3 Key Elements to your Modern end-to-end Data Strategy
A data-driven organization is imperative for the future
By 2024, global spending on AI, will reach $110 billion (IDC). No matter where you are today in our ML journey, you need a data strategy that works for your business needs now and for the future.
AI and Machine learning hold the power to completely transform existing business process and create new marketing and ways of thinking entirely. But at the heart of the success of these technologies is data. Data is the heartbeat of AI and ML, and unlocking its potential is one of the most important business challenges we face today.
Over the past decade, data has become the centerpiece of digital transformation. More today than ever before. It is no wonder that at this year’s AWS re:Invent AI/ML keynote, Swami Sivasubramanian, VP of machine learning at AWS, focused on the importance of data to achieving excellence with ML. After two years of virtual meetings, it was invigorating to be present for Swami’s keynote live and in person. He shared, “From modernizing your data infrastructure to unifying your data to the best of data lakes and analytics innovating with machine learning — this is going to help you re:invent data immensely.”
Looking at the themes, so much is relevant to how we are approaching harnessing data with our technology at SuccessKPI:
Reinvention is Driven by Data
What is powering the ML revolution? It is all about how customers are reinventing their business with data. “Data is the underlying force that fuels the insights and the predictions that help you make better decisions and spur completely new innovations.” Swami shared.
For example, tuition and Student Loan Assistance company, Edcor, tackled a digital transformation project which included a new cloud-based contact center with Amazon Connect and USAN-based technologies to replace a legacy on-prem set of technologies. SuccessKPI provided integrated analytics between Amazon Connect and USAN-based solutions. Edcor created full suite of analytic capabilities, including custom reporting, real-time and historical analytics, a robust AI/ML based speech & text analytics, custom QM scorecards and Automated Agent Scoring powered by AI. For their innovative solution, Edcor captured an Honorable Mention in the Best in Class Contact Center category at the 2021 CCW Excellence Awards.
Big Unstructured Data
“Big data” was coined in 1987, and since then, data has been multiplying through organizations like never before. Not just neat, structured data but 80% of data today is unstructured. Diverse data like images, documents, handwritten notes, geospatial data are spreading faster than most companies can keep track of often making it a challenge when trying to get value out of the data.
Survival of the Most Informed
While tackling unstructured data can be challenging, it is imperative to your current business and future. “It is the survival of the most informed, and those that can put that data to work to make better, more informed decisions, and respond faster to the unexpected and uncover completely new opportunities. Those are the businesses that are going to thrive,” Swami presented.
SuccessKPI analytics platform provides 360-degree view combining un-structured data (such as call recordings, chat transcripts, emails, social media data feed etc), CRM systems (such as Salesforce, ServiceNow, Microsoft Dynamics etc), HR and Time tracking systems (Workday, Deltek etc), contact center interactions data (Genesys, Talkdesk, Amazon Connect, Twilio, etc). Our Customers are uncovering new insight combining all data together and making informed decisions to operation their business.
Use Cases of Data Driven Decision Making
The use cases of machine learning across all industries are incredible.
On the front (phone) lines – battling the pandemic
The CDC faced the initiative to get the entire country vaccinated, as part of their strategy “the CDC worked with Maximus and AWS partner, SuccessKPI…to understand an end-to-end view of agent effectiveness and insights into the root causes of vaccination hesitancy.” Swami highlighted as a key success story.
This CDC use case was also presented in one of AWS re:Invent’s breakout sessions,” Accelerating innovation with AI and ML”. The full solution required tuning up 21k+ agents in under 8 weeks, including testing at scale. The solution included end to end visibility into topics, themes, sentiment, caller journeys, effectiveness of IVR and WFM insights in addition to handling conversations from the caller.
The world of sports – where every second matters
The Australian swim team has their eyes set on winning gold at the Olympics in 2024, and AWS shared how they are hoping to do that with the help of machine learning. With the AWS solution, the team has been able put data like stroke mechanics, psychologic testing, race analysis, skills, turn metrics all together to better understand each swimmer’s performance, and extract peak performance in the pool.
A modern end-to-end data strategy
Building a comprehensive end to end data strategy is not always an easy and straightforward journey. According to a McKinsey survey of B2B companies, 86% of respondents said they wished they could do more with data.
Implementing a modern end-to-end data strategy is more important than ever. One that can handle the enormous growth in data and one that can tie together the full data journey from storing your data to putting your data to work.
Swami’s three key elements to a modern end-to-end data strategy
- Modernize your data infrastructure: “Don’t run your database like you are living in the 1990s”, Swami said. “Don’t run your data infrastructure on-prem or self-managed in the cloud when you must deal with so much undifferentiated heavy lifting”
- Unify your data: Want to make decisions quicker? Create “a single source of truth” by connecting everything together including your data lake, data warehouse, and all your data stores into a coherent system that is secured and well governed
- Innovate with your data: create new experience and rearrange old processes with AI and Machine Learning
In his keynote Swami concluded, “data driven organization is imperative today and for the future of your organization. It is the difference between the companies that will just survive or those that are going to thrive.”
Watch Swami’s keynote and SuccessKPI’s CDC use case here:
Piyush drives technology vision and architecture across SuccessKPI. He leads a globally distributed and diverse team of technologists responsible for building, operating and securing the company’s innovative serverless, highly secured and AI driven products and platform. He is also a member of company’s Board of Directors.
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