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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Directions Hadoop is Moving In

Hadoop is a data system so big it is like a virtual jumbo where your PC is a flea. One of the developers named it after his kid?s toy elephant so there is no complicated acronym to stumble over. The system is actually conceptually simple. It has loads of storage capacity and an unusual way of processing data. It does not wait for big files to report in to its software. Instead, it takes the processing system to the data.

The next question is what to do with Hadoop. Perhaps the question would be better expressed as, what can we do with a wonderful opportunity that we could not do before. Certainly, Hadoop is not for storing videos when your laptop starts complaining. The interfaces are clumsy and Hadoop belongs in the realm of large organisations that have the money. Here are two examples to illustrate the point.

Hadoop in Healthcare

In the U.S., healthcare generates more than 150 gigabytes of data annually. Within this data there are important clues that online training provider DeZyre believes could lead to these solutions:

  • Personalised cancer treatments that relate to how individual genomes cause the disease to mutate uniquely
  • Intelligent online analysis of life signs (blood pressure, heart beat, breathing) in remote children?s hospitals treating multiple victims of catastrophes
  • Mining of patient information from health records, financial status and payroll data to understand how these variables impact on patient health
  • Understanding trends in healthcare claims to empower hospitals and health insurers to increase their competitive advantages.
  • New ways to prevent health insurance fraud by correlating it with claims histories, attorney costs and call centre notes.

Hadoop in Retail

The retail industry also generates a vast amount of data, due to consumer volumes and multiple touch points in the delivery funnel. Skillspeed business trainers report the following emerging trends:

  • Tracing individual consumers along the marketing trail to determine individual patterns for different demographics and understand consumers better.
  • Obtaining access to aggregated consumer feedback regarding advertising campaigns, product launches, competitor tactics and so on.
  • Staying with individual consumers as they move through retail outlets and personalising their experience by delivering contextual messages.
  • Understanding the routes that virtual shoppers follow, and adding handy popups with useful hints and tips to encourage them on.
  • Detecting trends in consumer preferences in order to forecast next season sales and stock up or down accordingly.

Where to From Here?

Big data mining is akin to deep space research in that we are exploring fresh frontiers and discovering new worlds of information. The future is as broad as our imagination.?

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Still Looking For A Way To Consolidate Excel Spreadsheets?

We use Excel spreadsheets everyday. We use them to prepare budgets and reports. We even use them when drafting plans and forecasts. With this ubiquitous office application, entering data and carrying out on-the-spot computations and analysis is quick and easy. However, when it’s time to consolidate Excel data, I won’t be surprised if you wished there was an easy way.

In fact, you were probably looking for a solution before landing on this page, right?

Because budgeting, reporting, planning, and forecasting are normally done by a group of people and not just by one individual, spreadsheets bearing the necessary data can be scattered in different folders, desktops, offices, and, in the case of really large organisations, geographical locations.

How are these data brought together? Through email attachments or by sharing folders in a local area network. Each member of the working team sends out copies of their own spreadsheets to other members, who then review them, make necessary changes, then send back to the source. The files can go back and forth until everyone is satisfied.

With each sending, sharing, and edit, business critical data gets exposed to all sorts of spreadsheet risks. Copy-paste errors, omission of a negative sign, erroneous inputs, accidental deletions, and even fraudulent manipulations can take place. And because each member can end up with multiple versions of a single spreadsheet, the chance of working on the wrong version exists.

So when all the data gets consolidated and finalised, it is possible for the end product to contain significant errors. It may not happen all the time, but it certainly can happen.

But that’s not the only disadvantage of spreadsheets. The entire process of comparing cells and sheets, copy-pasting data, linking cells, writing formulas, and specifying ranges can be very tedious, not to mention time-consuming. With spreadsheets, beating deadlines is always an almost impossible exercise.

What you need is a solution that will no longer require you to consolidate Excel spreadsheets. One that is faster, more reliable, and significantly less error-prone. Denizon has a server-based solution that has all those capabilities and much more.

With a server-based solution, all your data is stored in one place. Everyone is working on the same data source, so consolidation is fast and easy. Everyone becomes synchronised and no one has to worry about working on the wrong version.

Read more about our server-based solution

 

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