How DevOps Could Change Your Business

Henry Ford turned the U.S. auto industry on its head when he introduced the idea of prefabricating components at remote sites, and then putting them together on a production line. Despite many industries following suit, software lagged behind until 2008, when Andrew Clay Shafer and Patrick Debois told the Agile Conference there was a better way to develop code:
– Write the Code
– Test the Code
– Use the Code
– Evaluate, Schedule for Next Review

The term ?DevOps? is short for Development and Operations. It first appeared in Belgium, where developers refined Shafer and Depois? ideas. Since then, DevOps became a counter movement against the belief that software development is a linear process and has largely overwhelmed it.

DevOps – A Better Way

DevOps emerged at an exciting time in the IT industry, with new technology benefiting from a faster internet. However, the 2008 world recession was also beginning to bite. Developers scampered to lower their human resource costs and get to market sooner.

The DevOps method enabled them to colloborate across organizational boundaries and work together to write, quality assure and performance test each piece of code produced in parallel.
DevOps? greater time-efficiency got them to market sooner and helped them steal a march on the competition.

There are many advantages to DevOps when we work in this collaborative way. Cooperation improves relationships between developers, quality assurers and end users. This helps ensure a better understanding of the other drivers and a more time-effective product.

Summary of DevOps Objectives

DevOps spans the entire delivery pipeline, and increases the frequency with which progress is reviewed, and updates are deployed. The benefits of this include:

? Faster time to market and implementation

? Lower failure rate of new releases

? Shortened lead time for bug fixes and updates

The Psycho-Social Implications of DevOps

DevOps drills through organization borders and traditional work roles. Participants must welcome change and take on board new skills. Its interdepartmental approach requires closer collaboration across structural boundaries and greater focus on overarching business goals.

Outsourcing the detail to freelancers on the Internet adds a further layer of opportunity. Cultures and time zones vary, requiring advanced project management skills. Although cloud-based project management software provides adequate tools, it needs an astute mind to build teams that are never going to meet.

The DevOps movement is thus primarily a culture changer, where parties to a project accept the good intentions of their collaborators, while perhaps tactfully proposing alternatives. There is more to accepting a culture than using a new tool. We have to blend different ways of thinking together. We conclude by discussing three different methods to achieve this.

Three Ways to Deploy DevOps in your?Organisation

If you foresee regular DevOps-based projects, consider running your entire organisation through an awareness program to redirect thinking. This will help non-participants understand why DevOps members may be ?off limits? when they are occupied with project work. Outsourcing tasks to contracting freelancers can mitigate this effect.

There are three implementation models associated with DevOps although these are not mutually exclusive.

? Use systems thinking. Adopt DevOps as company culture and apply it to every change regardless of whether the process is digital, or not

? Drive the process via increased understanding and feedback from key receivers. Allow this to auto-generate participative DevOps projects

? Adopt a continuous improvement culture. DevOps is not only for mega upgrades. Feedback between role players is paramount for success everywhere we go.

You can use the DevOps concept everywhere you go and whenever you need a bridge to better understanding of new ideas. We diminish DevOps when we restrict its usefulness to the vital role it plays in software development. The philosophy behind it belongs in every business.

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A Definitive List of the Business Benefits of Cloud Computing ? Part 4

Lowers cost of analytics

Big data and business intelligence (BI) have become the bywords in the current global economy. As consumers today browse, buy, communicate, use their gadgets, and interact on social networks, they leave in their trail a whole lot of data that can serve as a goldmine of information organisations can glean from. With such information at the disposal of or easily obtainable by businesses, you can expect that big data solutions will be at the forefront of these organisations’ efforts to create value for the customer and gain advantage over competitors.

Research firm Gartner’s latest survey of CIOs which included 2,300 respondents from 44 countries revealed that the three top priority investments for 2012 to 2015 as rated by the CIOs surveyed are Analytics and Business Intelligence, Mobile Technologies, and Cloud Computing. In addition, Gartner predicts that about $232 million in IT spending until 2016 will be driven by big data. This is a clear indication that the intelligent use of data is going to be a defining factor in most organisations.

Yet while big data offers a lot of growth opportunities for enterprises, there remains a big question on the capability of businesses to leverage on the available data. Do they have the means to deploy the required storage, computing resources, and analytical software needed to capture value from the rapidly increasing torrent of data?

Without the appropriate analytics and BI tools, raw data will remain as it is – a potential source of valuable information but always unutilised. Only when they can take the time, complexity and expense out of processing huge datasets obtained from customers, employees, consumers in general, and sensor-embedded products can businesses hope to fully harness the power of information.

So where does the cloud fit into all these?

Access to analytics and BI solutions have all too often been limited to large corporations, and within these organisations, a few business analysts and key executives. But that could quickly become a thing of the past because the cloud can now provide exactly what big data analytics requires – the ability to draw on large amounts of data and massive computing power – at a fraction of the cost and complexity these resources once entailed.

At their end, cloud service providers already deal with the storage, hardware, software, networking and security requirements needed for BI, with the resources available on an on-demand, pay-as-you-go approach. In doing so, they make analytics and access to relevant information simplified, and therefore more ubiquitous in the long run.

As the amount of data continues to grow exponentially on a daily basis, sophisticated analytics will be a priority IT technology across all industries, with organisations scrambling to find impactful insights from big data. Cloud-based services ensure that both small and large companies can benefit from the significantly reduced costs of BI solutions as well as the quick delivery of information, allowing for precise and insightful analytics as close to real time as possible.

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Spreadsheet Reporting – No Room in Your Company in an Age of Business Intelligence

It doesn’t take a genius to understand why spreadsheet reporting still pervades the enterprise despite the rise of a complex but highly effective IT solution known to big shot CIOs as Business Intelligence or BI.

If you’re still in the dark as to what BI is, don’t worry because we?ll enlighten you shortly.

Business decisions from disparate data sources

In the meantime, let’s talk about how you make business decisions. If you’re a top executive, then you make decisions based largely on reports submitted to you by your managers, department heads, and so on. They in turn obtain information from different sources, like the company ERP and CRM as well as other external sources (e.g. market surveys).

Now, before their reports ever reach your desk, a lot of data is extracted, shared, filtered, analysed, consolidated, and summarised so that they become actionable information. In all these activities, one software tool gets to take part in most of the action – the spreadsheet.

The problem with spreadsheet reporting

The problem with spreadsheets is that they have very poor built-in controls. Thus, they are susceptible to human errors and are vulnerable to fraud. What’s more, collecting data and manually consolidating them into spreadsheets can be very laborious and time consuming.

If you don’t get accurate, reliable information, your judgement will be fuzzy and your business decisions compromised. In addition, if you don’t receive the information you need on time, your business will constantly be at risk of breaching critical thresholds, which may even force it to spin out of control.

Business Intelligence – actionable information on time

This is mainly the reason why large companies implement Business Intelligence systems. BI systems are equipped with built-in features like reports, dashboards, and alerts.

Reports consolidate data and present them in a consistent format composed of intuitive text, graphs, and charts. The main purpose of having a consistent format is so that you will know what kind of information to expect and how the information is arranged. That way, you don’t waste time searching or making heads or tails out of the data in front of you.

Dashboards, on the other hand, present information through visual representations composed of graphs and gauges that are aimed at tracking your business metrics and goals. The main function of dashboards is to feed you with actionable information at a glance.

Finally, alerts keep you informed when certain conditions are met or critical thresholds are breached. Because their main purpose is to prompt you at the soonest possible time wherever you are, a typical alert can come in the form of an SMS message or an email.

As you can see, all three features are designed to get you making well-informed decisions as quickly as possible.

The problem with Business Intelligence and the alternative solution

The usual problem with full BI systems is that they can be very costly. Hence, if your organisation does end up implementing one, chances are, not everyone under you will be able to access it. As a result, some departments will be forced to go back to using spreadsheets.

If your company cannot afford a full BI system, then that probably means you don’t need one. What you need is a more affordable alternative. There are actually Software as a Service (SaaS) Business Intelligence solutions that may not be as comprehensive as a full BI system, but which may suffice for small and mid-sized businesses.

The disadvantages of spreadsheets are more damaging than you could have ever expected. Be free of it now.

 

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Using Pull Systems to Optimise Work Flows in Call Centres

When call centres emerged towards the end of the 20th century, they deserved their name ?the sweatshops of the nineties?. A new brand of low-paid workers crammed into tiny cubicles to interact with consumers who were still trying to understand the system. Supervisors followed ?scientific management? principles aimed at maximising call-agent activity. When there was sudden surge in incoming calls, systems and customer care fell over.

The flow is nowadays in the opposite direction. Systems borrowed from manufacturing like Kanban, Pull, and Levelling are in place enabling a more customer-oriented approach. In this short article, our focus is on Pull Systems. We discuss what are they, and how they can make modern call centres even better for both sets of stakeholders.

Pull Systems from a Manufacturing Perspective

Manufacturing has traditionally been push-based. Sums are done, demand predicted, raw materials ordered and the machines turned on. Manufacturers send out representatives to obtain orders and push out stock. If the sums turn out wrong inventories rise, and stock holding costs increase. The consumer is on the receiving end again and the accountant is irritable all day long.

Just-in-time thinking has evolved a pull-based approach to manufacturing. This limits inventories to anticipated demand in the time it takes to manufacture more, plus a cushion as a trigger. When the cushion is gone, demand-pull spurs the factory into action. This approach brings us closer to only making what we can sell. The consumer benefits from a lower price and the accountant smiles again.

Are Pull Systems Possible in Dual Call Centres

There are many comments in the public domain regarding the practicality of using lean pull systems to regulate call centre workflow. Critics point to the practical impossibility of limiting the number of incoming callers. They believe a call centre must answer all inbound calls within a target period, or lose its clients to the competition.

In this world-view customers are often the losers. At peak times, operators can seem keen to shrug them off with canned answers. When things are quiet, they languidly explain things to keep their occupancy levels high. But this is not the end of the discussion, because modern call centres do more than just take inbound calls.

Using the Pull System Approach in Dual Call Centres

Most call centre support-desks originally focused are handling technical queries on behalf of a number of clients. When these clients? customers called in, their staff used operator?s guides to help them answer specific queries. Financial models?determined staffing levels and the number of ?man-hours? available daily. Using a manufacturing analogy, they used a push-approach to decide the amount of effort they were going to put out, and that is where they planted their standard.

Since these early 1990 days, advanced telephony on the internet has empowered call centres to provide additional remote services in any country with these networks. They have added sales and marketing to their business models, and increased their revenue through commissions. They have control over activity levels in this part of their business. They have the power to decide how many calls they are going to make, and within reason when they are going to make them.

This dichotomy of being passive regarding incoming traffic on the one hand, and having active control over outgoing calls on the other, opens up the possibility of a partly pull-based lean approach to call centre operation. In this model, a switching mechanism moves dual trained operators between call centre duties and marketing activities, as required by the volume of call centre traffic, thus making a pull system viable in dual call centres.

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