Addressing the Trust Gap. It is Possible
In our previous blog, we spoke about how in today’s world of rapid and constant change it has become ever so important to make the most of real-time inflow of data. Data is the new oil – and like oil, data needs a refinery before it is used across business use cases. To quickly take a step back, this trend always reminds me of the comic Tintin and The Land of Black Gold – “Boom! … One day your car goes Boom!”. The plot revolves around car engines exploding because of faulty petrol at its source. Similarly, if data is not clean at the source, your business decisions are bound to go “BOOM”!
Analytics has been commoditized today, with the entry of open source tools and technologies. However, there is a significant trust gap when it comes to the consumption of analytics. How much do you trust your data? How significant is the output of analytics in the organisations board meeting? While in our last blog we looked deeply into the trust gap and its roots, at the end of the day, we need to realise that analytics is just an application of Math-Technology-Business on data. So, if we believe in Mathematics, have faith in the technological revolution and are confident of our business intuition, there is no reason for analytics not to be considered as the most critical function – all that remains is refining the oil, i.e., data.
We at Subex, recognize and respect this trust gap. We also believe an analytics strategy should build around the golden triangle – People, Process, and Technology. The first and most critical step would be to have analytics done in a democratized manner. Everyone in the organization, from the C-Level, to the Department Head level, to the Analyst level should be armed to be data-driven. The involvement of machine should not undermine the trustworthiness, nor should it lead to a decrease in human involvement; instead, you should leverage the best of both human and machine intelligence to improve products, enhance the quality of service (QoS) and derive more returns from your investments.
Does Human Intelligence + Machine Intelligence = Trust?
Taking the Human Intelligence + Machine Intelligence philosophy into account, we have come up with a concept known as Subex ACT (Analytics Centre of Trust), designed to bridge the Trust gap by covering the end-end cycle of Data-Insights-Decisions (D.I.D.). Let us take a quick look at the three pillars of our ACT program:
- Defining a Strategy
Before starting the analytics journey, it is imperative to assess the following
- What is the analytical maturity of the organization?
- What are my objectives from the analytical program vis-à-vis the business vision
- Do I have a roadmap in place?
The main Objectives of this process are:
- Setting up the goals for the organization: The Strategy can help deliver competitive advantage, create incremental revenue opportunities, and reduce costs.
- Assessing your analytics maturity vis-à-vis your goals: Understand where you are in terms of your analytics maturity and identify the target maturity which will help you reach the goals defined in step 1
- Plan for the Transition: Understand how you will transition from your current maturity level to the desired maturity level and ensure the process is time-bound, tangible and step-wise. What we recommend is that you identify tangible use cases, such as churn, and move the analytics maturity of addressing churn from, say, 3 to 4. Once that is completed, define another use case and increase the maturity to address that similarly
- Setting up an Information Infrastructure
Post defining the analytical strategy it is imperative we have the right set of tools to handle the task at hand. The tools which organisations need today need to be the following:
- Agile: Create the ability to address the problem statements based on the requirements
- Scalable: Should be able to handle massive volumes and different types of data
- Reliable: The information that is generated by the system needs to be trustworthy
- Real-Time: For quick and accurate decision making the reports should be in real-time
- API Integration: The tools should be compatible with API-based integration
- User-friendly: Consumption of the reports/data should be easy to use
- Secure: The tool should be compliant with security guidelines
- Self-Serviceable: Accessible UI enabling the end user to self-generate reports
Such an Information Infrastructure should offer a self-service reporting environment wherein each stakeholder gets the access to the tools to analyze and act upon the information. This will not only reduce the time gap in execution but raise the operational efficiency to a new level. As the model evolves into an Analytics Centre of Trust (ACT), the transformation journey becomes smooth.
- Analytical Driven Business Outcomes
The final piece of the Analytical Framework, is clearly towards the analytical output. For too long, organisations have set up analytics practices with a mandate towards delivering on analytics outcomes. Subex is of the firm belief that the key to analytics is to attain business outcomes while ensuring insights are available across all audience levels in a democratized fashion which is easily understandable.
The world of digital technologies is open for Telcos to build new business opportunities as well as excel on the existing ones. It’s time to identify the gaps in your analytics strategy and develop an ACT that helps you climb the ladder faster. As an organization is preparing to capture the active markets, your analytics goals must focus on using information as a strategic asset to generate revenue, improve operational efficiency and provide best-in-class customer service.
In our next blog, we will cover how Subex ACT helps CSPs regarding addressing these three pillars and how it helps bring Agility, an Analytics to Business mindset and Democratization through Consumable Outcomes to your organisation.
This blog has been co-authored with Sandeep Banga.
Aditya heads Sales & Presales for Analytics for Subex in Africa. He has been in the analytics industry for 6+ years, with experience in Retail, Pharma, Technology and Telecom domains. He believes that Analytics is delivered right only in an Iron-Man setup (Man-machine model).