Introduction to strategic context


Tesco PLC is the largest food retailer within Great Britain
and holds the leading position within the grocery market, a share of 27.8% as
of August 2017 (see figure 1). The retail giant employs around 460,000
employees over 6,809 stores globally as of 2017, generating group sales of
£49.9bn and an operating profit of £1.28bn. 


Tesco’s governance framework is divided into a 3-tier
hierarchical structure. Operating within a wider framework allows decisions to
be made at the correct level of the business, by colleagues that are best
suited to that role. Therefore, decision making is provided through clear
direction, avoiding the creation of difficult processes, hindering progression.
(see figure 2).

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Tesco’s core
purpose is to ‘Serve Britain’s shoppers a little better every day’, this is at
the heart of all operations, ensuring prices are affordable and delivery high
quality products.  The code of conduct
ensures collaboration, working together across the business to achieve shared
success. The focus on strengthening relationships with customers and colleagues
to ensure the best possible outcome from those they do business with. The three
core values that Tesco strives to achieve are as follows;


·      No one tries harder for customers: Increase understanding and making the necessary
improvements required. Ensuring that that the tools available from consumer
insights and social media are properly utilised, thus, acting upon this to make
changes and innovating to meet demand.


·      We treat people how they want to be treated: Following a culture of trust and
respect is key to success. The recognition and rewards from performance
indicated will allow for future opportunities and further development, ensuring
consumer satisfaction is at its peak.



·      Every little help makes a big difference: Alignment of values and culture
signify the importance of working together, ensuring a more customer-focussed
approach. Therefore, aiding in the growth and expansion of the business, emerging
into new markets and regions.






Organisational analysis


Tesco’s business model is based around three pillars. This includes
customers, products and channels. They are constantly looking at reinvesting
into these areas, in the outcome of a more customer focussed approach, as a
result achieving their mission to ‘serve shoppers a little better every day’ (see
figure 3).


Business strategy


Tesco are looking to rebuild the trustworthiness of the
brand, investing in strengthening and offering a unique experience. To
differentiate through their products and services, offering quality products at
affordable prices. In addition to this they aim to simplify their systems and
deliver a consistently great service in store to improve customer experience.
Offering own-label products to become the point of differentiation, giving
customers a reason to choose Tesco as the retailer of choice.


Tesco aim to
reduce their operating costs by £1.5bn, whilst generating £9bn cash from their
operations by 2020. Opportunities include simplifying store operations,
modernising distribution and efficient procurement of goods and services (not
for resale). Improving in store service has been prioritised, recalibrating
business processes to identify opportunities to increase customer satisfaction
whilst reducing costs. In terms of logistics and distribution, the retailer has
been looking at improvements to be made in terms of stock flow and the
efficiency of the supply chain, speeding up the process of getting products to
the consumer. Generating positive cash flow and improving profitability will
require optimising working capital, allowing for improved forecasting, maximising
availability and a tighter assortment of products, reducing the amount of stock
held. Current stock ordering systems have simplified inventory management procedures
in stores. Thus, increasing the amount of stock delivered and stored on
shelves, increasing efficiency within stock management.


Tesco aim to achieve a 3.5% – 4% group margin by 2020. This
includes looking at driving growth in areas which offer sustainable
profitability. Shoppers are served through a variety of services and channels.
In order to achieve long-term profitability investments in new areas and
improving the economics of channels offers a greater mix to their customers.


Innovation has allowed Tesco to listen to what the customer
wants. Looking at broader consumer trends can drive innovation through products
and the channels through which they are sold. innovation can be seen evident
through the release of the PayQwiq digital wallet, integrating with loyalty
schemes to gain comprehensive ideas of consumer behaviour and simplifying the
checkout process.


The Club Card Program


Retailers implementation of information systems were
initially designed around a product-based cost approach, this included
maintaining profit margins and managing the cost of products. However, Tesco’s
mission and strategy did not align with the use of this type of system as they
were focussed on a more customer-centric approach. This issue was addressed
with the implementation of an enterprise wide system (CRM) known as the club
card program.


The club card program, also known as Tesco’s loyalty scheme,
seen by competitors as a method of targeting discounts and coupons was
abandoned due to unlikely profitability. Nonetheless, Tesco had realised the business
value of implementing the system. However, Tesco were unable process the influx
of data streams internally, therefore had outsourced this analysis to Dunnhumby,
a British marketing firm. A wholly owned subsidiary that specialises in mining
data from customer transactions and loyalty programs to uncover key facts about
their consumers. The three types of data analysed includes customer, sales and
market research. This analysis provides decision makers within the organisation
with valuable insights into consumer behaviour and buying habits. Dunnhumby
uses this data to create customer-driven action plans, used to strategize their
client’s business, matching operations to consumer needs. As a result, the
system gives Tesco access to multidimensional customer segmentation and
tailored communications, including
converting non-buyers. Findings had shown that new parents were not spending at
Tesco which led to the launch of the ‘Baby club’, resulting in a 24% share in the
market (Rainer et
al., 2010).


Business Intelligence


The incorporation of Artificial intelligence (AI) specifically machine
learning algorithms has allowed Tesco to manage their data lake to process
real-time data. Analysts were able to capture knowledge and the reasoning
behind it, in order to create models to aid in improved decision making. As the
retailer is heavily reliant on its physical stores, it’s imperative that
blending data through the connection of the online and physical space can help
to improve business operations. Mewbase is an open source system which allows developers
to better manage data, eliminating the need for communication with other
databases. The use of metadata allows access to real-time shopping basket
events, internet of things (IoT) sensors and supply chain stock, allowing for
more effective decision making such as, product availability for consumers and
internal stock process optimisation.  The
development and integration of this technology have allowed Tesco labs to
personalise the shopping experience for online customers, offering automatic
price drop alerts and increasing convenience through the use of AI-powered home
assistants (Google Home) for purchases. This includes ordering through voice
command as well as automatic suggestions from AI technology which spots missing
items from consumer baskets. In-store routing algorithms have allowed Tesco to
reduce the distance employees walk within stores. Optimisation of the routes
has resulted in an annual reduction of walking time by 20%, allowing the
completion of more orders, increasing productivity.  Similarly increasing efficiency for drivers
using more efficient van routes and scheduling aimed to reduce environmental impacts
(Carey, 2018).


Tesco’s use
of information systems allows them to further understand consumer needs
promoting innovation. In order to track and analyse customer information Tesco
had invested in a data warehousing system from Teradata. The data warehouse is
essentially a collection of historical data used for analysis and decision
making. Connecting with customers does not only require collecting data, but
also reaching out to customers. Therefore, using business intelligence,
specifically augmented reality (AR) technology from Krishino, allowed customers
to view products online, whilst giving a realistic in-store feel.  The integration of computers within UK stores
have also allowed consumers to view products that are not physically stocked in-
store, larger, bulkier products can be viewed from all angles, whilst Tesco
maintains efficient inventory management. Social media integration has also
been used through the development of their Facebook application which allows
users to vote on products they want to be added to price drop promotions. This
allows for direct feedback from consumers stating where they most value price
reductions, also this interaction with consumers allows for a more involved
approach connecting customers with the retailer and decision making (Stair and
Reynolds, 2015).


Tesco had realised that consumer buying preferences change regularly
depending on promotions, seasonality and special events, and must take action
in order to anticipate, predict, respond and to evaluate demand. Therefore,
ensuring that products are in the right place at the right time, available to
their customers. Tesco’s decision to partner up with IBM had allowed
researchers to develop a mobile application using AR to respond to these
challenges. Employees are able to use the application to capture what is on store
shelves, this is uploaded to a database, analysed and compared to the ideal
product arrangement. The database will return information regarding
superimposed products, revealing where the gaps lie. Tesco’s CIO Mike McNamara had
said, “improving the shopping experience for customers includes making sure
products are well stocked and easy to find, the implementation of the IBM
product will aid in improving in-store operations”. The new system will allow
for a more streamlined process, automating aspects of inventory management,
allowing employees to be more productive adding further value to the
business.  In addition, the application also
allows for shelf organisation illustrating a more presentable image, revealing
damaged or knocked over products, triggering a mobile alert to notify
employees, allowing them to rectify issues previous to becoming a barrier to
consumer satisfaction. Implementation of the technology allow Tesco to create a
more innovative and convenient consumer and retailer experience, maximising
sales and inventory maintaining a competitive advantage (Nazario, 2018).


Big Data and Predictive


Big data
analytics is an essential requirement to ensure the success of a business in
this day and age. Gathering and utilisation of consumer data is crucial. Thus,
gaining the ability to generate a wider insight, playing a major role in
decision making. Within Tesco’s eco system they are focussing upon the use of
Hadoop, an online analytical processing system (OLAP) central to their ‘data
lake’ model. This centralised cloud based repository ensures all of the company’s
data is made accessible for various departments whenever it’s needed. This methodology
has allowed the business to speed up data processing to better support
real-time modelling and forecasting, opposed to traditional methods which may
take 9-10 months to ingest relevant data. Challenges the company has faced is
ensuring that the correct data is transported to where it needs to go, e.g. the
financial department requires access to sales and forecast data and customer focussed
data would needed to be accessible through marketing.


In terms of
sales forecasting Tesco has been able to gain valuable insights modelling
trends in consumer behaviour. This includes weekly consumer buying habits, how
they shop, and individual products. Analytics and clustering have revealed
insights into the decisions consumers take when purchasing products.
In-database analytics allows for the deployment of technology where data is
stored, rather than transporting data in batches for external analytics.
Clustering allows for product predictability and behaviours. Using a
combination of historical sales and weather data, Tesco were able to use
regression testing through detailed weather forecasts received three times a
day linked with their product items and store information to reveal
correlations allowing for stock replenishment in the most efficient manner.


Tesco have
been aiming to reduce their energy bills thorough the increasing use of sensor
data optimising performance involving centrally monitoring fridge/freezer
temperatures every three seconds, revealing that temperatures were colder than
necessary, increasing expensive energy costs. The use of predictive algorithms has
also been used to determine timings for servicing or replacement parts. The
integration and encouragement of using open source technology have given Tesco
the opportunity to aid in market share retention and to uphold a competitive
advantage (Marr, 2018).





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