For at least two decades, the emphasis among business intelligence (BI) practitioners, implementers and integrators, consultants, vendors, and others has been on making business more “BI-driven.” Companies have invested a lot of time, effort and money in building datamarts, data warehouses etc. to do away with reporting on siloed systems and creating a single version of truth. Today these systems are mission critical in most of the organizations.
With the change in consumer landscape these “BI-Driven” systems are not enough. The rich data collected in these systems has to be leveraged now for deeper insights. We are living in a highly interconnected world where just analyzing the transactions a customer had with your organization is not enough. There is a need to analyze various interactions that a customer has about the organization as well his views, feedback on the product and services offered. This can be done by integrating analytics across various channels of ERP, CRM, Social Media, Call Center and any other channel that has a touch point with the customer. On this data, deep analytical insights using data mining should be developed that provide real business insights and value. This will make any organization truly “Analytics Driven”.
This whole area become so vast that the key question that arises is where to begin and how to approach this journey to become “Analytics Driven”. The path chosen has to be least disruptive, require minimum investments and provide maximum business value. A few key guiding principles are as below:
1. Key Business Issues
The likelihood of any project taking off successfully is much higher if it addresses the key business challenges. The common business challenges in consumer facing industries are Customer Acquisition, Churn, Cross-sell, Up Sell etc. and all of them can be successfully addressed by an analytics driven approach. Once a business problem is resolved, users will be very keen to get the benefits in other areas and it will help spread the adoption of analytics. This will overcome the initial issues of budget availability for the project.
2. Assess the proximity to the customer
Different businesses have different proximity to the customer. A telecom company has a high proximity whereas a consumer durables company has lower proximity. This does not mean that low proximity businesses do not need an analytics driven approach,but rather that they can afford to take one step at a time whereas a high proximity business has to start now.
Many businesses feel they are low proximity simply because they do not directly sell to thecustomers, like 2 wheelers, Cars where they do not even capture the full customer data. This is not true. These kind of products have high customer involvement and are big ticket purchases. How a customer feels about purchase experience, service and usage of the products is very important to his feedback, and influences others. Direct interaction with the customer using an analytical approach will help increase sales and improve product innovation. In the interconnected world, a customer has far more influencing power than a lot of businesses realize.
3. Important Customer Channels
Different businesses have different touch points/channelswith the customer that have high business value. For a restaurant industry the customer feedback on social media is far more important than an FMCG industry, like soaps, where the customer may not even provide the feedback. To identify the key customer channels will make the boundaries of the project more clear and have greater impact. Typically in a B2C business, Social Media, Customer Service are important channels apart from CRM, POS etc.
4. Assess Data availability
One may identify the important channels, but if the data is not available or the available data is not properly sanitized, analytics can provide completely wrong results. It is best to start with areas where the data availability is high and the quality is good. In the areas where the data is not present there should be a strategy defined to acquire that data. Typically in industries like automobiles, the data captured is not good or even not captured at all. For these industries the customer data is very important and organization should embark upon data acquisition strategy to build a long term “analytics driven” approach.
5. Senior Management Commitment
Analytics is something new to business. Although we believe that this is the most business critical discipline, often it is neglected either because of lack of exposure on how it can help or lack of bandwidth of the marketing team. “Analytics driven” approach requires a high level of senior management commitment and involvement to ensure it is implemented across the organization. Without that commitment, other operational issues will take priority for the team. More often than not we get busier in “cutting the wood” than “sharpening the saw”. It is the senior management’s responsibility to ensure that the teams sharpen the saw and, if required, to provide the necessary tools to so do.
6. Keep it small
The best approach is to keep the initial project small and provide business value. Once the business will taste blood they will come for more. With new technologies like Open Source, Cloud etc., analytics now can be implemented at fraction of the cost it used to be earlier.
With competition intensifying, customers becoming more discerning and less loyal, increased social media influence and overall power shift in the hands of the customer, only businesses that will leverage analytics to its fullest potential will be able to survive. Luckily, with technological innovations there is hardly any investment needed in H/W, S/w and the analytics-driven approach can be adopted by all sizes of organizations at minimum cost and risk. The impediment is the willingness of the senior management and the team to embark on this exciting journey.