11/2/2018 7:53:46 AM
ALM data strategies that mimic the principles of blockchain
ALM Data,Application Lifecycle Management
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App Developer Magazine

ALM data strategies that mimic the principles of blockchain



Christopher Pola Christopher Pola in Enterprise Friday, November 2, 2018
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How an ALM data strategy and infrastructure centered around three blockchain principles can help achieve a more agile business, more trust around transactions, and even dovetail into machine learning, and AI.

All too often, I hear from customers about a very common pain point: they do not have the data to run their business. It’s not that they lack data, but they lack trust in their data. While solving data issues can be a riddle at times, I believe this dilemma is symptomatic of antiquated and/or misappropriated application lifecycle management (ALM) systems requiring a little more strategic thinking, a little more discipline and some plain old TLC. The pain my customers are identifying is a gap between the process and their systems. If data serves as the common denominator in the people + process + technology equation, then addressing the harmonics of how they all work together might be getting overlooked. To prevent such pains, ideally, the data technology must line up with internal processes to create a solution that will actually solve your data-trust problem and create true business agility. 
Late one evening in the office, our team of Agile Advisors huddled in a conference room discussing how to help organizations make their ALM data strategies more omnipotent. We had just finished a couple of days of client meetings and it was very evident that they all suffered from the pain of not having the right ‘data’ at different phases of their software development lifecycle (SDLC).

The need for enterprise agility becomes more imminent as technology infuses our business models with more speed and complexity. Having feedback loops and improvement cycles that span the entire organization requires a level of trust and accuracy. Without the right data infrastructure, how do you achieve that level of agility?

Achieving enterprise agility

In an effort to find a way to adequately and accurately describe this common issue, I had an epiphany. Could an ALM data strategy that was similar to the benefits of blockchain be the remedy that would alleviate the current pains customers have with their SDLC data? We know that blockchain was designed to remove the uncertainty from trading value. Said another way, the basis of blockchain is to provide trust in transacting value with other parties. All the interactions in the SDLC are about moving value through the pipeline and everyone in a company is transacting to produce ‘value,’ so can we then consider that the very benefits that blockchain provides are exactly the benefits organizations seek in their ALM data infrastructure? 

Let's kick the tires on this a bit more…When organizations develop new products, there are literally thousands, even hundreds of thousands of “transactions,” right? Think of how many conversations take place at each level of planning and with each different stakeholder group. Every agile ceremony, portfolio planning discussion, or program or team planning activity results in a transaction of sorts. A lot of trading and transacting occurs within the discovery and planning hemisphere. Add to this – if you dare – all of the activities that happen during the engineering and execution phases – the activities around source code management, pull-requests, merge/builds, CI/CD, testing, security reviews, operations. Then add in all of the corporate functions of marketing, legal, finance, education, sales, support and so on. All of these types of “transactions” take place minute by minute, day by day, week by week, etc., and if you’re not able to either a) obtain a list of all these transactions easily; b) make sense of how all these transactions are related; or c) if you do not trust this data, then how resilient and agile can your product discovery and product delivery phases actually be? (By resilient, I mean anti-fragile and an organization that can deliver better outcomes when variability is introduced). 
The point is there are a lot of transactions that need to be managed. All organizations are aware that they need data to achieve their key business objectives, but what they lack is the ability to trust their current data infrastructure and they spend money to harness, prepare, review, decipher, interpret and manage whatever data is available, yet with little improvement in the trust factor.

An ALM data infrastructure that acts like blockchain

To set this up properly, let’s revisit the earlier analogy of an ALM data infrastructure that mimics the benefits of a blockchain. A sound ALM data infrastructure would remove the need for intermediaries (manual spreadsheets, data management and collation, thereby reducing costs) and supports the flow of value, which in our world is working software and any transaction that supports the principles of agile. Establishing an ALM system that mimics the three blockchain tenets from start to finish in the SDLC  – identity, transparency and governance – can remedy the pain everyone experiences when there is a gap between your organizational-wide processes and your data. If becoming an agile business is important to you, then invest time in a data strategy and infrastructure that will be ubiquitous with the benefits that blockchain provides.

Conclusion

In summary, please do not dismiss the importance of data. Data matters, period. By virtue of how a blockchain works – linking of transactions and standardization in how the transactional data is defined – an ALM data infrastructure that employs these same principles will allow you to mature quicker on your transformation journey. This has to be said too: Don’t fear data standardization. It does not limit the autonomy or creativity of the people and processes; but rather, it enables trust around all the activities/transactions that are happening and that trust is the basis for business agility. Taking it further, an ALM data strategy and infrastructure that provides discipline around the data will help any organization make the leap into machine learning, predictive analytics, AI and what lies ahead on the technology highway.



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