It is said that “Data is the new oil” and it is not without a reason. There are numerous success stories of companies that have built robust business intelligence based on data analysis – Netflix, Spotify, Amazon to name a few. Data has stories to tell which would be hard for a human mind to fathom without spending an enormous amount of time on significantly skilled people.

Does that mean that only Big Companies can take advantage of the data and built efficient Business Intelligence? The answer is ‘no’.

Marketing Technology News: Avatier Unveils 2021 Spring Release Identity Anywhere Suite

The article explain the importance of Business Intelligence to an organisation and how an organisation can use the data it generates to improve its performance and results.

Small and medium-sized companies have also benefitted a lot from using data to drive their decisions. Using BI (Business Intelligence) gives clarity on price fluctuations of key materials, working capital cycles, customer behavior, employee performances, uncontrolled costs, and the list is endless. By using data, Small and Medium-sized companies can position their niche skills against bigger competitors.

According to a survey conducted on 2000+ Companies using Business Intelligence, more than 74% reported an increase in operational efficiency, 66% reported an increase in customer satisfaction, 74% reported better decisions, 52% reported an increase in competitive advantage, more than 40% reported an increase in revenues and decrease in costs.The ROI on Business Intelligence is very high and one research puts the number at a whopping 1300%. Unbelievable…..right?

During the dreadful pandemic, 83% of data-driven Companies in India gained critical business advantages.

In an uncertain environment, it is the intelligent use of the Company’s “data” that acts as a key differentiator between Companies, as the Company using data can take “clear, thought-through, data-driven decisions” as against organizations who are not using data to drive their business.

Marketing Technology News: MarTech Interview with Ben Brenner, VP of Business Development and Strategy at Digital Remedy

This is how an organization can bring transformation by utilizing its own data;

A.    KPI Management

I.    Identify the Key Performance Indicators (KPIs) – KPIs are important parameters that measure a company’s organization’s health – it is at the foundation of building a business intelligence-driven business. The emphasis is on the word – within 15 to 20 KPIs for the overall organization.

II.    Set benchmark for the KPIs – It is important to set targets for each of the KPIs based on market study and internal considerations. Targets should satisfy the “SMART” criteria which mean they should be Specific, Measurable, Attainable, Relevant and Time-bound

B.    Decision Management

I.    Identifying key decisions a company need to make – Organizations need to take two types of decisions – a) “strategic decisions” includes things like dropping a product from the portfolio due to its poor performance or deciding on new geographical expansion or investing in a new business segment AND b) “Operational decisions” like price-to-quote, selection of vendors, prioritization of dispatches, etc.

II.    Set decision criteria – For every decision that an organization needs to make, there has to be a decision criterion – for example, Return on Investment (ROI) is one of the criteria for deciding to enter into a new business. Employee evaluation score is a criterion to promote or remove an employee depending on the performance. The decision criteria will be based on “variables” that the organization needs to decide based on which it would take the decision. Many operational decisions are “trigger” based set on a “variable”. For example, if the inventory of a particular raw material goes below a certain level, then the organization has to order more material. Here the variable is the “minimum stock” level.

C.    Data Management

I.    Identifying all Data Points for KPI and Decision Management – Once the KPIs are set with benchmarks and also the decision trees with their variables, the next step is to determine all the data points that are needed to measure KPIs and evaluate variables.
II.    Perform data gap analysis – All the data points needed for KPI and decisions must be available with the organization in some form or the other. So it is important to map the data points available vis-à-vis what is needed. The data can be internal data or an external one like market share etc.
III.    Data discipline analysis- Several organizations have data but their accuracy is suspect due to indiscipline in capturing them accurately and in a timely. An analysis of available data should be made to see if they are reliable from the perspective of accuracy and timeliness
IV.    Data improvement planning – Based on data gap and discipline analysis, the organization should plan and implement a “data improvement” program which should be timebound

D.    Design a Business Intelligence Framework

I.    Designing dashboards and data visualizations – It is a proven fact now that the human mind can understand data presented as images much faster than when it is presented in a tabular form. Thus getting critical insights through interactive dashboards will make it much easier to understand and act upon information represented by thousands and sometimes millions of records. Thus designing the dashboards with an ability to get critical insights and locate the exact problem area is the key.
II.    Role-based access -The organization should ensure that all people involved in achieving KPIs and taking important decisions have access to information whenever they need it and wherever they are. Mapping of various roles with the dashboards they need to see is a key step in setting up the BI framework
III.    Alert and Alarms – Setting alerts and alarms in the form of emails, notifications on mobile are important to ensure that critical actions are not postponed for want of human intervention.
IV.    BI automation – It is important that the entire BI solution is automated and does not depend on any human intervention. This will save significant costs incurred by the company for preparing the data. Automation opens up a world of possibilities where the organization can see critical information whenever they need it rather than waiting for a month-end report to take action.

E.    Set up resources for BI

The entire BI solution needs 3 important elements that have to come together:
a.    A strong BI tool – A strong BI tool that has elements of data visualization, alerts systems, role-based access, strong data security, and capability to integrate with other systems is needed
b.    Functional experts – Having a good BI tool is just the first step but more important than that is having the right functional team to design the BI system based on business drivers, KPIs, and decisions. A Company may have to dedicate a team from its internal resources or engage a third-party service provider for performing functional analysis
c.    Technology team – Once the functional team draws the design and functional requirements, the technology team has to develop reports and dashboards in the BI tool as well as set up an integration with the organization’s underlying transactional systems. They will also set up the automation of the BI system.

The organization has to evaluate the total costs of procuring a self-service BI tool, engaging functional and IT teams to run the BI system vis-à-vis the cost of going for a completely assisted BI solution where all the elements (functional, technical, and the BI tool) are managed end-to-end.

Some of the popular self-service BI tools are Tableau and Power BI whereas BiCXO is a good assisted BI solution that provides tremendous value for money.

Bottom line: Implementing a good BI system will go a long way in improving operational efficiencies, customer satisfaction, and significant monetary benefits for the organization but all this can be possible only under one circumstance – Complete belief and support of top management in the BI solution.