Buy locally, my dear Watson

Investigating the potential of an artificial intelligence that could assist midsized organisations in making smarter purchases locally.

In the pursuit to save money, some of those responsible for procurement and purchasing have hopped on the bandwagon of offshoring and taken advantage of the globalisation of suppliers, neglecting their local economies. Consumers have been making similar choices, turning away from local purchasing toward buying online. What some may deem progress, others experience as draining the life out of their local High Street.

To achieve a mix of local and global, a clearer understanding of product/service's supply chain must be available, both for consumers, and those involved in business. Imagine the day when Watson, the cognitive computer that defeated humans at the quiz show 'Jeopardy' in 2011, develops a heart. Who knows, with IBM's recently announced business unit, The Watson Group, along with its $1 billion initial investment, anything may be possible in the years ahead.

A Heart for the High Street

The High Street, a living symbol of local economy, is in trouble. What could serve as a retail hub for the local community has been displaced, in many ways, by more competitive alternatives that offer lower prices and a simple online shopping experience. This shift to online has left many storefronts vacant in the UK and is also expected to unleash a 'tsuanami' of store closings by large retailers in the USA.

An imbalance has arisen between online and physical retail experiences. It was noted in a Telegraph article which cited recent findings by the UK's Office of National Statistics: "£1 in every £10 is now spent online rather than in stores". The trend has left "one-in-seven shops on the high street empty". The Centre for Retail Research has predicted the decline will continue, with store numbers dropping by 22% by 2018. 

In a wild 'what-if' effort to figure out what can be done, we imagine the somewhat improbable benefits of a disruptive innovation built from Watson, yet with a heart for your local economy. Could it help increase the wealth and wellbeing of the community, in addition to boosting the health of the overall environment?

Could an AI really help local business?

First of all, Watson has become somewhat of a banking wizard since Citigroup began using it to decide what new products and services the bank could offer its customers (via Economist). Although, Watson is also doing some good in aiding cancer researchers at the University of Texas M. D. Anderson Cancer Center. The researchers are utilising the cognitive computer in the cloud to "fine-tune treatment plans, and assess risks" as part of the programme's mission to eliminate cancer. If Watson can assist decision-makers with the challenges of banking and reducing cancer, why couldn't it help us facilitate a positive local impact on the High Street? 

How might consumers tap into Watson's power, if not something akin to the familiar voice interface known as Siri from Apple's iPhone and iPad devices? Watson would need to answer more complicated questions than "Where can I buy milk?" If the prediction made by Carolina Milanesi, the research vice president at Gartner, comes true, by 2017, smartphones will be smarter than their users. Additionally, the vision of Bernie Meyerson, IBM's vice president of innovation, could bring us a hands-on, voice-activated Watson. He told SFGate reporter Sarah Frier that Watson could then be used by everyone:

A farmer could stand in a field and ask his phone, “When should I plant my corn?” He would get a reply in seconds, based on location data, historical trends and scientific studies.

Consider how many of us have grown accustomed to making purchasing decisions with the assistance of our mobile devices. The UK's shoppers spent 138% more using mobile devices in 2013 than in the previous year, according to research from IMRG and Capgemini (see ComputerWeekly). Certainly, some iPhone users have become accustomed to asking Apple's Siri for tips on purchasing decisions, but by in large, Siri serves most users and offers a form of touch-free search. Siri may rarely provide a direct answer, but has been found to answer relatively simple questions spoken clearly such as "What is the average price of a gallon of gasoline in Denver?" A start, but not yet what most of us are looking for.

Smarter purchasing in a complex world

“I have the advantage of knowing your habits, my dear Watson,” The Adventure of the Crooked Man, Memoirs of Sherlock Holmes, Arthur Conan Doyle  

While some have predicted that "one day soon Siri will know exactly what you want and when" (The Guardian), it seems more probable that the cognitive computing 'Ecosystem' for app developers, provided by IBM's Watson is a better model. Watson may well replace Siri, particularly when it comes to assisting with purchasing decisions. Developers could create Watson apps that tackle supply chain issues and balance the trade-offs between purchasing locally vs. globally, so that we don't have to.

Through the Watson Ecosystem's SaaS (Software-as-a-Sevice) model, The North Face utilised the API (Application Programming Interface) to provide a relatively simple eCommerce shopping assistance service. While it is limited in scope compared to what may be possible, Wired reports that the app could be asked relatively dynamic questions to give consumers comprehensive answers. For example:

A parent can ask, “What should I bring for my trip to Yosemite with my son and daughter?”, and receive tailored results for boy and girl items as well as products for parents that are suited to the specific park’s climate.

Is it possible, that by 2017, we could reach the point when AI, or as IBM calls it, 'cognitive computing', could be asked about important purchasing decisions to influence buyers to local purchasing opportunities? 

One thing is certain, something far more sophisticated than Siri will be needed, because as it stands, consumers are seeking dialogue from their digital assistants. In a recent survey by Nuance Communications, 83% of respondents said they would like digital assistants like Siri to talk back more and engage in "conversational dialogue", as an alternative to just one-way voice commands. Searching for answers involves a process of questioning and answering. Conversational voice interfaces may be the next step beyond simple search commands. Especially if these cognitive apps draw upon a full range of supply chain sensors from the Internet of Things.

Realistically speaking, what can be done now?

I asked data strategist David Pidsley to give a shot at answering this question after entertaining the challenges and possibilities outlined in this post. Here's what he had to say:

The price of a product or service is the biggest signal buyers use to make purchasing decisions. Irrational emotions also play a significant part when it comes to assessing the cost vs. benefit of a purchase. Additionally, costs which are external (i.e. invisible or ignorable except over a long time frame) to the buyer, seller and supply chain are not priced-in.

For organisations wanting to price-in the purchasing costs, otherwise borne by others (typically, taxpayers) they can introduce ways to sort and filter candidate suppliers and their products/services, beyond price alone. The choice of whose costs an organisation adopts as their own will be based in their values and objectives. Examples include excluding non-High Street suppliers or working to quotas of, for example, a minimum of 20% of expenditure value going to High Street stores. High Street biodiversity can be encouraged by preferring sole traders or long-established businesses. If you have the data to identify some differentiator, any buyer can select for or against it being something you want more of in the High Street or not. 

It's then a question of pushing data, about positive local impact of suppliers, out to your decision-makers. Business Intelligence solutions which feature search on a mobile to return data visualisation or maps to the purchaser in situ will lead to better decision making. For the procurement professional at their desk, embedded analytics in their catalogue or sourcing apps can inform them as they evaluate candidate suppliers or products/services. Whilst historical analysis of expenditure that has a positive local impact is valuable, knowledge of suppliers financial vulnerability/dependence on your purchases as well as predictive analytics are most valuable. 

In many ways using a Watson (or a Deep Blue) is taking a sledgehammer to the walnut. There is certainly a role for Watson in data mining and machine learning for advanced Analytics. However, Clarke's Third Law states that, 'Any sufficiently advanced technology is indistinguishable from magic.' Many computer and data scientist will be the last people to try to dispel business people of the idea that the things they create are magic.

Organisations who choose to look behind the curtain will see that a Business Intelligence solution can enable decision makers to get the right information before or at the point of purchasing to make decisions about what positive local impact is right for living the organisation's values and meeting their goals. It doesn't take a magical box to create a little magic.

Posted by +Dan Durrant

Cause Analytics is here to help you navigate through Business Intelligence, understand today's challenges and tomorrow's technologies.

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Image adapted from 'Dovercourt High Street' by Harwich & Dovercour.
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