DDDM for investment

Satisfy your investors with data-driven decision making

The case for data-driven decision making is clear. ‘Data-led’ companies report higher revenues and productivity. Data drives personalised marketing – fuelling conversions and customer loyalty. It’s easy to see why data is reassuring for investors.

Researchers have discovered over 100 different human biases (and counting). Humans are not the rational decision makers we once thought we were. In fact, we’re often not even aware of our blind spots. No wonder that big data is being hailed as an antidote. It can augment human judgement. And prepare for questions that aren’t being asked yet.

Many venture capital firms are exploring how to use data to make better investments. So you may find that your investors are already sold on the idea. They may also be aware that companies often only use 50% of available data for decision-making. Lots of decisions are still based on gut feeling or experience. It begs the question: why is uptake still low?

Read on for how to use data to make decisions at your company. And how to overcome potential barriers.

Laying the foundation

Accurate, reliable reporting is square one. But putting it in place is often a challenge. Hurdles can include diverse data sources, quality control and resources for data processing. Not to mention the competing priorities facing most fast-growing startups.

Data quality and master data management are amongst the top concerns for businesses. In an annual BI survey, they came first for the third year running. In fact, only 35% of executives reported a high level of trust in their companies’ data.

When teams mistrust their data, they’ll ignore insights that contradict their own judgement. They’ll choose data that matches their own experience, undermining the whole exercise. In short, poor reporting reintroduces bias. Clean data is imperative.

If you want to get started, here are three first steps to consider:

Step 1. Create your data lake by centralising all data at a single location. Connect your data sources and schedule data loading according to your business requirements. Using ELT minimises the human capital needed and cost.

Step 2. Build structured data domains from your raw lake by applying business logic (This is the Transform stage of the data pipeline). It puts the data into the hands of your analysts. Adopt SQL, the universal language of data manipulation/interrogation. This ensures both speed of delivery and iteration.

Step 3. Pick your BI/visualisation layer. There are lots of options, including Tableau, Looker, Qlik and PowerBI. This layer is the front end that will generate your reports and empower analysis. Choose a tool based on the usability needs of your analysts and business.

Preparing for the future

Data infrastructure is an essential part of building a data-centric business. It’s as important as the plumbing or internet connection. Having it in place opens up new possibilities, including automation. Putting more data in the hands of your teams also allows them to drive greater value for the company.

Companies such as Amazon and Netflix have taken personalised recommendations to new heights. A ‘single view of customer’ holds the key to a good customer experience. Companies where each department has different customer data are arguably behind the times.

Other potential applications include automated general ledger workflows. This allows companies to reduce time-consuming manual processes and introduce greater standardisation. Google uses data for HR decisions, United Airlines for baggage tracking and upselling. The list goes on.

However, data-driven decision making isn’t just about IT dashboards. To be effective, it has to be accompanied by an appropriate mindset and company culture. Organisations must recognise both the value of data and its limitations. And staff need to adjust their behaviour to work well with these new systems.

Final thoughts

No employee really wants to do laborious, manual work. However, leaders may prioritise lower short-term costs, rather than investing in data infrastructure. The cost of purely human decision-making is a long-term consideration. In fact, could bias be at play? We’ll let you be the judge. One thing is for sure: data-driven decision making can free up your team for higher-value work. And reassure your investors that they’ve found the right partnership with you.

Want to know more? We’d love to chat. Please get in touch.