9 Practical Steps To Building Your Data Strategy.

Time to get rid of the smoke and mirrors! In this guide we lay out nine simple steps you should take, to make more of the data goldmine your organisation is sitting on.

Data strategy

Step 1: Defining the questions

Data is a powerful tool that can provide information to guide and back-up commercial decision making. But for it to truly support growth, data needs to be closely aligned to the goals of the business. So, the first step is to understand what key questions you want your data to answer. Involve key stakeholders from all relevant departments and come up with a list of key questions.

Some examples could be:

  • “Who are our most valuable customers?”
  • “What sales channel is performing best?”
  • “Which stores should we support with marketing?”
  • “What will my customer buy next?”
  • “What is the optimal price for our product?”
  • “Why are people returning our product?” 

Step 2: Look beyond the obvious

Real insight from data is achieved when multiple data sources are combined. This means identifying where you are currently collecting data from in your organisation and evaluating the value that could be extracted from it. It also means remembering that precious business insight can come from sources that you haven’t looked at, including social media, web analytics and product usage. It sometimes feels like the number of sources never stop growing, but there can be real gold in there. 

Step 3: Sharing is caring

In any business, there is an ecosystem of people collecting data who all need to be involved in harnessing its value. These could be in different departments, such as finance, sales, product, etc. Or they could be in the supply chain, for instance, a vendor, retailer or channel partner. By emphasising the mutual benefits of sharing and analysing different data sets, you can bring on board internal and external partners to generate wins for everyone.

Step 4: If it can’t be measured, it doesn’t exist

You need to quantify how you are going to measure the impact that investing resources in data will have on your business. Value is only really generated when the data delivers new insights that improve decision-making and improve performance. So KPIs need to be performance related, not data related. Do you want to understand customer behaviour and use this to drive loyalty, purchase or investment decisions? Then sales, customer satisfaction or loyalty should be what you aim to measure. Likewise, if it is operational improvements you seek, then look at cost or speed to market.

Step 5: Actionable insight

Actionable insight is a buzz phrase you will almost certainly have heard. It refers simply to being able to create insight from data that drives change. It’s part of a move from big data to smart data. If your data and business strategy are aligned, it is almost certain that the insights you are gathering will fuel change and improvement. The key challenge is to make sure that the relevant teams are ready to trust and act on the information being presented to them. 

Step 6: Don’t run before you can walk

Integrating large amounts of data in one go and getting it 100% spot on straightway is unrealistic. Remind yourself: harnessing your data is a marathon not a sprint. It’s best to set realistic expectations and introduce changes step-by-step. And while you’re on the journey, be mindful that providing ‘good enough’ information that’s useful for the business can win over sceptics early. Make sure this happens by starting with the best data that’s immediately available. 

Step 7: Consistency, consistency, consistency

A simple rallying cry, but one often overlooked. Make sure you agree a common set of numbers for business reports and collect data for the reports in a uniform way. This avoids confusion, stops people arguing in meetings and maintains a common agenda for everyone.

Step 8: Privacy, sensitivity and security

We believe that harnessing your data will help you see your way to new levels of profit and growth. But that doesn’t mean you should forget your legal requirements to keep personal or sensitive data safe. Leaks are costly in terms of fines and damage to reputations. Also, be sensitive to the use of data and the impact it can have. For instance, in the past retailers have used data analytics to predict due dates of pregnant women. Unfortunately, their subsequent communications revealed the pregnancy to family members (we’re sure that didn’t go down well).

Step 9: Monetisation of your data

Could your data become a profit centre in its own right? We are not talking about selling customer names and addresses but providing valuable insight to non-competitive businesses. As devices become smarter, they collect more data. For example, phone manufacturers can utilise location data for the benefit of retailers. Smart usage of data from cars could be used for the insurance industry. If your data has value to someone else, then it could provide income that can be reinvested in improving further improving your analytics, or even create a whole new revenue stream for your business.

Should we talk?

Reading this guide is just the start. Better and quicker business decisions are just around the corner. No matter what stage you are at, Ipsos Jarmany can help you to harness or better harness your data.

Starting from scratch?

We can work on your overall strategy and collect and structure data, so it can be analysed and modelled.

On the road to data enlightenment?

We can create dashboards that report the key metrics to the right people at the right time.

Approaching data black belt?

We can create advanced predictive models that will help you plan for the future.

Not sure where you are?

Talk to us to get an honest appraisal of where you can improve.