Keys to successful digital transformation initiatives

Aug. 19, 2019
Critical to the success of digital transformation is to focus on the subscriber experience, break down operational data silos, invest in the necessary underlying technologies, and initiate digital transformation in bite-sized chunks.

Cable operators that have successfully implemented digital transformation programs have lowered their operating cost, improved their subscriber experience, and enhanced the productivity of their operating staff. Operators who do not implement digital transformation are unlikely to be able to retain their client base and sustain their profit margins.

But many digital transformation programs fail to generate the expected results. Critical to the success of digital transformation is to focus on the subscriber experience, break down operational data silos, invest in the underlying technologies that will support the organization into the future, and initiate digital transformation in bite-sized chunks that can return value quickly to the cable provider and their subscribers.

Have a strategy

Digital transformation is happening. The end goal is to deliver a new or better business model and a differentiated service experience for your subscribers. Putting all available data to work to achieve better, faster, smarter and more automated experiences requires mastery of multiple layers of coordinated technologies, virtual and physical assets along with analytics, artificial intelligence, automation and a lot of data. With digital transformation, there are no shortages of ideas, experiments or projects competing for executive attention, prioritization and funding. Unfortunately, many of these will not deliver value.

Based on our experience in supporting service providers on their journey to digital transformation, we’ve found that focusing on these four areas to be critical to delivering measurable value and enabling continuous improvement:

  1. Placing customers at the center of the digital transformation strategy
  2. Breaking down operational and data silos
  3. Making the right investments to future-proof transformation and enable continuous improvement
  4. Executing initiatives that will deliver value rapidly and enable ongoing self-funding efforts.

Customer-centric focus

Digital transformation revolves around becoming more agile, automated and cost-effective, and most importantly creating highly engaged customers who are more brand loyal and spend more. Always on and immediate response are no longer "nice to haves" but customer requirements. Today, first and foremost, companies need to place their customers at the center of their digital transformation strategy to define the transformational change needed to improve the customer experience and differentiate from competitors.

To begin, this requires mapping the customer journey across customer interactions to determine where service can be improved. Providers also need to understand the relationship between the subscribers’ experiences and other key business and performance indicators. This leads to the second critical success factor -- breaking down operational and data silos.

Breaking down data and operational data silos

To address all the interactions with your customers, you need to break down the operational and data silos that exist across business entities, functional departments and applications.

Every cable provider has vast and growing quantities of data. The availability of data is not the challenge. The challenge is to clearly understand the relationships between the quality of the client experience and the business processes and then take the right actions to accelerate change and transform.

The volume and complexity of data makes it impossible to explore all possible relevant data relationships using traditional approaches. Traditional approaches assume known data relationships that are understood by the business or newly discovered by business analysts. And, most analysts are not looking for patterns outside of their area of focus. To explore combinations of data relationships that may be highly relevant to the customer experience but remain undetected requires advanced analytics and artificial intelligence. It requires using all the data across service layers from the business process to the application through the infrastructure that supports it.

Providing a service while remaining dependent on silos of disconnected data across applications, the network and infrastructure is no longer an option. Providers successfully transforming their operations are measuring service operations holistically and making use of multiple modes of technology and data to drive better experiences and outcomes.

Technology investments to future-proof transformation

Digital transformation initiatives should be focused on the customers and their experience while investing in technologies including advanced and predictive analytics, real-time event-based processing, artificial intelligence, and machine learning:

  • Real-time analytics and event-based processing applies logic and analytics to data as soon as it is produced to enable insights to be developed, conclusions to be drawn, and action to be taken rapidly based on immediately available information. Gartner refers to this as “continuous intelligence.”
  • Artificial intelligence and machine learning enable decisions to be made and actions to be taken that normally require human expertise and intervention.
  • Advanced analytics combined with machine learning can continuously seek out data patterns and anomalous behavior and enhance performance, augment capabilities and initiate and automate processes.
  • Predictive analytics and machine learning can automatically discover the leading indicators and fingerprints that foreshadow problems. The predictive models continuously monitor the incoming data for early problem detection leading to proactive resolution.

Before making technology investments, organizations should consider the solution’s abilities to:

  • Capture, enrich and analyze data across service layers from infrastructure through the business function in real time.
  • Apply an ever growing, changing, and improving set of artificial intelligence and machine learning analytic algorithms and models to these cross correlated data streams to detect opportunities and anomalies, determine root cause and define intelligent real-time action.
  • Use the algorithms, tools and technologies without disruption to upstream or downstream processing.
  • Scale on commodity hardware/compute infrastructure with open core commercially supportable technology neutral to cloud, on-premise or hybrid deployment.
  • Enable business users to make changes to analytic models and rules to reduce the need for continuous engagement of data scientists.
  • Integrate with other enterprise systems to leverage learning and data-driven awareness.

Equally important to the technology investments when embarking on digital transformation is a data-driven and collaborative mindset across the organization. This is needed to break down data and process-driven silos. Improving data literacy throughout the organization as well as in-house competencies in data science, data engineering, machine learning and artificial intelligence are also critical investments for transformational success.

Executing digital transformation initiatives to deliver rapid value

At Vitria, we recommend our customers begin by organizing around the customer engagement processes within an end-to-end service or subservice. The best scenario is to move rapidly but start in those bite-sized chunks that are going to return value to the customers and to the organization quickly. We understand that successful digital initiatives lead to data-driven execution, that is, the correct use of all available data to guide or automate the next best response under all operating conditions, all the time and in real-time.

We recommend beginning by gathering the data associated with the service or subservice from many different dimensions, automating data feeds and building the analytic pipeline. Operationalizing the full analytic pipeline in which business context is used to determine relevancy, root cause or next best action results in the real value.

The table lists a few examples of how operationalizing the analytic pipeline can result in rapid recognition of value within the cable industry.

Digital transformation is complex and can be extremely expensive if investment and execution is not clearly tied to a business case and outcomes. Focusing on improving the end-to-end experience of the customer, building analytic pipelines across operational data silos, investing in technologies that will enable and support continuous improvement and beginning with initiatives that can return value quickly are critical to successful digital transformation. Begin by understanding what your business is capable of today and then put a plan together that makes sense that you can implement incrementally.

Debra Schleicher is CMO at Vitria Technology Inc., which offers an advanced analytics platform for agile, fast and simplified digital transformation. She is a global executive skilled in helping companies achieve true competitiveness by intensifying the effectiveness of field and channel sales organizations.