7 risks to your data strategy

Business Intelligence (BI), the digitalised process of collecting and analysing data, is a driver for growth in every industry. Understand the risks by asking seven key questions of your business.

Effective BI implementation enables companies to accelerate through the innovation loop of experimentation, measurement and learning, and keep pace with technological change.

Research into the State of Technology at UK SMEs  reported that increasing use of data and insights was a top three business priority. On the other side of the coin, one of the biggest technology concerns for SMEs was data management. 

BI initiatives are gaining traction, yet many businesses fail to implement them successfully. So where do they go wrong? There are common pitfalls.  Here are the questions you need to ask of your business to make sure you do it right. 

1. Are all our stakeholders bought in?

BI is a tool for the whole business not an IT or data project for a core team. Every successful BI initiative starts with the education of key users at all levels of the business, so they understand how they can use it to be more effective.

Without this your BI implementation will be under-valued, under-used and ultimately, it won’t deliver.

2. Am I asking the right questions, aligned to my business strategy?

If you’re not asking the right questions, you won't get the answers you need. Get senior leaders on board to define the key performance indicators (KPIs) and ensure they are aligned to your business strategy.

A retailer might ask, ‘How many sales did product X get?’ But when you can also see and compare individual shop's product placements, promotions, customer demographics, and even weather patterns, you can understand how they are affecting the sales. Your strategic decision-making is radically improved. 

3. Are we capturing all the data electronically?

Often the things you want to measure at a strategic level aren't captured electronically at source. This means inefficiencies in manually entering data, increased risk of errors, and lags in information.  

If a business wants to know how store configuration affects sales, it needs a digital record of each store’s configuration and your BI system can then cross-reference this with sales and produce a report.

Mapping out where your data is paper-based or manually captured can identify areas where digital apps could enhance data insights and efficiency, and avoid missing key insights. 

4. Is the data of adequate quality?

Good quality data is standardised data. If your data is inconsistent, the answers you get will be inaccurate.

Imagine if a business wanted to know why they were getting higher recalls than normal on a new product. If different quality controllers are recording the same issue as ‘faulty part Y’ and as ‘product defect Z’, then this variation will make it impossible to get the right answer out of the system.

Putting in system controls to reduce this likelihood make for more accurate data insights.

5. Is our data integrated, aligned and stored and accessed centrally?

If your business’s information is captured in disparate systems then you’ll get disparate answers which take time to manually collate and analyse. By feeding separate data sets into a single data warehouse or BI tool, the power of your data analytics and BI insights will be significantly enhanced.

6. Have we adopted the right BI and data analytics tools?

One of the most powerful motivations for investing in a BI tool is the 'self serve' ability it gives everyone to automatically generate real time reports and portray results in meaningful visualisations.

The right tools reduce the technical know how needed by end users, reducing the reliance on technical developers to build and share new reports, and integrate new data sources.

This puts more power in the hands of business users, and reduces the dependency on central IT to deliver.

7. Is the overall BI initiative likely to be cost effective?

BI initiatives can easily become the tail that wags the dog. Adopt agile development approaches to ensure that you rapidly deliver dashboards and data insights that generate business value, rather than trying shove everything into a data warehouse and then look to get value out of it later.

Start small and look to make incremental progress, rather than trying to design an all encompassing solution that meets every single business requirement.

With a step by step approach you can stop when you've spent enough or where the value has diminished, whereas with a waterfall approach, you may be stuck on an expensive train that you can't get off.

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