Making Click-and-Collect click

In my previous post, I introduced you to integrated e-commerce and explained why it is the right way to extend your business online. If you already have a brick-and-mortar retailing business and you’re looking to improve your online presence, you could start offering a click-and-collect service.

With click-and-collect, customers order online and then collect their merchandise from one of the retailer?s local branches. Why would they want to do that?

Apparently, there are buyers who now prefer a click-and-collect service over the delivery service of a purely online retailer. With the latter, they sometimes have to wait forever for the delivery van to arrive or contend with a missed-delivery card.

Basically, customers who want both the convenience of placing orders online and better control of their time find click-and-collect a better option.

Last December 2011, IMRG (Interactive Media in Retail Group) reported a ?significant rise in the percentage of click-and-collect e-retail sales in the 3rd quarter of 2011?. This accounted for 10.4% of all e-retail sales in that quarter. More specifically, the gain was 7.4%, which was also the strongest quarterly gain since IMRG started collecting this data.

Clearly, this particular service is gaining popularity. But how do you meet the rising demand in this area?

A click-and-collect service requires a highly synchronised ecosystem. You don’t want to have a customer order items from your online store, drive a couple of minutes from his house to your nearest outlet, only to find out that one of the items is no longer available.

This can only work if all systems involved are interconnected. Changes in the inventory in your individual outlets should reflect on your database in real time. In turn, these changes have to be reflected instantly on your online store. Conversely, once a buyer has picked items online and is already directed to a local outlet, those items have to be reserved there.

But that’s not all. Your system has to be seamless enough to support fast and reliable service. You don’t want your buyer to have to wait a long time before the items are ready for pick-up. It also has to be capable of tracking the status of ordered products, handling uncollected orders, and monitoring inventory.

By implementing an integrated e-commerce system, these won’t be the only things you?d be able to do. You can even add more value to your service. For example, you can connect to your CRM and learn more about your customers? purchase history, buying habits, and preferences.

That way, it would be easier for you to provide a faster and more convenient buying experience for them in the future.

Click-and-collect is a very promising way to increase your sales and improve customer loyalty.

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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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Saving Energy Step 3 ? Towards a Variable Energy Bill

Do you remember the days when energy was so cheap we paid the bill almost without thinking about it? Things have changed and we have the additional duty of reducing consumption to help save the planet. This is the third article in our mini-series on saving energy. It follows on from the first that explored implementing a management system, and the second listing practical things to implement on the shop floor. These open up the possibility of the variable energy bill we expand on as follows.

If ?variable energy bill? sounds strange to you, I used the unusual turn of phrase to encourage you to view things in a different light. We need to move on from the ?pie chart? mentality where we focus on the biggest numbers like materials, facilities and labour, and zoom in on energy where we can achieve similar gains faster with less pain. But first, we need to see beyond the jargon that governments and consultants love, and get to grips with the reality that we can vary our energy bill and bring cost down.

As executives we recognise this, although other pressures distract us from accepting it as a personal goal. And so we delegate it down the organisation to a level where it becomes ?another crazy management idea? we have to follow to stay out of trouble. I read somewhere that half the world?s organisations do not have energy as a defined objective to monitor in the C Suite. No wonder commerce is only pecking away at energy wastage at a rate of 1% per year.

Find out where you are ?spending energy? and relate this to your core business. If there are places where you are unable to make a connection, challenge the activity?s right to exist. Following the energy trail produces unexpected benefits because it permeates everything we do.

  • Improved product design reducing time spent in factory
  • Streamlined production schedules reducing machine run times
  • Less wear on equipment reducing costly maintenance
  • A more motivated workforce that is prouder of ?what we do?

As you achieve energy savings you can pass these on in terms of lower prices and greater market share. All this and more is possible when you focus on the variables behind your energy bill. Run the numbers. It deserves more attention than it often gets.

Uncover hidden opportunities with energy data analytics

What springs to mind when you hear the words energy data analytics? To me, I feel like energy data analytics is not my thing. Energy data analytics, however, is of great importance to any organisation or business that wants to run more efficiently, reduce costs, and increase productivity. Energy efficiency is one of the best ways to accomplish these goals.

Energy efficiency is not about investment in expensive equipment and internal reorganization. Enormous energy saving opportunities is hidden in already existing energy data. Given that nowadays, energy data can be recorded from almost any device, a lot of data is captured regularly and therefore a lot of data is readily available.

Organisations can use this data to convert their buildings’ operations from being a cost centre to a revenue centre through reduction of energy-related spending which has a significant impact on the profitability of many businesses. All this is possible through analysis and interpretation of data to predict future events with greater accuracy. Energy data analytics therefore is about using very detailed data for further analysis, and is as a consequence, a crucial aspect of any data-driven energy management plan.

The application of Data and IT could drive significant cost savings in company-owned buildings and vehicle fleets. Virtual energy audits can be performed by combining energy meter data with other basic data about a building e.g. location, to analyse and identify potential energy savings opportunities. Investment in energy dashboards can further enable companies to have an ongoing look at where energy is being consumed in their buildings, and thus predict ways to reduce usage, not to mention that energy data analytics unlock savings opportunities and help companies to understand their everyday practices and operating requirements in a much more comprehensive manner.

Using energy data analytics can enable an organisation to: determine discrepancies between baseline and actual energy data; benchmark and compare previous performance with actual energy usage. Energy data analytics also help businesses and organisations determine whether or not their Building Management System (BMS) is operating efficiently and hitting the targeted energy usage goals. They can then use this data to investigate areas for improvement or energy efficient upgrades. When energy data analytics are closely monitored, companies tend to operate more efficiently and with better control over relevant BMS data.

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