Digital Transformation Project – Marqt

13

October

2016

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According to Berkhout (2015), a successful grocery retailer of the future operates in several channels at the same time, meaning that the retailer offers its products and services through both offline and online channels (multi-channel). Industry analysis of the Dutch grocery retail industry showed that many players have shifted from an Offline-Dominated Strategy to a more Integrated strategy in which the retailers apply a multi-channel strategy (Müller-Lankenau et. al, 2004). We have seen that one particular player, Marqt, still follows an Offline-Dominated strategy and is not planning on changing that (based on our field research). Marqt has a uniquely differentiated value proposition, offering great specialty products to niche shoppers. Additional research shows the increasing trends of customers becoming less loyal to brands and more active online, especially for the niche and long tail products (Dunson, 2016).

As the competition moves more and more towards multi-channel strategies and based on our own field research, Marqt needs to find new ways to stay competitive. Although targeted marketing has become increasingly important in most industries, the grocery retail industry has yet to catch on with this trend (video). Traditionally, marketing is aimed at the entire target group, rather than specific individuals. However, several of Marqt’s direct competitors have recently moved into the online domain. Not only limited to marketing, digitalization can impact Marqt’s business model through e-commerce, customer loyalty programs, and by creating a community through a platform mediated network among other possibilities.

The proposed solution for the abovementioned need is an online retail channel (ORC), through which the current and an extended range of products are sold. Extensive information is offered on all products and quality service is paramount for the success of the channel. By ways of a positive feedback loop, customers will be drawn to the channel for its convenience and extensiveness and data is gathered from these customers by analyzing their behavior and loyalty programs. This gives Marqt the opportunity to improve customer informedness, exploit customer segment preferences, generate higher willingness-to-pay, and apply different pricing strategies to increase customer engagement.

During the coming 3 years, this plan will be implemented according to our 5 proposed objectives. The digitalization of Marqt will cost approximately 3.5 to 10 million euro, and could break even after 6 months to 6 years. The tangible benefits are a 10 percent increase in revenue over the first three years after implementation. The intangible benefits are: increase in marketing efficiency, brand awareness, geographical reach, product range and customer satisfaction. According to our projections, the critical success factors are met for this project.

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The internet of.. cows?

6

October

2016

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The internet of things is known to connect physical devices, vehicles and even buildings to each other by using electronics to collect and exchange data. For example, I want to know whether there is any milk left in the fridge, but I don’t want to open the door because that would mean the fridge needs to consume a little energy to cool it to the temperature it was before and we should all play our part in saving the planet. Samsung has a fridge that shows you whether or not you have any milk left in your fridge via a display on the door of your fridge.

Now, interesting as this may be, making an electronic device smart has been done for quiet some while now, but the guys over at Connecterra took it one step further. They developed the first ‘Dairy Monitor’ which is a which is a sensor cube attached to the neck of a dairy animal. This device enables customers to monitor animal health by tracking animal movements. Next to the hardware, the company offers software in the form of a cloud based analytics platform. Rather than just raw data, the Connecterra claims to provide the customer with insights in how to increase animal health and by that increasing productivity. One of the strong points of the platform is the data from multiple sources. Rather than just the insights from one herd from a single farm, the platform gathers the data on all customers’ farms, inducing a positive feedback loop. More data means better functionality, which should attract more customers who provide more data and the circle is complete.

The author is no expert on cow behaviour, but at the time of writing not much research can be found on the relation between cow movement and dairy productivity. And the website of Connecterra doesn’t offer any insights in the way this works neither. This means Connecterra can break new ground on productivity in the dairy productivity field of research, but at the same time, it could be a great risk to bet on a causal relationship without any scientific evidence. Either way, I cannot wait for the day that I can check my refrigerator on how far my cow grazed around for my bottle of milk.

Sources:

Connecterra: Internet of Things – Dairy Activity Monitor – Home Page

http://mashable.com/2016/01/05/samsung-fridge-amazon-alexa/#JYAjYZcSgkqo

Connecterra, ‘Fitbit voor koeien’, haalt 1,8 miljoen dollar op

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Autopilot, what’s the hold up?

2

October

2016

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Technology has come a long way for automobiles and the next era is about to commence. The autopilot phenomenon, where the driver is not the driver anymore, has been a very controversial topic as of lately. Fatal crashes with self-driving capable cars from manufacturer Tesla, who have been one of the first to offer and promote the autopilot function, have raised questions about whether the function should already be available. Can we completely entrust our cars, more precisely the makers of our cars, with our safety on the road or should we be more cautious?

To better see where we stand on driverless cars, it is important to know how technology is replacing the driver. Autonomous cars are equipped with an entire arsenal of cameras and sensors to provide a 360 view of the surrounding area. The sensors reach goes as far as 5 meters, after which a satellite provides further information.  They work together to accurately pin-point other cars, other objects, lane marking and traffic signs which the car takes into account when maneuvering across the road. With this information, at the current level of automatization, while driving the car can: steer within a lane, change lanes, manage the speed of the car and brake by itself. Wonderful attributes and it can certainly be beneficial, but hardly as operational as a true self-driving car should be.

The problem lies in the enormous amount of variables influencing the needs of the system. The cars’ autonomous driving is based on artificial intelligence which control the car based on the input of the sensors, cameras and satellites. Unlike what most think, autonomous driving is not a matter of IF – THEN statements. Machine learning based on constantly updated data lies at the basis of how these cars function. Google has for example made over 2 million kilometers on public roads in test drives to gather actual scenarios for the car to learn from. Unlike simple functions like parking and keeping distance to the car in front on the highway, a truly autonomous mode can have no margin for error and should be functioning to perfection from the moment it is made available.

One way to limit the amount of scenarios an autonomous vehicle needs to be able to handle is to control the environment the vehicle operates in. For instance, pre-defined routes clear of any traffic or unknown objects, limited speed and a relatively small set of data needed to control the car can all greatly benefit the success of an autonomous vehicle. The shuttle service at Kralingse Zoom metro station is a prime example. The input needed to drive these vehicles is not changing, at least not nothing that can be controlled for in most of the cases, which takes away the need for these vehicles to constantly learn. This example gives away where the market for autonomous vehicles will focus on in the near future, which will not be the consumer. Businesses can better control their fleet than a bunch of consumers can, they can run pre-destined routes which limits possible scenarios and can make their fleet learn from itself. Daimler AG for example already demonstrated tests on public roads with self-driving buses and ‘caravans’ of autonomous trucks.

Autonomous driving technology has come a long way over the past decade, and in certain situations some cars offer their driver the opportunity to sit back and relax while they’ll do the work. However, the number of situations where this is possible are thus limited that speaking of an autopilot function might be premature. Manufacturers and tech companies are working hard to make advances and this is shown in the field by innovations from Tesla and Mercedes for example, but keep your hands on the wheel for now.

 

Sources:

http://www.techinsider.io/how-teslas-autopilot-works-2016-7/#to-activate-autopilot-you-simply-pull-the-cruise-control-stalk-towards-you-twice-and-the-car-will-take-over-steering-5

www.driverless-future.com

 

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