How to Align Your Business Strategy with Your Data
Almost every organization in business and government realizes the value of data. As a result, many groups are seeking to build strategies to more effectively use the data at hand.
If your company has begun this process or you’re thinking of starting now, then here are our suggestions on how to best-approach your transformation.
Start from the VERY beginning
You should start by asking “What is our (business) strategy, and how can data support it?”. Working with data should be a means to an end and not an end in and of itself. You should stay true to your core business and implement solutions that are not confusing, burdensome or simply useless.
2. Avoid crafting in isolation--get technology, business teams, and everyone in between ALIGNED
Whatever you decide your strategy to be, it should be communicated between all your teams. Your data approach should foster alignment with the business owners and with the other members of the company. So, if as an experiment, you ask a Java developer in your company and another who is directly responsible for booking revenue (sales, servicemember, etc.), questions like “What data does the firm own?” or “What data does it need?”, should receive similar answers. If not, that is a red alert that your strategy is poorly aligned.
3. Identify Internal Data Practices
Identifying frameworks, both from current practices, and from external firms who indeed, that would be worth imitating.
First, review your current data practices in light of a few questions:
Can we get rid of this practice/tool altogether? This sounds like an obvious statement, but you might be surprised how much time, attention, and energy is given to legacy code and tools which have far surpassed their business value.
Is this practice being done in different ways by different teams in the company? If the practice is inconsistent, seek to standardize it before reinforcing any of the divergent methods used.
Can this practice be improved? If there are obvious lags in the practice, then address them before seeking to broaden the application of the practice.
Can this process be automated? This is a no-brainer. Do not invest in maintaining a practice that could otherwise be automated.
If your current practices fail the above questions, then it’s a good idea to bring in fresh thinking.
4. Be Cautious When Implementing “Supposedly” Best Data Practices from External Firms
Another approach that you could take is looking at what external firms are doing and implementing their practices. But that’s not to say you should blindly do what other companies do. Before implementing practices from other firms, review them in light of a few questions:
1. Does the firm face the same regulatory / oversight pressures as our firm?
While this may seem outside of scope, it’s a great question. If you are in a heavily regulated industry (e.g. finance, life sciences), trying to follow the practices of a firm in an unregulated industry could be problematic. Proceed with caution.
2. Do we have the personnel to implement the practices from the firm in question?
Hiring consultants to train your own team or to buy time while creating your own team is acceptable practice. But do not invest in a practice if you do not already have the people (or plan) in place to implement it.
3. Do we have access to, or intent to use, the same type of data as the firm in question?
Benchmarking against a firm that uses completely different data than your company can set unreasonable expectations. It is worth doing a quick “sanity check” to make sure you aren’t trying to follow a precedent that your company couldn’t reach in any condition, simply because of the type of data your company uses.
Whether you’re looking to align your strategy with the data you have at hand or you want to develop a more data-prone approach, you should start by reviewing your business objectives and understanding how data can impact them. Once you have a clear vision, you should get your entire team involved in the process. This approach allows your company to foster a data-driven mentality and ensures that everything that is developed is understood and used by all your groups. After you address the possibility of designing in isolation, together with your teams, you can identify frameworks internally and from competitors seek to institutionalize best practices.