Most companies today do not utilise external data in a systemic manner but instead focus their analyses and rigour on internal data such as company financials. The problem with such an approach is that it is very reactive. Internal data is the end-result of historical events. Running a company based on internal data such as last quarter’s financials is like driving a car looking in the rear-view mirror.
The main thesis of this book is that decision-making is up for a major overhaul and need to adjust to a new digital reality. The internet has transformed the way we communicate, get news, shop, socialize, advertise and bank. Yet, despite all these changes, corporate decision-making processes have remained surprisingly static.
In this book, a new decision-making paradigm is proposed, called Outside-Insight (OI). It is an approach focused on anticipating changes in the competitive landscape by following and analysing the ‘online breadcrumbs’ that competitors, clients, suppliers and other players in your ecosystem leave behind online.
This new approach to decision-making moves away from the old paradigm centred on inwardly Key performance Indicators (KPIs), financials, annual plans and quarterly reviews. Rigour is instead directed towards real-time analyses of external data. It is an approach that moves the focus away from what you are doing to what the industry is doing and, crucially, to understanding and anticipating changes in your market conditions in real time.
My main takeaways out of this book are:
- We are in a cusp of a big transformation when it comes to corporate decision-making. The use of online information will change the way boards are run, the way we develop strategies, the way a company’s health is measured and the way executive pay is earned. The companies with the best ability to anticipate change, and to respond accordingly, will win. Central to this will be a company’s ability to use external data and to create insights from the outside.
- While Business Intelligence (BI) is primarily focused on company-specific operational metrics, most of which are lagging performance indicators, OI is concerned with a real-time understanding of the ebb and flow of the competitive landscape in order to anticipate future threats and opportunities.
- OI is adding a new level of sophistication to the executive toolbox. With OI, executives can look beyond a company’s data and develop a real-time understanding of how the whole industry is developing. The impact of external factors can be measured and analysed, bringing Porter’s Five Forces to life in dashboards and real-time alerts.
- OI is still in its infancy. We have a lot to learn before we can harvest its full potential. There is an opportunity to take advantage of external data in a more systematic way.
- An obvious place to look for clues about what is happening inside another company is its corporate website. There you can read about big client wins, awards and other significant accomplishments. Similarly, any changes to the executive team. Companies use their website to share all the latest positive updates with their clients. In the process they are also inadvertently broadcasting that information to competitors and suppliers. So, carefully analysing the changing content on your competitors’ websites will give you a lot of valuable competitive intelligence.
- Another interesting trail of online breadcrumbs to follow is search engine marketing (SEM), or so-called pay-per-click (PPC) spending (eMarketer). Although search spend doesn’t tell the full story, it is a very interesting metric to track for most companies.
- Another commonly used metric for competitive intelligence is web traffic. Web traffic data is not easy to get hold of, but there are third-party companies such as Comscore that estimate website visits. In a similar fashion, you can use Google AdWords to see how often your company is searched. Compare this data with that of your competitors. If app downloads are important to you, a commonly used service is App Annie. Web traffic, search volume and app downloads are all measures of the level of demand of your products.
- Tracking patent data applications, credit ratings, litigation and import declarations, are important sources of online information as well. They are readily searchable in most countries.
- Mining internal data is lagging data – an obvious limitation with ERP systems is that they contain lagging data based on historical events. The figures in financial reports are the end-result of activities and investments that took place in the past. A key thesis of this book is that we need to be careful with how to use ERP software, while bearing in mind it can only answer a few of the questions we have to ask ourselves when making important decisions. History doesn’t necessarily predict the future – even less when you study your company’s internal data in isolation. You don’t get current information about what your competition is doing. You don’t get reliable information about industry trends. You create a world-view based on what you see through the lens of your historical operational efficiency.
- Being too internally focused is dangerous, given the pace with which the world is changing today. Forty percent of Fortune 500 companies in the year 2000 were gone ten years later – one of their main problem lay with fighting preconceived beliefs and breaking through internal bias (Blackberry case).
- Mining external data is looking into the future – external data is one of the biggest blind spot in corporate decision-making today. Every company has external factors that impact future business performance positively and negatively (Kodak and Instagram-Facebook case).
- Decision making will change in three key ways. First, it adds forward-looking insights from external data as critical component in the decision process. Second, decisions happen in real time, responding to critical changes in external factors. Third, companies measure their progress and plan for the future by benchmarking against their competitors.
- One of the most fascinating opportunities with external data is that you can learn as much about your competition as you can about your own company. This is an unprecedented opportunity unique to OI.
- Real time. External data offers us a real-time view of how our ecosystem and competitive landscape are evolving. Using real-time analytics, we can spot opportunities and threats much earlier than previously and act accordingly. The habit of using last quarter’s set of results in order to set the course for the following quarter does not cut anymore. Instead, external data empowers companies to adjust to events as they unfold.
- If transactional historical (internal) data shows what customers have bought in the past, social networking data has the potential to show what they may buy in the future. Board typically meet quarterly, but consumer behaviour can change tremendously in three months nowadays.
- ‘If you are not benchmarking, you are looking at a single data point in a world where a single data point has no value. The data point only gains value if you can see it in comparison to other data points and build a relation between them. I do not believe an organisation can exist without benchmarking‘ – Jan-Patrick Cap (The Global Benchmarking Network – GBN)
- Consumer sentiment about a product or service cannot be established in isolation, and opinions about other brands will need to be taken into account as brand strength is established relatively.
- KPMG study: ‘60 per cent of companies do not include external drivers of business performance in their financial forecasting models – most companies exclusively rely on internal data and ignore the external factors that drive their business‘
- Every company talks about information as an asset, but not many companies actually behave that way.
- OI is in its infancy, and as new technology develops over time, the use of OI by board and executives will increase in sophistication.
- Three steps for OI in practice: a) Understanding the competitive landscape through OI; b) Integration of OI into core internal processes; and c) Conversion to the OI paradigm.
- ERP and Business Intelligence transformed decision-making into a rigorous, data-driven approach based on all the company’s operational data. OI would extend this to all the external factors that influence a company’s future development.
- Data Science is an umbrella term for statistical and mathematical techniques used to analyse large, noisy and complex data sets such as those found on the open internet. We live in a ‘big data’ era and are drowning in data – internal and external. The nuggets of insights we want to get to can be very valuable but are often hard to extract.
In 1609 Galileo Galilei earned fame and riches by presenting to the Venice establishment a telescope that could be used to see seafaring ships two hours before they could be seen by the naked eye. The military benefits of such technology were obvious and were deployed with significant success. The benefits for a company that mines external data for forward-looking insights are equally attractive nowadays.