
- Working closely with the Master data warehouse team and the business analysts to understand the complexities, challenges and business rules around creating a Master data warehouse.
- Communication including the why, when, how, what is expected of the business employees at a strategic level and assurance. This information must be customised to the different stakeholders, so that employees don’t experience communication fatigue.
- Training, which includes both technical training and the relevant level appropriate to each stakeholder group, as well as business training on data-driven businesses, processes and policies.
- Working closely with Line of Business and HR to ensure that people have the right skills, job descriptions and that remuneration is aligned with the Human Capital strategy.
Data repositories
Best practice dictates that the company’s customer data is centralised into a single, accessible and usable repository, sometimes called a data-lake and then analyse it. Sales data should be linked to marketing data and combined with all other data related to customer interaction, including semantic voice recognition and data from back-end financial systems so that a customer centric-view of the customer can be created.
This in itself is a huge advantage for the organisation, since it will identify the same customer in all his guises across the organisation’s data stores and present a consolidated view of the company’s transactions and interactions with each unique customer. To further enhance this data as a platform for analysis, it should also be enriched with relevant external market data, including key demographic variables and the like.
Analysis
Having built the necessary data repository and ascertained the required insights from the analysis function to support the strategy of the business, the analysis should commence with five simple objectives in mind: who; what; why; when and where.
The ‘question’ or ‘end-goal’ could be, for example, to identify: who the ideal customers are after incorporating any hidden costs associated with servicing them. Then one can plan on incentivising or engaging with customers with these same characteristics to begin doing business with the company and encourage the non-ideal customers to move to competitors.
A good first step to this process is to analyse the company’s revenue streams and build an ideal client portfolio around each of those revenue streams, taking into consideration the fixed, variable and hidden costs associated with them. It is imperative that the entire organisation is involved in this process.
Sales, social media behavioural data, marketing, manufacturing, procurement, delivery and management input is key to the successful implementation of a BI project and ensures that the results gained from a BI initiative are actionable across the organisation.
It is imperative that the company has the appetite to act on findings. It is pointless embarking on a fact-finding mission, like that involved in a BI process, if the business is not prepared to respond to those findings by investing in or re-engineering business processes.
Creating real value
When it comes down to it, BI only presents real value to an organisation if the integrity of the underlying data is sound, the data is intimately understood and the organisation is prepared to action the findings. It is only after “actioning” these findings that the organisation will begin maximising the benefit from attracting and retaining ideal customers, reducing costs and ultimately becoming more profitable.
Digital Bridges enhances the Return on Technology Investment by approaching IT from a Strategy, Business and People perspective. For assistance with your Digital Strategy, Translation of your Data Models into Business Plans, Business Analysis and Change Management, please contact Kate@Digital-Bridges.co.za
