Continuous improvement requires continuous intelligence

Business leaders must take the initiative to leverage their data using new technologies and approaches to adapt and succeed in the digital world.

The digital age has presented businesses with a significant challenge: adaptation. Organizations can only hope to survive in this new era if they are able to adapt to the new reality of doing business.

For the past few years, adaptation efforts have fallen under the umbrella of digital transformation. It is now widely understood that organizations must engage the groundswell of digital data and refine it into a byproduct that can inform decisions or instantaneous actions. However, because digital data flows continuously, the data engagement model should also be continuous, leveraging advances in machine learning, AI, IoT, and analytics. This sort of continuity will catalyze organizations to adapt and thrive in the new digital reality.

Continuous intelligence

Because IT has historically focused on batch processing, the concept of continuous processing is fairly new to most organizations. Continuous intelligence waits for nothing. Not data collection periods, not resource availability, not processing time. It is the non-stop generation of insight and actions based on operational data stores as well as streams of data and events generated in the moment. It is the ability to harness an ever-changing environment where the data is constantly flowing and the insights and actions are perishable.

According to Gartner, success can only be achieved in a world that is constantly changing by implementing a continuous approach. Gartner suggests that continuous intelligence is at the heart of fast-paced digital business and process optimization. However, continuous intelligence is not only about IT architectures. Successful implementation requires a change in managerial approach as well.

New leadership approach

Conway’s Law gave us the insight that system designs reflect the communication structures of the organizations that design them. Because designing continuous intelligence requires new architectures, it is critical that the organizations designing them reflect the architectural intent.

Most organization structures today assume they are performing in a batch-processing world. One team works to complete a task before handing it off to the next team, there is no continuity of visibility or activity. Initiating a continuous intelligence effort with the limitations inherent in a batch processing management model will produce feet but no wings.

To fully implement the continuous intelligence approach, business leaders need to adapt to agile management methodologies. Just as the DevOps world engages continuous integration across teams, so must the larger IT organization engage in a more active and constant way. The rate of engagement is necessarily radically higher, that is the only way for the broader team to understand what’s going on in the organization. This approach will facilitate initial success and be the foundation for staying ahead in an era of new, dynamic technologies and continuous change.

The need for speed

One of the fundamental changes to the IT stack required for continuous intelligence is a new data processing layer designed to perform at extremely low levels of latency. Regardless of whether the data already exists in operational data stores or arrives in event-based streams, the concept of continuity is at odds with latency.

Our traditional systems of record do not have this design point, nor should we expect them to. They will continue to do their job well while a new, complementary data processing layer is added.

Innovations in IoT, machine learning, and AI assume both constancy and immediacy. Business value has become inextricably linked with real-time action. New applications require speed and scalability in the underlying data processing to produce responses as well as to 'feed the beast' to inform models. The money is in the microseconds, whether the data is at rest or in motion.

Digitization has permanently changed the business landscape. Continuous intelligence is achievable. Business leaders must take the initiative to leverage their data through new technologies and approaches to adapt and succeed in the digital world.

Author: Kelly Herrell

Source: TDWI

How to be a digital leader in a time of large-scale technology transformation

Following interviews with hundreds of industry executives, McKinsey recently shared fivecornerstones that are enabling organizations across every industry to integrate and capitalize on advanced technologies such as analytics, AI (artificial intelligence), machine learning, and the Internet of Things.

These cornerstones of large-scale technology transformation include: 

1. Developing technology road maps that strategically focus investments needed to reinvent legacy businesses and create new digital ones
2. Training managers to recognize new opportunities and build in-house capabilities to deliver technologies
3. Establishing a modern technology environment to support rapid development of new solutions
4. Focusing relentlessly on capturing the strategic value from technology by driving rapid changes in the operating model
5. Overhauling data strategy and governance to ensure data is reliable, accessible, and continuously enriched to make it more valuable 

When it comes to the latter, McKinsey says that while every executive understands data will yield a competitive advantage (MicroStrategy’s Global State of Enterprise Analytics Report 2020 shows that 94% believe data and analytics are important to digital transformation and business growth), few have put in place the business practices to capitalize on it. For most, the data is messy and hard to access, and current technologies cannot scale to take advantage of a fast-growing wealth of data sources. 

Constellation Research founder and Disrupting Digital Business author Ray Wang says this is what's driving the growing divide between digital leaders and laggards, one where digital leaders are taking 40-70% of market share in the future of data in digital transformation.

'Digital leaders are folks that understand the impact of data', says Wang. 'They understand how to ask the right business questions. They understand that integration is important. They understand why data quality is needed. They understand why testing is so important before releasing something, because if you don't properly test, what you end up with is a lot of bad insights and next best actions which reduces the confidence in the data. They understand the human factors behind data and data design'.

'They're always looking for new data sources and how to get those data sources to work', continues Wang. 'And they're always trying to figure out how to empower people with not just data, but the ability to make better decisions'.

'Using data effectively in digital transformation is not easy. To make it work, you've got to have your data house in order. Build a foundation to support strong governance, data prep, streaming, and agility'.

Author: Tricia Morris

Source: Microstrategy

The 5 dimensions that help your business with a successful technological transformation

Businesses that have mastered the ability to change quickly share one common denominator: technology is transforming their business. Technology can be a transformative engine that gives your organization the power to learn, adapt and respond at the pace of change.

Today’s IT leaders have many tools to enable speed and flexibility, including Lean IT, Agile, DevOps and Cloud First among others. However, these concepts alone rarely deliver the technology transformation that organizations need because companies are tempted to think of transformation as a predominately organizational journey. Organizations need to think much more holistically in order to lead a technology transformation and enable a flexible and efficient business.

There are five essential components, the 5 dimensions, that can lead to a successful technology transformation. Each dimension allows you to learn something unique about your organization, somewhat similar to an archeologist digging through an archeological tell. The 5 dimensions can be used to drive a holistic technology transformation that fits your historical and cultural context.

Here's a brief look at the 5 dimensions and how they can serve you:

1. Business alignment 

Far too many organizations build their technology strategies by aligning with the tactics of their business operations. The result is strategic dissonance, as IT resources are not correctly prioritized to meet strategic business priorities. This misalignment leads to new architectural debt. Today's tech leaders need to understand the organization's business model and build a technology strategy that unlocks and empowers that model, ensuring alignment along the way.

2. Architectural debt 

Most organizations suffer from technical debt: systems built for expediency instead of best practices. Architectural debt, on the other hand, is the systemic root cause in the creation of technical debt. A recent survey by IDG and Insight Enterprises found that 64% of executives cited legacy infrastructure and processes as a barrier to IT and digital transformation. ‘Legacy infrastructure and processes’ is just another way of describing architectural debt. Debt is an important concept for technology organizations because it constrains flexibility and results in an IT organization managed by the inertia of their systems. If you want to lead an IT or digital transformation, you must quantify your architectural debt and pay down (minimize) or pay off (eliminate) that debt in order for your transformation to be both successful and sustainable.

3. Operational maturity 

IT organizations exist on a spectrum of maturity, classified into three distinct phases: operators, automators, and innovators. Operational maturity is a critical enabler of an organization’s ability to execute their vision or goals. There is a high correlation between business value and operational maturity. Mature IT organizations are focused on high quality, business value-added activities. An IT organization’s capabilities directly correlate with its phase of maturity along our spectrum. You must look at the people, processes, technologies and artifacts to understand where change must occur in order to increase operational maturity.

4. Data maturity

Clive Humby, U.K. mathematician and architect of Tesco's clubcard, famously said in 2006 that 'Data is the new oil… It’s valuable, but if unrefined it cannot really be used'. Nearly a decade later, The Economist called data the world’s most valuable resource. Many organizations are sitting on mountains of unrefined data, uncertain how they should be storing, processing or utilizing that valuable resource. Top-performing organizations that are using data to drive their business and technology decisions have a distinct competitive advantagetoday and tomorrow.

5. Organizational dexterity 

Your organization’s capacity for innovation and change directly correlates with its dexterity. To quote Peter Drucker: 'In times of turbulence, the biggest danger is to act with yesterday’s logic'. Organizations falter when they have institutionalized a culture of yesterday’s logic. An agile organization isn’t just a decentralized organization, it’s an organization that has the capability to learn and unlearn, demonstrates complex problem solving, emotional intelligence and much more.

We live and work in turbulent times, with more volatility on the horizon. Is your technology ready? How about your organization? The 5 dimensions play a critical role in building a holistic understanding of your organization. Seeing the whole picture enables you to build a pragmatic path forward that leads to a true technology transformation.

Author: Alex Shegda

Source: Information-management