Intelligence Driven Business: Making it Real

By Ramshanker Krishnan, Sr. Director of Enterprise Services and Delivery of Data and AI, Microsoft

Ramshanker Krishnan, Sr. Director of Enterprise Services and Delivery of Data and AI, Microsoft

The Digital Feedback Loop

Companies who survive the digital revolution will do so only by capturing critical information across software-infused products, operations, customer engagement, and employees.

The digital feedback loop breeds success by allowing companies to improve customer experiences based on their continually evolving needs and innovate based on what customers really want.

Enabling the digital feedback loop is taking that signal 'digital feedback’ and driving it back into the products and services you deliver.

An intelligent platform is at the core to collect data and capture these signals across boundaries. It then enables to connect and synthesize the data to create deep insights, leading to meaningful actions and improved business outcomes. This allows an organization to create deeper relationships with their customers, have more efficient operations, more effective employees, and better products and service.

An Intelligent platform must support the waves of innovation happening in the field of artificial intelligence such as deep learning, knowledge mining, reinforcement learning. It needs to break data silos and help uncover the latent insights present in structured-unstructured real-time data from sensors and make it readily available to be processed. It harnesses the power of the cloud and the edge to provide deep insights and supports real-time and automated decision support.

Becoming more data driven is now on the critical path for organizations to stay competitive and meet their customer and stakeholder demands.

It is no surprise that majority of global executives say that effective data and analytics strategies are essential for business transformation. An intelligent platform, built for purpose, with security and privacy at its core, can help address common challenges around data management. It enables the democratization and broad usage of the technology across the organization.

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Enterprise-Wide Operating Model

Data and analytics has a broader, enterprise-wide purpose and needs to be integrated deeply into the way organizations work. There needs to be a clear link to business vision and an intelligence driven culture supported by measurable goals. This needs to be followed up with an operating model that aligns with the business vision, establishing the following:
1. An innovation process that can identify a list of use cases aligned to the overall Executive strategy.
2. Business use cases prioritization based on ROI and rapid experimentation.
3. Strong technical and functional capabilities that support productionizing the prioritized use cases, through agile delivery and dev ops approach.
4. Governance that facilitates efficient decision making across IT and Business. Leveraging the best practices around compliance, ethics, change management, and value realization of use cases.

A strong operating model will ensure that you have the control, innovation, and speed to market while keeping the costs manageable.

Adaptive Leadership: Addressing the Human Element

The biggest blocker to Digital transformation is the lack of cultural transformation. Building the right culture requires more than just investments in tools and technology. It requires adaptive leadership to directly address the human aspects. The concept of adaptive leadership was extensively researched and published by Ronald Heifetz and Marty Linsky in their book, “The Practice of Adaptive Leadership”.

The most common cause of failure is addressing transformation as if it were merely technical challenges. We are the first generation in human history that is dealing with decisions made by machines. While the algorithms and models are progressively getting better, we need to address the human elements of building trust, while continuing to be accountable for the outcomes. Fear of the unknown needs to be overcome through awareness, creation, and trust building.

The other key blocker is the emerging skills gap. While existing people need to learn new skills, there is also a need for new roles. As every company moves towards being a digital and AI company, they need new skills that are typical to technology companies. One such skill is that of product owner/product manager, which helps create and manage digital experiences, through products and services. There are many such roles that are emerging, such as business translators, change managers, data scientists, and data engineers, to name a few. There needs to be a concerted effort to build a sourcing strategy to identify in-house versus external talent for these skills. It requires focus and investments towards establishing academies with robust curriculums, to help reskill existing employees, as well as gearing up talent acquisition programs to attract the best and brightest from the market.

Taking a ‘Balcony View’—One of the Key Elements in Adaptive Leadership

To watch everyone in action and identify patterns that would be hard to observe, if you just take a project or program specific approach. This should enable continuous learning that can help course correct based on failures, keep an eye on the cultural transformation, and ensure business value is being realized.

An intelligence-driven business can only become real if it is built on the core pillars of intelligent platform, a robust enterprise operating model, and establishing a control tower that enables you to use AI responsibly, accelerating your transformation journey.