Shared Services ? Are They A Good Idea

Things happen fast in business and we need to stay on top. It does not seem long ago that some enterprises were still hands-on traders or artisans with a few youngsters to help out. People like that did not do admin and their accounting was a matter of making sure there was enough money in the jar.

When Wal-Mart’s Sam Walton took over his first shop in 1945 things had moved on from there, although he did still deal directly with his customers. When he died his legacy was 380,000 jobs, and a business larger than most economies. So there?s plenty we can learn from how he grew his business.

One of Sam?s secrets was his capacity to centralise what needed gathering together, while empowering store managers to think independently when it came to local conditions. His regional warehouses had individual outlets clustered around them within one day?s drive each. This shared service eliminated 90% of safety stock and released capital for expansion.

Wal-Mart took sharing services a step further in February 2006, when it centralised accounts payable, accounts receivable, general accounting and human resources administration at Wal-Mart Stores and Sam?s Clubs in the U.S. and Puerto Rico. The objective was to bring costs down, while allowing local managers more time to focus on their business plans and other initiatives. As a further spin-off, Wal-Mart was able to integrate its data on a single SAP platform and eliminate significant roadblocks.

This is an excellent example of sharing services by creating own centres of excellence.? Of course, this is not the only business possibility. Other corporates have successfully completely outsourced their support activities, and Wal-Mart has no doubt had a variety of similar offers too. But, is the Wal-Mart picture entirely rosy, or is there a catch?

The Association of Chartered Certified Accountants has indicated that top talent may be the loser globally. This is because the Wal-Mart model removes many challenges through standardisation, and offers less scope for internal promotion as a result. Language and cultural differences may also have a long-term detrimental effect on the way the departments work well together.

Local outsourcing ? this is the business model where several firms engage a shared service provider independently- may hence prove to be a more malleable option for smaller companies. It often makes more sense to hunt down made-to-order services. Offerings such as the professional support we offer on this site.

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EcoVaro ? ESOS Solution on a Cloud

The UK?s Energy Saving Opportunity Scheme ? and all others in the EU stable – is bound to generate huge quantities of data beyond the reach of processing on standalone computers. This leaves some companies in the mandatory sector between a rock and a hard place. They already have to divert scarce talent to draft compliance reports. Now they face purchasing equipment with big data processing power.

The more astute are turning to cloud computing solutions like EcoVaro in increasing numbers. They are also keen to benefit from remote secure backup. .

Increasing migration to public clouds has caused a growth in niche big data consultants. EcoVaro is one of these. We want to do more than simply open up a port and leave you to become familiar with our technology. We service a growing group of companies who want us to analyse their energy usage reports, and isolate the main demand drivers so they know where to start saving.

We are consumer-centric energy consultants with the emphasis on corporates and sme?s. We offer more than just big data processing facilities. We also help set up your dashboard and are full of practical ideas you can use to start trimming energy costs right away. So please treat us as your affordable energy partner who really wants to help.

Finally, contact EcoVaro for a discussion.

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Finding the Best Structure for Your Enterprise Development Team

An enterprise development team is a small group of dedicated specialists. They may focus on a new business project such as an IoT solution. Members of microteams cooperate with ideas while functioning semi-independently. These self-managing specialists are scarce in the job market. Thus, they are a relatively expensive resource and we must optimise their role.

Organisation?Size and Enterprise Development Team Structure

Organisation structure depends on the size of the business and the industry in which it functions. An enterprise development team for a micro business may be a few freelancers burning candles at both ends. While a large corporate may have a herd of full-timers with their own building. Most IoT solutions are born out of the efforts of microteams.

In this regard, Bill Gates and Mark Zuckerberg blazed the trail with Microsoft and Facebook. They were both college students at the time, and both abandoned their business studies to follow their dreams. There is a strong case for liberating developers from top-down structures, and keeping management and initiative at arm?s length.

The Case for Separating Microteams from the?Organisation

Microsoft Corporation went on to become a massive corporate, with 114,000 employees, and its founder Bill Gates arguably one of the richest people in the world. Yet even it admits there are limitations to size. In Chapter 2 of its Visual Studio 6.0 program it says,

‘today’s component-based enterprise applications are different from traditional business applications in many ways. To build them successfully, you need not only new programming tools and architectures, but also new development and project management strategies.?

Microsoft goes on to confirm that traditional, top-down structures are inappropriate for component-based systems such as IoT solutions. We have moved on from ?monolithic, self-contained, standalone systems,? it says, ?where these worked relatively well.?

Microsoft’s model for enterprise development teams envisages individual members dedicated to one or more specific roles as follows:

  • Product Manager ? owns the vision statement and communicates progress
  • Program Manager ? owns the application specification and coordinates
  • Developer ? delivers a functional, fully-complying solution to specification
  • Quality Assurer ? verifies that the design complies with the specification
  • User Educator ? develops and publishes online and printed documentation
  • Logistics Planner ? ensures smooth rollout and deployment of the solution

Three Broad Structures for Microteams working on IoT Solutions

The organisation structure of an enterprise development team should also mirror the size of the business, and the industry in which it functions. While a large one may manage small microteams of employee specialists successfully, it will have to ring-fence them to preserve them from bureaucratic influence. A medium-size organisation may call in a ?big six? consultancy on a project basis. However, an independently sourced micro-team is the solution for a small business with say up to 100 employees.

The Case for Freelancing Individuals versus Functional Microteams

While it may be doable to source a virtual enterprise development team on a contracting portal, a fair amount of management input may be necessary before they weld into a well-oiled team. Remember, members of a micro-team must cooperate with ideas while functioning semi-independently. The spirit of cooperation takes time to incubate, and then grow.

This is the argument, briefly, for outsourcing your IoT project, and bringing in a professional, fully integrated micro-team to do the job quickly, and effectively. We can lay on whatever combination you require of project managers, program managers, developers, quality assurers, user educators, and logistic planners. We will manage the micro-team, the process, and the success of the project on your behalf while you get on running your business, which is what you do best.

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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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