What is a Digital Transformation?

I've recently been asked to describe and define transformation so that organizations, end-users, and vendors can claim transformation. According to the multiple definitions I found on the web, "A transformation is an extreme, radical change" So what do we deem extreme and radical? I would say that while pursuing a digital program, an organization discovers a new or dramatically extends a business model. An example would be an insurance company that became so great at insurance claims that it started a subsidiary to manage other organizations' claims. Another would be if an organization had a significant change in its competencies and skills that it looked and behaved radically different. However, there are incremental ways of sneaking up in these sweeping changes and transformations. So it might take a while to claim a true digital transformation.

While I don’t think that transformation ends, there are points in the transformation process to declare an organization transformed. To that end, I tried to develop a way to measure if the transformation effort is significant. Besides the softer sides of organizations like culture, organization, competencies, and skills that are harder to measure, there are five dimensions of change that I was able to noodle out to describe here. I'm sure this will morph over time, but this is my first stake in the ground, and I'll go from here. See Figure 1 for a spider diagram (aka Kiviat diagram) of the dimensions of transformation where I showed a typical traditional process or application measured on the diagram. The idea is to move the measurements to the edge as depicted by the red arrows. The five dimensions are described below. While the shape will vary by organization, a transformation would occur with an average of a "4" for each measure.

                                       Figure 1 Transformational Dimensions

Innovation: You can find many business leaders and business GURUs saying that innovation is the new area for competitive differentiation. I find this hard to argue with as many new digital technologies are emerging as business climates are changing and new/non-traditional competitors are entering many industries. So organizations that can match the many moving parts of customer need with the emergent set of digital technologies at the right time will be pretty innovative. Like it or not, change is accelerating, and how organizations deal with it will make the difference in the survive, thrive, and capitalize continuum. If you are reacting to table-stakes change, you might survive. If you are collaborating or ideating on better solutions, you can go beyond survival. If you are "built for change" and practice agile approaches, you are more likely to thrive. If you practice "Out of the Box thinking and implement it before others, you are likely to capitalize. Pushing this dimension to the edge requires a stomach for risk. Take the risk to become innovative.

Personalization: Today, if you know your customer and have much of the data accessible in one spot or as few as many, you have a good chance for survival. However, this is the minimum. You need to know more about your customer, which notably includes their overall goals and the goals of each interaction with your organization. Organizational goals will often be at odds with customer goals, so striking a balance between your organization's goals and your customers' goals will be essential. This goal confusion is where digital assistance and real-time analytics can help sharpen focus on what the customer really wants. Listening to the customer sentiment emerging in their voice and moving images can tell you a lot at the moment or over time. Customers do not just want standard transactions aimed at organizational outcomes; they want better practices aimed at their whole journey. This process includes transactions outside of your organization's scope at times. This process applies to employees, partners, and vendors as well. Pushing this dimension to the edge will imply more short-term costs, but the outcomes will be more profitable overall in terms of satisfaction and loyalty. Invest in your constituents.

Scope of Impact: Often, short-term costs and timing can be wrung out of departmental processes and workflows to the delight of the accountants and the department heads. However, cross-organizational methods that consider the goals conflicts between organizational units have proven to deliver more benefits over the long haul. The short-term benefits for any department may not be optimized, but the overall outcome will be better for all. Savvy organizations will look at their internal processes and consider comprehensive strategies that include external organizations. Some organizations have outsourced tasks and functions to make them cheaper at the cost of the end-to-end process. When something goes wrong in this case, the "finger-pointing starts."  More progressive organizations will look at complete value chains, entire supply chains, along customer/employee journeys. Pushing this dimension to the edge takes longer and costs more, but the overall solutions are better. Journeys constitute an important principle included in Industry 4.0 that pushes this dimension to the edge. Break down the walls inside or outside your organization.

Automation: Hyper-automation is a popular term today that combines the automation benefits of many digital tech streams. There are many benefits in this particular dimension that have driven BPM, RPA, and Mining. While this is a good direction, this automation needs to become intelligent and learn to become better over time. The collaboration of man and machine starts to emerge to augment the humans involved in the processes. These and future automation will be free to sense, decide, and act independently as they learn over time. However, automation will need to be driven by goals and guided by constraint guard rails. As more business conditions, events and patterns become emergent and changing; this dimension will travel to the edge over time. Free your automation to seek goals and be guided by constraints.

Secure Digital Tech: Digital technology will need to emerge and mature. Organization's experiences with each technology stack, such as iBPMS, RPA, Machine Learning, Mining, Data Mesh, Hybrid Cloud, Deep Learning, Distributed Database, Chatbots, Knowledge-bots and Bots/Agents on the Edge will play an essential role in the future. These unique digital technologies have started to converge in profitable pairings and end up Digital Business and Technology Platforms that work well together. Over time they will become competent and help organizations self-adapt. Combine digital technologies into platforms for better leverage.

Net; Net:

There are no universally accepted transformation definitions that guide organizations today. This writing is my attempt to start one, and I hope it evolves. You will see me use the above dimensions to rate example implementations to show if a transformation is impactful enough to be declared a transformation. Until then, each vendor will claim transformation victory, and organizations will make changes incrementally. Remember that closer to the edge means real transformation. Also, remember to give your organization credit for softer progress implied by skill-building that leads to competencies.

 

 

  

Attaining Real-Time Strategy Adjustment

It was pretty much a given that strategy was done on an infrequent basis from one to three years regularly. The static approach to strategy is no longer feasible or even advisable with the amount of change occurring in the real world. The days of steady-state for long periods are numbered. We see supply chain delays, geopolitical shifts, environmental events, plagues, and competitive landscape shifts, all expecting management to deal with the strategy adjustments. These kinds of push events tend to be reactive and mostly unplanned for most organizations. It may mean reprioritizing efforts and introducing new technologies.

The data is coming on faster as we move from dashboards to fast boards on the pull side of strategy. Because management wants to be proactive on operational and tactical adjustments, there is also a push for aggressive actions highlighted by a management cockpit that enables visualization, understanding, and contextual analytics and predictions. The need is for understanding the current state in contexts and steer to the best outcomes delivered by a variety of solutions represented by new projected conditions. It is not to say that there won’t be operational challenges that need to be dealt with alongside strategy adjustments which could likely include managing work better, measuring performance, inspiring workers, and keeping up with trends. However, there could be potential culture changes, mergers/acquisitions, and leadership changes.

Addressing Real-Time Problems & Concerns:

Up until now, the advantage of real-time or near real-time results on the scorecards and dashboards just weren’t a common tactic. With the advent of real-time data meshes that grow in terms of problem and context scope on the cloud that is easy to link up to, the opportunity to address problems and concerns in a near-immediate fashion is real for many businesses today. Things are speeding up for organizations to cope with large amounts of change and even "big change" scopes.

Understanding Contextual Implications of Specific Situations

Understanding an event, a trigger, or a new pattern can also be much more insightful and associated with other moving parts of a situation that may only be emerging for the first time. Understanding a problem, an out-of-bounds pattern or alarm in its actual context and scope will significantly differentiate the excellence in resulting decisions and appropriate actions, both reactive and proactive.

Collaborate with Others for True Success

Now managers don’t have to observe and orient themselves in a vacuum. Collaborating with others quickly and responsive can also expand insights and test new insights for decisioning and taking intelligent actions. The more perspectives and experience a manager can apply to an emergent or repeating situation, the better the long-term outcome is for organizations.

Survive, Thrive and Capitalize with Innovation

Today innovation is turning into a new digital currency that does require taking unnecessary risks. Innovation, as well as decisions, can leverage the collaboration mentioned above. Being able to innovate on operational improvements, the tactical angles for competition, and new products and services is the typical way organizations succeed. Using key analytics for impact analysis helps the innovation process project results for future state management cockpit results, thus reducing risk.

Balance Management with Risk Guardrails

The balancing side of innovation and change is doing proper and more immediate risk analysis to anticipate both good and bad outcomes. Risk guidance keeps organizations from avoidable dangers. The same kind of insightful analytics can help set up the guardrails and tolerances for notification of violation.

Net; Net:

It is vital to anticipate, intercept and engage in change because the time to market response is essential for competitive advantage. Sitting still is not an option anymore because you will be facing reactive change at all levels; organizations will have to become adept at real-time strategy adjustments. Hopefully, your organization will practice this in a proactive fashion and know when to shift goals to make or keep them relevant. With the help of business strategy software such as a management cockpit, organizations will handle change well.

 

 

 

 

Speed, Scale & Agility Delivered with Distributed Joins

Organizations are driving towards faster decisions and actions across more comprehensive ranging data sources than ever. Broader scope means multiple data sites because of business drivers alone. The distributed join is a query operator that combines two relations stored at different locations. Because the cloud-based distributed database creates many more data storage sites, the trend towards distributed joins is strong. The implication is there will be many more distributed joins in your future. This situation puts a premium on handling larger/broader scales of data and dynamic join capabilities. 

Why the Move to Distributed Databases?

We all know that distributed databases allow local users or bots to manage and access the data in the local databases while providing global data management that provides global users with a global view of the data. Because distributed databases store data across multiple computers, distributed databases may improve performance at end-user worksites by allowing transactions to be processed on many machines instead of limited to one. Increased foresight with tuned distributed databases can be used for business transactions plus analytical-driven business strategy and tactics. The drive to the cloud leveraging incremental relocation and more operations occurring at the edge with intelligent automation all feed the distributed database trend.

Advantages of Distributed Databases

Distributed databases provide some real benefits in the agile world and fall typically into these four categories:

·        Better Transparency: Users have the freedom from the operational details of the network, the replication (multiple copies of the data), or fragmentation issues in the data.

·        Increased Reliability/Availability: Because data can be distributed over many sites, one site can fail, and the data usage can continue.

·        Easier Expansion: The expansion of the system in adding more data sources, increasing data size, or adding more processors is much easier.

·        Improved Performance: A distributed DBMS can achieve interquery and intraquery parallelism by executing multiple queries at different sites by breaking a query into several subqueries that run in parallel.

Distributed Joins 

To make distributed joins scalable for high throughput workloads, it’s best to avoid data movement as much as possible. Some options for doing this are:

·        Make small and rarely updated tables that you regularly join against into reference tables, thus avoiding broadcasting these small tables around.

·        Try to choose shared key columns that are commonly joined upon regularly. This approach will promote using local joins to minimize data movement and promote parallel joins.

·        Try to restrict the number of rows in joins that cause any of the joined tables to reshuffle.

Net; Net:

Most users of SQL databases have a good understanding of the join algorithms in a single process server environment. They understand the trade-offs and uses for nested loop joins, and hash joins. Distributed join algorithms tend not to be understood and require a much different set of trade-offs to account for table data spread amongst a cluster of machines. The data movement trade-offs are key here, so designing them into the user views and the joins they imply is crucial. It was once thought that you could not cost-effectively scale distributed relational databases. Or, in other words, have a scale-out relational database. This is now possible and this type of modern database is table stakes. Modern databases are distributed-native and also combine NoSQL and SQL data access patterns, thus reducing the need for special-purpose datastores.