Archive: Apr 2018

Fantastic day with friends at Woburn Golf Club. Huge thank you to everyone who came.

In 2017, a content creator called Oobah Butler decided that he wanted to do something with the experience he’d gained writing fake positive restaurant reviews on TripAdvisor.

What if, he wondered, he set up an entirely fictitious restaurant based in the shed in his garden and then started to manipulate TripAdvisor ratings?

What happened surpassed his wildest expectations. In just six months The Shed at Dulwich became the top-rated restaurant in London, even though nobody had ever actually eaten there, based solely on fake reviews, fake pictures and the word of mouth created by a complete inability for anybody to book a table.

It’s a tale that tells us an awful lot about the way we live now. Not least, the way in which we rely on rating systems and the Internet to tell us what we should think and do.

We routinely check TripAdvisor for our meals and hotel stays, IMDb to tell us which movies to watch and even crave the dopamine kick we get when somebody likes something we share on social media.

According to a report from online marketing firm Podium, reviews impact purchasing decisions for 93 percent of buyers, 82 percent of people now read reviews before making purchase decisions, 60 percent look at reviews on a weekly basis and if the reviews make them confident in a product or service then 68 percent of them are then willing to pay up to 15 percent more than a standard price.

This is just one part of a wider issue rooted in the increasing convergence of the digital and physical world and its ability to generate a huge amount of useful information. This process is so pervasive and based on so many data points, that it has even generated its own terminology and a number of new jobs and disciplines. Data Scientist has now been identified as the ‘best job in America’ for three years running.

Its creeping definition now incorporates a wide range of fields such as business analytics, the application of data, and good old-fashioned statistics.

In a workplace context it can range from the sort of Big Data organisations generate through the use of building sensors through to HR Analytics and the use of ratings in the supply chain.

This kind of information is obviously extremely valuable for a business. But its usefulness will depend on context and objectives. There is also a temptation to complicate issues that may be best judged with a simple binary decision between two possible outcomes.

We also have unprecedented access to the experience of our peers. Most of us commonly experience this in our day to day lives when making decisions about products and services but it’s a commonplace practice in B2B purchasing decisions too.

Google, Trustpilot, Feefo and Bazaarvoice are all commonly used B2B review sites, although Google claims an extra degree of impartiality because it does not make money directly from its reviews. Glassdoor is also important to prospective customers because they will often make a judgement about the way a firm treats its employees as a guide to its general approach to business.

Concluding, although there is a call for restrictions in the ability to create false ratings and manipulation of ratings, we must remember to never take the individual out of decision making and goal setting and remain focused on people, with all their unquantifiable preferences and behaviours.

One of the most commonly talked about issues amongst workplace professionals over the past few years has been the ability of data to transform the way we think about, plan, design and create workplaces.

Much of this debate is centred on major technological issues such as Big Data and the Internet of Things and the increasingly sophisticated approach to existing technologies such as smart building systems, booking systems and workplace sensors.

Similar trends are unfolding in the overlapping field of HR. Although HR departments have traditionally collected key information on issues such as turnover and absenteeism, the increasing convergence of the digital, physical and cultural workspace means they are more and more involved in the gathering and analysis of wider forms of data related to performance, productivity and wellbeing.

Increasingly the use of analytics in a workplace context has focused on people. A recent report from the Institute for Corporate Productivity (i4cp) called The Promising State of Human Capital Analytics, suggests that nearly 70 percent of organisations are using people-based data to drive their businesses in some way.

“Successful companies tend to be those that purposefully use data to anticipate and prepare rather than to react to daily problems,” the authors say. “The future focus of professionals in the human capital analytics field will increasingly be on using analytics to guide strategic decisions and affect organizational performance.”

In a world with masses of sophisticated data, we can forget that on certain measures, success can be defined in purely binary terms. At the very outset of an office fit-out we can provide yes or no answers to the most fundamental questions of whether the project was completed on time, to budget and with no defects.

The same approach can be extended to the outcomes of the workplace design itself because it is extremely likely that it will have been created with a series of clear objectives in mind. These are likely to include the fostering of collaborative work, wellbeing and productivity, accessibility, the user experience and the integration of technology.

At the root of all these issues is how well they create a productive environment for people, and so we are fortunate that we have a range of metrics in which to assess the performance of the workplace in this regard.

The challenges we face now are massively augmented iterations of a pair of problems that we have known about for a long time, namely what to measure and what to do with the measurements we produce.

It’s important to get this right. In a business context, most people will be aware of Peter Drucker’s famous dictum that ‘what gets measured gets managed’ but maybe less so with his idea that ‘there is nothing quite so useless as doing with great efficiency something that should not be done at all.’

There is an added complication in that we can change something merely by observing it. In quantum theory this is described as the Heisenberg Uncertainty Principle, but a similar idea is at play in working environments.

If we tell people we are measuring them by the hours they are at their desk, they will behave in one way. If we tell them instead they are to be measured on their output, they’ll behave in another.

There are lessons here for occupiers in our data rich age. Technology and data by themselves are not enough. Organisations must acquire the skills to filter and analyse data and use it to meet the right objectives and ask the right questions about what they want from their facilities, employees and working culture.

Remember it’s all about people!

The experience people have of buying products in their personal lives has had an understandable influence on their behaviours and expectations in B2B purchasing. This sets a high bar when you consider how seamlessly efficient organisations such as Amazon are in creating satisfied customers. Nevertheless, it’s a challenge that has to be accepted and it’s important to understand what lessons can be learned from B2C providers.

One of the key drivers of satisfaction lies in interactions with technology. This isn’t just about the use of specific technologies such as eProcurement platforms but also a more generalised approach to how firms interact with clients and technology. People want technology that is easy to use and intuitive. This includes the ability to learn about products and services.

There are some aspects of organisational procurement that are unique however. For example, there are logistical and compliance issues that must be taken into account, especially for sophisticated and multi-layered purchasing decisions. There is no reason why B2B transactions can’t aspire to the same levels of excellence as those in the B2C market, but they are often far more complex. In complex business transactions, there is often almost as much focus on the journey as the destination.

While an Amazon customer will be happy to order a book and have it delivered the next day, there is no interpersonal relationship involved beyond the technological interface and no need to delayer the supply chain; for example by ordering the book from Amazon and then having it delivered by a courier of your choice because you don’t trust the one Amazon uses or you think you have a better option.

By contrast, the procurement of a workplace typically involves a complex supply chain, a long decision-making process, careful selection of suppliers or a primary supplier, the choice of procurement model and so on.

Of course, the simplest route for procurement is the selection of a single trusted supplier who then manages all of the sub-contractors and suppliers and shoulders most of any risk. Ideally this will be a transparent relationship, especially when it comes to issues such as the environmental standards of everybody in the supply chain or compliance with legislation, so the important thing is to develop trust and a mutually beneficial relationship.

However, sometimes the demands can appear contradictory. End users may want to strike the right balance between short term value and long-term return on investment. They want to work with a trusted partner, who they also want to carry most or all of the risk of the project. And they want to maintain, long-term relationships with a trusted group of suppliers while maintaining freedom to choose another procurement route.

These are not insurmountable issues and they can be overcome primarily by the development of long term relationships and a focus on long term goals. Expediency may encourage organisations to take on more risk by delayering the supply chain, and that may be the right decision in the right circumstances.

Data plays an important role in decision making about the supply chain. A 2015 study from Deloitte called Business Ecosystems Come of Age identifies the ways in which complex supplier networks that focus on knowledge sharing and collaboration add more value than simple transactions. The data sharing of everybody involved in a relationship creates new insights and allows the partnership to develop for the benefit of all parties. Thus, creating a modern way in which common problems within this area can be avoided and solved.