Behind every great company there's a good set of data. It is now becoming an imperative for startups and business owners to make sure their business models either leverage off or are backed up by solid data.
Gitex Startup Movement key takeaways
Last month I attended the Gitex Startup movement at the Dubai World Trade Centre. It was a pretty amazing environment to be in, surrounded by bright, innovative and entrepreneurial minds. The main theme was to connect startups with investors so it was no surprise that the topic of what do investors really want to see from early stage start ups came up as a general theme. To sum up, it was very clear that the key the prerequisites were:
Having a passionate team driven by purpose, and
A brilliant business idea backed by data .
It goes without saying, and a separate topic worthy of it's own discussion, that that the people behind an ambitious company aiming for success have to have a strong and genuine desire to solve a problem or make an impact through their business - passion meeting purpose. However the financials are one area that often gets brushed over. One angel investor, that I had a conversation with, could not emphasise enough how the business idea had to be backed by data. By the end of our talk we were chanting "backed by data, backed by data" as though we're rallying troops! Although she was at that point preaching to the converted, it was clear that she had encountered many that did not quite get this. It gave me immense joy to see that there was such a great effort being made to educate entrepreneurs about the importance of supporting a business model with solid data.
So, what does "backed by data" really mean?
It's well enough that we've established that a business idea must be backed by data, however recently I was challenged to think deeper about what this really means and how it can be implemented. I came down to these 5 key strategies:
1. Operations Driven Financial Model
The core of a financial model rests on understanding the key drivers. This means the model should reflect the key drivers of revenue, key drivers of cost and most importantly it should demonstrate the causal relationship between the costs and the revenue. The key drivers effectively represent the key operational activities, so whether revenue growth is driven by sales force headcount, by Marketing activity, by production activity or by any other driver, the model relationship must be clearly represented in the model. This will allow businesses to use the financial model as a tool to summarise activity "funnel" metrics that can be used to measure the effectiveness of the critical operational activities in meeting targets.
2. Dynamic Drivers
Drivers or assumptions should always be a dynamic element of the model. In other words they should be input cells in a model that can be changed easily to simulate the impact on profitability of various scenarios instantly. A dynamic model gives a business foresight and allows for predictions into what changes need to be done to stay on target and also serve as a great tool for quick decision making.
3. Real Meaningful Data
A financial or business model is not really "Backed by data" unless the data is researched and meaningful. With more and more companies embracing technology in their operational activities, it is becoming much easier to collect data relating to business activities.
According to BSCG, a tech research firm, 64 percent of small and medium businesses in Europe today rely on cloud-based technology. Source: The small business revolution: trends in SMB cloud adoption. Gartner, another research firm, predicts that by 2020, about a quarter of organizations in emerging regions will run their core CRM systems in the cloud, up from around 10 percent in 2012. Source: Gartner Says Modernization and Digital Transformation Projects Are Behind Growth in Enterprise Application Software Market.
In fact with SaaS and subscription based revolution, it is possible to digitise almost all business activities without any large (or even no) capital IT investments. With these possibilities its very easy for a financial model to spiral out of control. It becomes very important to include only critical drivers that have the most impact on revenue and those that are measurable, controllable, predictable and defined.
Pre-revenue or startups not yet operational are not precluded from doing this. Data can and must be thoroughly researched and substantiated. With sites like, Google Analytics and Yahoo Finance, and other online resources, that with a little investigating, can provide some insight into metrics and benchmarks from comparable firms.
4. Big data - Innovate to Dominate
This is a hot topic among corporations. Existing companies realise the value to be unlocked in analysing and monetising existing data to meet customer needs. Companies are mainly using this data to identifying ways to improve operations, customers service, product offerings and to gain strategic advantages. Emerging businesses are also becoming more customer centric and even disrupting industries by building scalable "Big Data" business models.
Businesses are challenged to find the most efficient ways to harness relevant data with limited resources. This means not just collecting as much data as possible but rather understanding the advantage that it can bring, identifying key data collections points, realising the possibilities and depth of relevant data that can be obtained, and then finding ways to maximise and automate the collection of data at those points, so that the company can keep up as the data grows.
Even with efforts to curate data, the digital world has become breeding ground for data. Companies have to adopt the most efficient processing capabilities to cope. This is where innovation and integration of innovations comes in. There are a variety of BI tools available now that are developed by top tech companies to help with techniques such as analysis, data mining and predictive modelling. A key deciding factor when investing in such tools is a classic case of the Internet of Things, where you have to consider how the solution connects with current or future IT. How can information flow be faster and more agile?
5. Data Culture
The above images sum up the biggest barrier to "Backed by data" efforts. Data-driven models and decisions are only as effective as the humans involved. So how do you avoid these communication breakdowns that can lead to costly decisions being taken? Automation of decision making, by programming business rules, is one way that is suggested by BlueYonder. However perhaps dealing with the underlying issues that lead to communication breakdowns, such lack of understanding and of interest in analysis and reporting, is more effective.
Creating a culture of data ownership and accountability can give more insight into the data. Company leaders must be able to paint the picture of how all the core operational activities impact each other and the financial model, to adopt an inclusive approach that involves all, and also to encourage a sense of ownership of the operational activities generating or affecting the data. As Benjamin Franklin said "Tell me and I forget, teach me and I may remember, involve me and I learn".
If you've managed to make it his far, I would love to get your thoughts. There's no denying that data is empowering to an organisation. What does "Backed by Data" mean to you and what strategies have worked for you?