Data strategy – two words that are widely used by service providers and organizations of all types, and yet they can mean many different things to different people.
Having encountered quite a few interpretations and versions of “data strategy”, I would like to share our approach at BLeader, which was honed over years of leading dozens of such processes in the organization of all verticals and stages.
First, when we talk about data strategy, we’re referring to 4 key stages that have to take place for the strategy to be relevant: Business strategy, Strategy-oriented data solutions, technological execution plan, and process execution plan.
Stage 1: Business strategy/business consulting, which at its core is the definition of your organization’s business goals which are achievable via data-based solutions. The process may include some changes and tweaks to the internal processes in the organization – from both the business and technology aspects. That’s when we, as the consultants, hold the rope at both ends. We consult on both the business side and the data side – otherwise, our work wouldn’t be justified. The value we bring here is our experience and our understanding across verticals and segments, which enables us to help organizations design business processes in which we can weave data solutions that will lead to tangible business results. In other words, this is the stage when we identify business opportunities and prioritize them.
Stage 2: Strategy-oriented data solution: At this stage, we define and prioritize the various data solutions that we’d like to incorporate into those business processes, and that are meant to deliver the desired value. Some of the solutions may be AI-based and some may be fairly simple. Solutions don’t have to be technologically or methodologically complicated to deliver meaningful value. Sometimes it’s as simple as finding a new data source – which can prove to have an immense impact.
Planning data solutions is a creative process combining our business goals with “bending” the technologies and methodologies and choosing the best way to use the data-based solution to achieve the business target. The consultants have to know the solutions available in the market extremely well in order to build the right jigsaw puzzle for the specific challenge at hand.
We help the organization define solutions in areas like personalization and data-based customer management, automating operational processes, recommendation engines for discounts, operations, content, and even new product lines – based on the customer’s preferences, systems promoting information such as dashboards that can be incorporated into managerial and operational processes, information infrastructures that can accelerate the organization’s response time, new data sources and so on. All of these always have to be according to the strategy set on the first stage.
Stage 3: Technological execution: Most data service providers and consultants stop here. At BLeader, we believe that the technological execution is also part of the consultants’ responsibility. The reason is that recommending solutions is pretty easy, but backing those recommendations and implementing them into the organization, making them a reality, is more challenging. There are many considerations when selecting the right technological solutions and tools: budget, existing technology, and infrastructure – as well as knowing the people and function in the organization who are going to be using the solution and examining their level of readiness for using simple or advanced solutions.
At this stage, we grade the solutions according to the ease of use and cost of implementation on the one hand, and the business and monetary value they can bring on the other hand.
Stage 4: Process execution: This is the most essential stage. The absolute key to success is planning the implementation of the solutions in the organizations and examining change management – as early as creating the data strategy and the technological solutions. Skipping this stage, a large part of the solutions you’ve invested so much in planning and developing is likely to turn into a white elephant. The approach saying you should first plan the strategy and then tackle the implementation plan is wrong and counterproductive.
During this stage, we’ll plot out all the different – and specific – processes in which the data solutions will be incorporated, whether they are automatic or involve decision-making. We’ll check the interfaces between units and departments around the solution, and examine the organization’s ability to execute the solution’s by-products whether it’s a recommendation engine or an engine making information accessible for decision-making purposes.
Leading such processes requires consultants with deep managerial and business knowledge pertaining to the various areas in which the organization is active, combining high technological skills with the ability to deliver, read the organization’s DNA map, and understand what are the success rates for each possible plan, and above all – to become a real partner in stirring these processes from A-Z.
Personally, I find that these processes are immensely fulfilling. There’s nothing like seeing a strategy or a roadmap come to life and turn into new business and revenue lines.
