How DevOps oils the Value Chain

DevOps ? a clipped compound of development and operations – is a way of working whereby software developers are in a team with project beneficiaries. A client centred approach extends the project plan to include the life cycle of the product or service, for which the software is developed.

We can then no longer speak of a software project for say Joe?s Accounting App. The software has no intrinsic value of its own. It follows that the software engineers are building an accounting app product. This is a small, crucially important distinction, because they are no longer in a silo with different business interests.

To take the analogy further, the developers are no longer contractors possibly trying to stretch out the process. They are members of Joe?s accounting company, and they are just as keen to get to market fast as Joe is to start earning income. DevOps uses this synergy to achieve the overarching business goal.

A Brief Introduction to OpsDev

You can skip this section if you already read this article. If not then you need to know that DevOps is a culture, not a working method. The three ?members? are the software developers, the beneficiaries, and a quality control mechanism. The developers break their task into smaller chunks instead of releasing the code to quality control as a single batch. As a result, the review process happens contiguously along these simplified lines.

Code QC Test ? ? ?
? Code QC Test ? ?
? ? Code QC Test ?
? ? ? Code QC Test
Colour Key Developers Quality Control Beneficiary

This is a marked improvement over the previously cumbersome method below.

Write the Code ? Test the Code ? Use the Code
? Evaluate, Schedule for Next Review ?

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

The Key Role that Application Program Interfaces Play

Application Program Interfaces, or API?s for short, are building blocks for software applications. Using proprietary software-bridges speeds this process up. A good example would be the PayPal applications that we find on so many websites today. API?s are not just for commercial sites, and they can reduce costs and improve efficiency considerably.

The following diagram courtesy of TIBCO illustrates how second-party applications integrate with PayPal architecture via an API fa?ade.

Working quickly and releasing smaller amounts of code means the OpsDev team learns quickly from mistakes, and should come to product release ahead of any competitor using the older, more linear method. The shared method of working releases huge resources in terms of user experience and in-line QC practices. Instead of being in a silo working on its own, development finds it has a richer brief and more support from being ?on the same side of the organisation?.

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The DevOps Revolution Continues ?

We close with some important insights from an interview with Jim Stoneham. He was general manager of the Yahoo Communities business unit, at the time Flickr became a part. ?Flickr was a codebase,? Jim recalls, ?that evolved to operate at high scale over 7 years – and continuing to scale while adding and refining features was no small challenge. During this transition, it was a huge advantage that there was such an integrated dev and ops team?

The ?maturity model? as engineers refer to DevOps status currently, enables developers to learn faster, and deploy upgrades ahead of their competitors. This means the client reaches and exceeds break-even sooner. DevOps lubricates the value chain so companies add value to a product faster. One reason it worked so well with Flickr, was the immense trust between Dev and Ops, and that is a lesson we should learn.

?We transformed from a team of employees to a team of owners. When you move at that speed, and are looking at the numbers and the results daily, your investment level radically changes. This just can’t happen in teams that release quarterly, and it’s difficult even with monthly cycles.? (Jim Stoneham)

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Introduction to Matrix Management

A leader is responsible to empower his people and get the best out of them. Yet an organisational structure can either help or hamper performance. Worst, it can make or break success.

Looking at the fast-changing world of the global economy, whatsoever slows up and obstructs decision-making is a challenge. Hierarchical management is rather unattractive and functional silos are unlikable. Instead, employees desire to create teams equipped with flexibility, cooperation and coordination.

Recognising that companies have both vertical and horizontal chains of command, the matrix model is created. The concept of this principle lies in the ability to manage the collaboration of people across various functions and achieve strategic objectives through key projects.

Consider this scenario:

Ian is a sales executive of a company. His role is to sell a new product under the supervision of a product manager. The manager is expert about the product and she is accountable to coordinate the people across the organisation, making sure the product is achieved.

Moreover, Ian also reports to the sales manager who oversees his overall performance, monitors his pay and benefits and guides his personal development.

Complicated it may seem but this set-up is common to companies that seek to maximise the effect of expert product managers, without compromising the function of the staffing overhead in control of the organisation. This is a successful approach to management known as Matrix Management.

Matrix Management Defined

Matrix management is a type of organisational management wherein employees of similar skills are shared for work assignments. Simply stated, it is a structure in which the workforce reports to multiple managers of different roles.

For example, a team of engineers work under the supervision of their department head, which is the engineering manager. However, the same people from the engineering department may be assigned to other projects where they report to the project manager. Thus, while working on a designated project, each engineer has to work under various managers to accomplish the job.

Historical Background

Although some critics say that matrix management was first adopted in the Second World War, its origins can be traced more reliably to the US space programme of the 1960’s when President Kennedy has drawn his vision of putting a man on the moon. In order to accomplish the objective, NASA revolutionised its approach on the project leading to the consequent birth of ?matrix organisation?. This strategic method facilitated the energy, creativity and decision-making to triumph the grand vision.

In the 1970’s, matrix organisation received huge attention as the only new form of organisation in the twentieth century. In fact it was applied by Digital Equipment, Xerox, and Citibank. Despite its initial success, the enthusiasm of corporations with regards to matrix organisation declined in the 1980’s, largely because it was complex.

Furthermore, the drive for motivating people to work creatively and flexibly has only strengthened. And by the 1990’s, the evolution of matrix management geared towards creation and empowerment of virtual teams that focused on customer service and speedy delivery.

Although all forms of matrix has loopholes and flaws, research says that until today, matrix management is still the leading approach used by companies to achieve organisational goals.

Which KPI?s to Use in CRM

Customer relationship management emerged in the 1980?s in the form of database marketing. In those tranquil pre-social media days, the possibility of ?managing? clients may have been a possibility although Twitter and Facebook took care of that. Modern managers face a more dynamic environment. If you are one, then what are the trends you should be monitoring yourself (as opposed to leaving it to others).

If you want to drip feed plants, you have to keep the flow of liquid regular. The same applies to drip-feed marketing. Customers are fickle dare we say forgetful. Denizon recommends you monitor each department in terms of Relationship Freshness. When were the people on your list last contacted, and what ensued from this?

Next up comes the Quality of Engagements that follow from these efforts. How often do your leads respond at all, and how many interfaces does it take to coax them into a decision? You need to relate this to response blocks and unsubscribes. After a while you will recognise the tipping point where it is pointless to continue.

Response Times relate closely to this. If your marketing people are hot then they should get a fast response to sales calls, email shots and live chats. It is essential to get back to the lead again as soon as possible. You are not the only company your customers are speaking too. Fortune belongs to the fast and fearless.

The purpose of marketing is to achieve Conversions, not generate data for the sake of it. You are paying for these interactions and should be getting more than page views. You need to drill down by department on this one too. If one team is outperforming another consider investing in interactive training.

Finally Funnel Drop-Off Rate. Funnel analysis identifies the points at which fish fall off the hook and seeks to understand why this is happening. If people click your links, make enquiries and then drift away, you have a different set of issues as opposed to if they do not respond at all.

You should be able to pull most of this information off your CRM system if it is half-decent, although you may need to trigger a few options and re orientate reporting by your people in the field. When you have your big data lined up speak to us. We have a range of data analysts brimming over with fresh ideas.

Migrating from CRM to Big Data

Big data moved to centre stage from being just another fad, and is being punted as the latest cure-all for information woes. It may well be, although like all transitions there are pitfalls. Denizon decided to highlight the major ones in the hope of fostering better understanding of what is involved.

Accurate data and interpretation of it have become increasingly critical. Ideas Laboratory reports that 84% of managers regard understanding their clients and predicting market trends essential, with accelerating demand for data savvy people the inevitable result. However Inc 5000 thinks many of them may have little idea of where to start. We should apply the lessons learned from when we implemented CRM because the dynamics are similar.

Be More Results Oriented

Denizon believes the key is focusing on the results we expect from Big Data first. Only then is it appropriate to apply our minds to the technology. By working the other way round we may end up with less than optimum solutions. We should understand the differences between options before committing to a choice, because it is expensive to switch software platforms in midstream. data lakes, hadoop, nosql, and graph databases all have their places, provided the solution you buy is scalable.

Clean Up Data First

The golden rule is not to automate anything before you understand it. Know the origin of your data, and if this is not reliable clean it up before you automate it. Big Data projects fail when executives become so enthused by results that they forget to ask themselves, ?Does this make sense in terms of what I expected??

Beware First Impressions

Big Data is just that. Many bits of information aggregated into averages and summaries. It does not make recommendations. It only prompts questions and what-if?s. Overlooking the need for the analytics that must follow can have you blindly relying on algorithms while setting your business sense aside.

Hire the Best Brains

Big Data?s competitive advantage depends on what human minds make with the processed information it spits out. This means tracing and affording creative talent able to make the shift from reactive analytics to proactive interaction with the data, and the customer decisions behind it.

If this provides a d?j? vu moment then you are not alone. Every iteration of the software revolution has seen vendors selling while the fish were running, and buyers clamouring for the opportunity. Decide what you want out first, use clean data, beware first impressions and get your analytics right. Then you are on the way to migrating successfully from CRM to Big Data.

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