IT Transformation

Prometheus Applied – Knowledge’s Lever

By Sheppard Narkier December 26, 2015

Transformational Leverage

Archimedes once stated that with a big enough lever and a firm enough place to stand on, he could move the earth. Knowledge has that power, but much like Prometheus teaching man to use fire, that impact can be for good or ill. No one wants to share the fate of Prometheus be it the one from Greek Mythology or the one from the Claymation video link above.  In last week’s blog, Knowledge was revealed as the key to driving successful IT transformations.  Applying knowledge requires a balanced set of tactics, starting with what knowledge is. So this IT mythos epic will conclude as a trilogy, exploring Knowledge’s Levers.

Deconstructing Knowledge

Pervasive and Evolving

The use of knowledge is very wide ranging and in today’s lightning fast world it ages rapidly turning yesterday’s knowledge into a liability. Some EMC colleagues have suggested very impactful approaches to manipulate data in order to enable better business decision making.

Interconnected with Unmanageable Velocity

In the case of IT transformations, we add the complexity of IT and business needing to collaborate across semantic barriers and knowledge domains in order to tackle the complexities of IT transformations involving ten thousand applications. For many executives, with both time and resource pressures this is endless abyss they face in their darkest nightmares. How can we move forward by reducing technical debt while keeping the lights on?

Massive Clustering Causing Decision Inertia as much as Lack of Data Does

Suppose the answer is to use key performance indicators (KPIs) such as agility, cost, operational effectiveness, reliability. Suppose you cannot legitimately focus on just one set.  Suppose as a previous blog explored, you just focus on agility. The reality is that each project has competing driving forces, but an application portfolio of thousands of applications in chaos will test every aspect of the IT organization to its limits. You need multiple experts working in conjunction, but how can this “Tower of Babel” properly communicate. Here is another knowledge framework to consider from Financial Services:

Figure1_dimensionsofknowledge

Notice how Knowledge dimensions align to purpose, seen at the end of the dimension arrows {Logical Forms, Scope and Control, Subject Matter, Operational Force}. Knowledge follows the dictates of form and function.

When evaluating Data, Information and Knowledge, the latter is the most stable for instance books and white papers are written about Knowledge, not data.  Data science has significantly shortened the cycle to test knowledge and often creates unusual perspectives on what was assumed unassailable.

One of the major aims of creating knowledge is that the incessant streaming of new data and information can be placed into an established context, namely patterns. Patterns combine ordering and classification along with a practical action framework.  I will show one such pattern deconstruction and how it can be used to streamline the analysis of thousands of applications in portfolio management.

Knowledge’s Lever- Pattern Analysis

Deconstructing a Business Value Chain

In 1985, Michael Porter realized that most businesses in every industry exhibit similar behavioural patterns and therefore tend to invent structure to optimize that behaviour. He titles it the business value chain.

Figure_2

In the Adaptivity platform, the power of this pattern-based thinking allows practitioners to meld business needs and IT imperatives in order to make better business driven decisions. We modified this model so that we could build knowledge bases and rules that characterize the nuances of business demand. This allowed us to combine technical and business knowledge methodically.

This diagram below focuses on direct business impact, with added structure.

Figure_3

Note that the five distinct value chain functions are depicted, which includes overlays for traditional thinking about front, middle and back offices. More importantly, we have mapped the behavioural characteristics of each major part of the business value chain.  These behavioural characteristics drive the business demand, and shape the way applications are designed. They are also the key to understanding how to best approach a massive portfolio of applications that need rationalization and transformation.

The Pattern Lever- Aligning Executive needs to sift the portfolio chaos

KPIs provide a powerful focus for executives:

  • If they are fixated on Time to Market Agility then the applications that operate on Market and Client facing activities, including service get top priority. The recent surge in cloud native application migration validates this. So does a move to big data.
  • If they are fixated on Business Process Agility, then Inbound and outbound logistics are a major focus along with some key applications in Operational Transaction processing.
  • If either Agility strategy is in play, most executives consider this existential and will provide leeway on cost
  • If either Operational or Capital cost pressures are top of mind then the middle office applications will receive the focus.
  • Reliability concerns typically affect process flows involving multiple applications, but those concerns can be partitioned into one of the depicted processing segments above.

Adaptivity’s Prometheus Reboot will make this mapping easier than it has ever been.

The Knowledge Lever and the Filter

Adaptivity now features Application Classification and Alignment Services, which currently enable our EMC practitioners to sort through hundreds of apps quickly to discern likely investment strategies. The Prometheus reboot will enhance that guidance by aligning KPIs and value chain tendencies; and value chain demand characteristics mapped to application types.  All of these services will be added to make it easier for practitioner and client alike to make relevant defensible and repeatable decisions. This knowledge has been collected from decades of experience, harvesting data and information from hundreds of projects. Prometheus won’t stop there, since we know that all manner of knowledge is changing fast as the world tends towards becoming a complex adaptive system.

In a virtual world a virtual lever needs to be bigger than ever because data has gravity and the wrong decision could cost 1000x to fix in maintenance.

For more thoughts on this and other transformation topics, consider reading the book I co-authored.

About Sheppard Narkier


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