5 Key Factors for Successful Competitive Analysis
To state the obvious, a winning competitive strategy positions the company in a competitive position in relation to its competitors. To know ‘where’ your competitors are means you need to be ‘watching’ them all the time. This requires companies to have a formal approach to ‘watching’, aka – Competitive Analysis (or Competitive Intelligence).
Competitive Analysis is a component of the bigger process required to develop a Competitive Strategy. Ultimately we’re talking about the collection and synthesising of data relating to the competition, enabling strategists to evaluate and take appropriate action.
Competitive Analysis done well, is an ongoing process of collecting, organising, evaluating, synthesising and communicating data to relevant stakeholders for the purposes of developing and evolving competitive strategies.
These are significant programmes for a business to undertake, meaning the organisation needs to fully understand the necessity of strategy and its role in developing ongoing organisational success – and wholly commit to it.
To be successful (delivering high quality information and strategic insights for the organisation) takes executive support, allocation of resources, long time horizons, planning and infrastructure. This post gives summaries on each of these.
Customer Analysis Programmes need Executive Support
For any programme [of strategic importance] to be successful it requires support from senior decision makers who judge on return on capital investment (ROCI), which typically means executives and directors. Therefore any Competitive Analysis programme will require their support, primarily due to the cost component.
Although Competitive Strategies are vitally important for businesses to win over the longer term (or enter more crowded markets) the lack of a quantifiable return will be a concern to some. Therefore you need more foundational buy-in from a senior executive/director – someone that will support this programme over the longer term, even in the face of early hiccups and costly learnings.
Something important to think about, on a practical level, is that you need to ensure your internal supporters look good and can show their support is delivering value. Therefore, always clarify what success looks like for them, and work hard to deliver a version of it, even if an MVP. If you’re able to show success quickly, this higher-level support will grow over time and you might even recruit more executives to your side of the table.
Recruit the right team to deliver
In order to deliver a strong Competitive Analysis programme you need to recruit the right people to deliver on it. This team will require a diverse set of skills, some of which are likely better ‘rented’ (ie contracted) than ‘bought’ (ie employed).
If you need to build a data pipeline you probably need a data engineer, if you need dashboards to be built using SQL queries you probably want an analyst, if you lack someone to make sense of the information collected you need a competitive strategist.
Once you understand what skills you need to deliver on the programme, you can easily evaluate those you’re lacking and need to recruit. This is the beginning of your functional strategy, and you should consider both consultants and employees to deliver on it.
At Daleth we often advocate for a hybrid approach, meaning you get all the speed and experience of consulting teams, whilst training and developing an internal team of employees to take full ownership at some point in the future. But this decision will largely fall based on velocity desired and resources available.
It’s worth stating there are clear pros and cons associated with both consultants and employees. In general recruiting externally (i.e. using consultants, agencies or freelancers) lets you move very quickly as you can ‘rent’ high quality experience immediately without any legal/employment constraints, but the costs will likely be higher.
Employment, although a far longer process means the business is building its competencies internally thus reducing costs over the longer term and making Competitive Analysis a longer term competitive competency. But, the lack of experience of employees (when compared with consultants) can result in higher costs in the shorter term, whilst the employees up skill.
Either way, you need to resource the requirements – otherwise it will fail.
Long time horizons
Above I stated you need to show results reasonably quickly for tactical reasons – but your own time horizons will need to be longer. Ultimately the process of competitive intelligence does not stop, and so should be delivering value to commercial, data, growth, marketing, software and physical product strategies over time.
The value of Competitive Analysis also compounds over time meaning those with longer term time horizons will produce the biggest results for the organisation. Building strong Competitive Analysis foundations will result in faster reactions to competitor moves (simply put, you will see them earlier), strategies that more successfully intersect strong market trends and produce better results by being positioned in markets and industries with less competition. After all, this is the main focus of a Competitive Strategy.
It’s all about position, and in the words of Wayne Gretzky you need to
‘skate to where the puck is going’…
Because your competition is never static, and always trying to out compete you – you need a long term ‘always on’ approach to Competitive Analysis.
Planning
You might have all the support and resources you need, mixed with very long time horizons – but if you don’t plan your approach to developing a Competitive Analysis programme you will not deliver much of anything.
Planning is simply agreeing on the timing of effort, focus and spend to deliver on agreed deployments. I won’t teach you how to plan a project, but here are some things you should be considering.
1) Who are your competitors?
2) What information do you want to have?
3) What questions do you want answered about your competition’s strategies?
4) What can you deliver quickly that does not require much effort (i.e. the low hanging fruit)?
5) What opportunities can you unlock with certain ‘bits’ of information?
6) What infrastructure components are not deployed within the organisation?
Below are a few general comments about planning these programmes:
What does success look like?
Ensure you have sourced all the questions being asked around the organisation, at all levels of the organisation.
Make sure this vision of success is shared across the organisation, especially if you have any internal sponsors and advocates.
Be very clear on the definition of this success. Don’t be fluffy, be precise – fluffiness can get you killed out here!
Tackle the low hanging fruit first
Understand what data sources, data points and information already exist in the business? Start here, as there are typically so many valuable insights sitting on the other side of an hour of concerted analysis.
Don’t be afraid to challenge existing truths within the business, I would actually say this is a core component of Competitive Analysis. If it’s clear any axioms are false it’s your responsibility to bring them to the table.
Build a roadmap
Understand what infrastructure is required to answer certain questions, and the value of answering those questions. Quantifying the resources required and the value of the outputs helps you more easily prioritise the deployments of new capabilities.
Build clear development requirements, and ensure costs are wholly understood. Take your time here, there is no value in hurrying to start a project or deployment only to find out the problem is less understood and more complex to resolve. Slow down, take a breath, and focus on planning. As was drilled into me when I was younger – ‘piss poor planning leads to piss poor performance’. Amen to that.
Make sure you allocate ownership of projects and deployments to individuals. These ‘responsible persons’ (RPs) have the autonomy to make decisions, but also can and should be held to account for their decisions. This means A+ players can thrive and deliver quality results.
Remain agile
(Although not a part of the planning process) the programme needs to remain agile. As the business navigates forward things will change; competitors will make strategic moves, markets and cost of capital will fluctuate, technology will evolve – meaning the deployment of the plan should remain flexible. We recommend an agile management approach, enabling the core team to re-evaluate priorities and workload periodically.
Working within an agile methodology facilities regular communication and feedback, which reinforces efficient resource allocation. If you’re getting regular, quality feedback on what is and is not working then you can course correct more accurately over time, thus saving time and money.
Data Strategy Infrastructure
You can’t deliver on any sizeable data project without infrastructure. As they say ‘junk in equals junk out’, so a keen awareness of data quality from source to strategy is key.
Mapping the current and planned data pipeline, i.e. what data goes where and how, is vital to ensure team wide understanding on what the vision is, the stages of deployment are, and anticipated outputs at each stage.
Therefore when thinking about infrastructure you should ask at minimum:
- What data sources do you need to answer your questions?
- Are you looking at structured proprietary data, or unstructured publicly available data?
- Are there costs for any relevant API access?
- Does your data need converting and merging to something more valuable (this is modelling)?
- What are your timescales for reaching certain milestones?
Data management tools
The business should build a Single Source of Truth (SSOT) – a single repository of customer (and other data) meaning the rest of the stack is downstream to this SSOT.
This means all integrated systems and teams are working from the same, up to date view of the business’ data, and prevents silos (which ultimately means teams can be working from fundamentally different data sets and building inconsistent axioms across the business).
Below are the core components of any SSOT data stack:
Data sources
There are many types of data source to leverage, so think about what you need to evaluate performance and strategy.
We recommend only building into those you need. Only collect what you plan on using, as it costs to collect and house data.
Are you wanting structured or unstructured data, is it proprietary or nonproprietary etc?
Extract Transfer Load (ETL)
Extract, transfer, load – aka data loaders. Essentially we’re talking about moving data from one source to another without corruption.
Integration is key here, so APIs are your core tool. Unless APIs are your core competency, don’t try to build and maintain proprietary APIs. Instead use an API platform – whose role is to maintain a range of APIs used by the business.
Data Warehouses
Data will need to be securely stored in a structured format. Typically on a database, but there are many occasions when a Google Drive/Dropbox will suffice (typically used when data is unstructured).
Data Modelling Platform
If you’re pulling structured data (and to some extent unstructured data) you will need to model it – which effectively means convert it to something of more value. This requires conceptual, physical and logical data models – meaning what calculations do we want to process of our data?
These new outputs can then be stored in another table or warehouse, providing consistent company wide data points and metrics for further use and evaluation.
Business Intelligence Platforms
With consistent, relevant, data points across the organisation analysts can build both dashboards and run ad hoc analysis. This can provide both consistent performance reporting and a drip feed of constant new insights for synthesis.
With the right tools it is possible for all team members to analyse the data. This is called self-authorship, and although it requires a little more investment to set up, it delivers huge gains across the organisation because anyone can chase their instincts and run highly local (aka relevant) analysis on reliable data points.
And so, summary…
Running ongoing Competitive Analysis enables businesses to remain current, and ‘on-point’ with its Competitive Strategy. Once established they require ongoing resources and development – but the value they provide far outweighs any costs. Before undertaking any Competitive Analysis programme you need higher up executive support to increase the chances of success, to recruit to fill the requirements using either consultants or employees, ensure you have long term time horizons to deliver the value inherent in these programmes, plan plan and plan some more, and new be aware new data infrastructure will likely be required.
So, if you’re ready to take your Competitive Strategy ‘game’ to the next level seriously consider improving your Competitive Analysis. If you’re not 100% sure where to start or you need support or just want a discussion please get in touch, we’d be happy to help.
Recent Comments